Relative positions are recent solutions to overcome the limited accuracy of GPS in urban environment.
Vehicle positions obtained using V2I communication are more accurate because the known roadside unit
(RSU) locations help predict errors in measurements over time. The accuracy of vehicle positions depends
more on the number of RSUs; however, the high installation cost limits the use of this approach. It also
depends on nonlinear localization nature. They were neglected in several research papers. In these studies,
the accumulated errors increased with time due to the linearity localization problem. In the present study,
a cooperative localization method based on V2I communication and distance information in vehicular
networks is proposed for improving the estimates of vehicles’ initial positions. This method assumes that
the virtual RSUs based on mobility measurements help reduce installation costs and facilitate in handling
fault environments. The extended Kalman filter algorithm is a well-known estimator in nonlinear problem,
but it requires well initial vehicle position vector and adaptive noise in measurements. Using the proposed
method, vehicles’ initial positions can be estimated accurately. The experimental results confirm that the
proposed method has superior accuracy than existing methods, giving a root mean square error of
approximately 1 m. In addition, it is shown that virtual RSUs can assist in estimating initial positions in
fault environments.
SECURING BGP BY HANDLING DYNAMIC NETWORK BEHAVIOR AND UNBALANCED DATASETSIJCNCJournal
The Border Gateway Protocol (BGP) provides crucial routing information for the Internet infrastructure. A problem with abnormal routing behavior affects the stability and connectivity of the global Internet. The biggest hurdles in detecting BGP attacks are extremely unbalanced data set category distribution and the dynamic nature of the network. This unbalanced class distribution and dynamic nature of the network results in the classifier's inferior performance. In this paper we proposed an efficient approach to properly managing these problems, the proposed approach tackles the unbalanced classification of datasets by turning the problem of binary classification into a problem of multiclass classification. This is achieved by splitting the majority-class samples evenly into multiple segments using Affinity Propagation, where the number of segments is chosen so that the number of samples in any segment closely matches the minority-class samples. Such sections of the dataset together with the minor class are then viewed as different classes and used to train the Extreme Learning Machine (ELM). The RIPE and BCNET datasets are used to evaluate the performance of the proposed technique. When no feature selection is used, the proposed technique improves the F1 score by 1.9% compared to state-of-the-art techniques. With the Fischer feature selection algorithm, the proposed algorithm achieved the highest F1 score of 76.3%, which was a 1.7% improvement over the compared ones. Additionally, the MIQ feature selection technique improves the accuracy by 3.5%. For the BCNET dataset, the proposed technique improves the F1 score by 1.8% for the Fisher feature selection technique. The experimental findings support the substantial improvement in performance from previous approaches by the new technique.
UTILIZING XAI TECHNIQUE TO IMPROVE AUTOENCODER BASED MODEL FOR COMPUTER NETWO...IJCNCJournal
Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in computer network security, such as fraud detection, network anomaly detection, intrusion detection, and much more. However, the lack of transparency of ML and DL based models is a major obstacle to their implementation and criticized due to its black-box nature, even with such tremendous results. Explainable Artificial Intelligence (XAI) is a promising area that can improve the trustworthiness of these models by giving explanations and interpreting its output. If the internal working of the ML and DL based models is understandable, then it can further help to improve its performance. The objective of this paper is to show that how XAI can be used to interpret the results of the DL model, the autoencoder in this case. And, based on the interpretation, we improved its performance for computer network anomaly detection. The kernel SHAP method, which is based on the shapley values, is used as a novel feature selection technique. This method is used to identify only those features that are actually causing the anomalous behaviour of the set of attack/anomaly instances. Later, these feature sets are used to train and validate the autoencoderbut on benign data only. Finally, the built SHAP_Model outperformed the other two models proposed based on the feature selection method. This whole experiment is conducted on the subset of the latest CICIDS2017 network dataset. The overall accuracy and AUC of SHAP_Model is 94% and 0.969, respectively.
MEKDA: Multi-Level ECC based Key Distribution and Authentication in Internet ...IJCNCJournal
The Internet of Things (IoT) is an extensive system of networks and connected devices with minimal human interaction and swift growth. The constraints of the System and limitations of Devices pose several challenges, including security; hence billions of devices must protect from attacks and compromises. The resource-constrained nature of IoT devices amplifies security challenges. Thus standard data communication and security measures are inefficient in the IoT environment. The ubiquity of IoT devices and their deployment in sensitive applications increase the vulnerability of any security breaches to risk lives. Hence, IoT-related security challenges are of great concern. Authentication is the solution to the vulnerability of a malicious device in the IoT environment. The proposed Multi-level Elliptic Curve Cryptography based Key Distribution and Authentication in IoT enhances the security by Multi-level Authentication when the devices enter or exit the Cluster in an IoT system. The decreased Computation Time and Energy Consumption by generating and distributing Keys using Elliptic Curve Cryptography extends the availability of the IoT devices. The Performance analysis shows the improvement over the Fast Authentication and Data Transfer method.
Privacy Preserving Reputation Calculation in P2P Systems with Homomorphic Enc...IJCNCJournal
In this paper, we consider the problem of calculating the node reputation in a Peer-toPeer (P2P) system from fragments of partial knowledge concerned with the trustfulness of nodes which are subjectively given by each node (i.e., evaluator) participating in the system. We are particularly interested in the distributed processing of the calculation of reputation scores while preserving the privacy of evaluators. The basic idea of the proposed method is to extend the EigenTrust reputation management system with the notion of homomorphic cryptosystem. More specifically, it calculates the main eigenvector of a linear system which models the trustfulness of the users (nodes) in the P2P system in a distributed manner, in such a way that: 1) it blocks accesses to the trust value by the nodes to have the secret key used for the decryption, 2) it improves the efficiency of calculation by offloading a part of the task to the participating nodes, and 3) it uses different public keys during the calculation to improve the robustness against the leave of nodes. The performance of the proposed method is evaluated through numerical calculations.
BER ANALYSIS FOR DOWNLINK MIMO-NOMA SYSTEMS OVER RAYLEIGH FADING CHANNELSIJCNCJournal
The Multiple-input multiple-output (MIMO) technique combined with non-orthogonal multiple access (NOMA) has been considered to enhance total system performance. This paper studies the bit error rate of two-user power-domain NOMA systems using successive interference cancellation receivers, with zeroforcing equalization over quasi-static Rayleigh fading channels. Successive interference cancellation technique at NOMA receivers has been the popular research topic due to its simple implementation, despite its vulnerability to error propagation. Closed-form expressions are derived for downlink NOMA in single-input single-output and uncorrelated quasi-static MIMO Rayleigh fading channel. Analytical results are consolidated with Monte Carlo simulation.
FUZZY LOGIC-BASED EFFICIENT MESSAGE ROUTE SELECTION METHOD TO PROLONG THE NET...IJCNCJournal
Recently, sensor networks have been used in a wide range of applications, and interest in sensor node
performance has increased. A sensor network is composed of tiny nodes with limited resources. The sensor
network communicates between nodes in a configured network through self-organization. An energyefficient security protocol with a hierarchy structure with various advantages has been proposed to
prolong the network lifetime of sensor networks. But due to structural problems in traditional protocols,
nodes located upstream tend to consume relatively high energy compared to other nodes. A network
protocol should be considered to provide minimal security and efficient allocation of energy consumption
by nodes to increase the network lifetime. In this paper, we introduce a solution to solve the bottleneck
problem through an efficient message route selection method. The proposed method selects an efficient
messaging path using GA and fuzzy logic composed of multiple rules. Message route selection plays an
important role in controlling the load balancing of nodes. A principal benefit of the proposed scheme is the
potential portability of the clustering-based protocol. In addition, the proposed method is updated to find
the optimal path through the genetic algorithm to respond to various environments. We demonstrated the
effectiveness of the proposed method through an experiment in which the proposed method is applied to a
probabilistic voting-based filtering scheme that is one of the cluster-based security schemes.
Approximation of regression-based fault minimization for network trafficTELKOMNIKA JOURNAL
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
SECURING BGP BY HANDLING DYNAMIC NETWORK BEHAVIOR AND UNBALANCED DATASETSIJCNCJournal
The Border Gateway Protocol (BGP) provides crucial routing information for the Internet infrastructure. A problem with abnormal routing behavior affects the stability and connectivity of the global Internet. The biggest hurdles in detecting BGP attacks are extremely unbalanced data set category distribution and the dynamic nature of the network. This unbalanced class distribution and dynamic nature of the network results in the classifier's inferior performance. In this paper we proposed an efficient approach to properly managing these problems, the proposed approach tackles the unbalanced classification of datasets by turning the problem of binary classification into a problem of multiclass classification. This is achieved by splitting the majority-class samples evenly into multiple segments using Affinity Propagation, where the number of segments is chosen so that the number of samples in any segment closely matches the minority-class samples. Such sections of the dataset together with the minor class are then viewed as different classes and used to train the Extreme Learning Machine (ELM). The RIPE and BCNET datasets are used to evaluate the performance of the proposed technique. When no feature selection is used, the proposed technique improves the F1 score by 1.9% compared to state-of-the-art techniques. With the Fischer feature selection algorithm, the proposed algorithm achieved the highest F1 score of 76.3%, which was a 1.7% improvement over the compared ones. Additionally, the MIQ feature selection technique improves the accuracy by 3.5%. For the BCNET dataset, the proposed technique improves the F1 score by 1.8% for the Fisher feature selection technique. The experimental findings support the substantial improvement in performance from previous approaches by the new technique.
UTILIZING XAI TECHNIQUE TO IMPROVE AUTOENCODER BASED MODEL FOR COMPUTER NETWO...IJCNCJournal
Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in computer network security, such as fraud detection, network anomaly detection, intrusion detection, and much more. However, the lack of transparency of ML and DL based models is a major obstacle to their implementation and criticized due to its black-box nature, even with such tremendous results. Explainable Artificial Intelligence (XAI) is a promising area that can improve the trustworthiness of these models by giving explanations and interpreting its output. If the internal working of the ML and DL based models is understandable, then it can further help to improve its performance. The objective of this paper is to show that how XAI can be used to interpret the results of the DL model, the autoencoder in this case. And, based on the interpretation, we improved its performance for computer network anomaly detection. The kernel SHAP method, which is based on the shapley values, is used as a novel feature selection technique. This method is used to identify only those features that are actually causing the anomalous behaviour of the set of attack/anomaly instances. Later, these feature sets are used to train and validate the autoencoderbut on benign data only. Finally, the built SHAP_Model outperformed the other two models proposed based on the feature selection method. This whole experiment is conducted on the subset of the latest CICIDS2017 network dataset. The overall accuracy and AUC of SHAP_Model is 94% and 0.969, respectively.
MEKDA: Multi-Level ECC based Key Distribution and Authentication in Internet ...IJCNCJournal
The Internet of Things (IoT) is an extensive system of networks and connected devices with minimal human interaction and swift growth. The constraints of the System and limitations of Devices pose several challenges, including security; hence billions of devices must protect from attacks and compromises. The resource-constrained nature of IoT devices amplifies security challenges. Thus standard data communication and security measures are inefficient in the IoT environment. The ubiquity of IoT devices and their deployment in sensitive applications increase the vulnerability of any security breaches to risk lives. Hence, IoT-related security challenges are of great concern. Authentication is the solution to the vulnerability of a malicious device in the IoT environment. The proposed Multi-level Elliptic Curve Cryptography based Key Distribution and Authentication in IoT enhances the security by Multi-level Authentication when the devices enter or exit the Cluster in an IoT system. The decreased Computation Time and Energy Consumption by generating and distributing Keys using Elliptic Curve Cryptography extends the availability of the IoT devices. The Performance analysis shows the improvement over the Fast Authentication and Data Transfer method.
Privacy Preserving Reputation Calculation in P2P Systems with Homomorphic Enc...IJCNCJournal
In this paper, we consider the problem of calculating the node reputation in a Peer-toPeer (P2P) system from fragments of partial knowledge concerned with the trustfulness of nodes which are subjectively given by each node (i.e., evaluator) participating in the system. We are particularly interested in the distributed processing of the calculation of reputation scores while preserving the privacy of evaluators. The basic idea of the proposed method is to extend the EigenTrust reputation management system with the notion of homomorphic cryptosystem. More specifically, it calculates the main eigenvector of a linear system which models the trustfulness of the users (nodes) in the P2P system in a distributed manner, in such a way that: 1) it blocks accesses to the trust value by the nodes to have the secret key used for the decryption, 2) it improves the efficiency of calculation by offloading a part of the task to the participating nodes, and 3) it uses different public keys during the calculation to improve the robustness against the leave of nodes. The performance of the proposed method is evaluated through numerical calculations.
BER ANALYSIS FOR DOWNLINK MIMO-NOMA SYSTEMS OVER RAYLEIGH FADING CHANNELSIJCNCJournal
The Multiple-input multiple-output (MIMO) technique combined with non-orthogonal multiple access (NOMA) has been considered to enhance total system performance. This paper studies the bit error rate of two-user power-domain NOMA systems using successive interference cancellation receivers, with zeroforcing equalization over quasi-static Rayleigh fading channels. Successive interference cancellation technique at NOMA receivers has been the popular research topic due to its simple implementation, despite its vulnerability to error propagation. Closed-form expressions are derived for downlink NOMA in single-input single-output and uncorrelated quasi-static MIMO Rayleigh fading channel. Analytical results are consolidated with Monte Carlo simulation.
FUZZY LOGIC-BASED EFFICIENT MESSAGE ROUTE SELECTION METHOD TO PROLONG THE NET...IJCNCJournal
Recently, sensor networks have been used in a wide range of applications, and interest in sensor node
performance has increased. A sensor network is composed of tiny nodes with limited resources. The sensor
network communicates between nodes in a configured network through self-organization. An energyefficient security protocol with a hierarchy structure with various advantages has been proposed to
prolong the network lifetime of sensor networks. But due to structural problems in traditional protocols,
nodes located upstream tend to consume relatively high energy compared to other nodes. A network
protocol should be considered to provide minimal security and efficient allocation of energy consumption
by nodes to increase the network lifetime. In this paper, we introduce a solution to solve the bottleneck
problem through an efficient message route selection method. The proposed method selects an efficient
messaging path using GA and fuzzy logic composed of multiple rules. Message route selection plays an
important role in controlling the load balancing of nodes. A principal benefit of the proposed scheme is the
potential portability of the clustering-based protocol. In addition, the proposed method is updated to find
the optimal path through the genetic algorithm to respond to various environments. We demonstrated the
effectiveness of the proposed method through an experiment in which the proposed method is applied to a
probabilistic voting-based filtering scheme that is one of the cluster-based security schemes.
Approximation of regression-based fault minimization for network trafficTELKOMNIKA JOURNAL
This research associates three distinct approaches for computer network traffic prediction. They are the traditional stochastic gradient descent (SGD) using a few random samplings instead of the complete dataset for each iterative calculation, the gradient descent algorithm (GDA) which is a well-known optimization approach in deep learning, and the proposed method. The network traffic is computed from the traffic load (data and multimedia) of the computer network nodes via the Internet. It is apparent that the SGD is a modest iteration but can conclude suboptimal solutions. The GDA is a complicated one, can function more accurate than the SGD but difficult to manipulate parameters, such as the learning rate, the dataset granularity, and the loss function. Network traffic estimation helps improve performance and lower costs for various applications, such as an adaptive rate control, load balancing, the quality of service (QoS), fair bandwidth allocation, and anomaly detection. The proposed method confirms optimal values out of parameters using simulation to compute the minimum figure of specified loss function in each iteration.
STUDY OF DISTANCE MEASUREMENT TECHNIQUES IN CONTEXT TO PREDICTION MODEL OF WE...ijscai
Internet is the boon in modern era as every organization uses it for dissemination of information and ecommerce
related applications. Sometimes people of organization feel delay while accessing internet in
spite of proper bandwidth. Prediction model of web caching and prefetching is an ideal solution of this
delay problem. Prediction model analysing history of internet user from server raw log files and determine
future sequence of web objects and placed all web objects to nearer to the user so access latency could be
reduced to some extent and problem of delay is to be solved. To determine sequence of future web objects,
it is necessary to determine proximity of one web object with other by identifying proper distance metric
technique related to web caching and prefetching. This paper studies different distance metric techniques
and concludes that bio informatics based distance metric techniques are ideal in context to Web Caching
and Web Prefetching
Improved Routing Protocol in Mobile Ad Hoc Networks Using Fuzzy LogicTELKOMNIKA JOURNAL
In mobile ad hoc networks, route selection is one of the most important issues that is studied in
these networks as a field of research. Many articles trying to provide solutions to choose the best path in
which the important parameters such as power consumption, bandwidth and mobility are used. In this
article, in order to improve the solutions presented in recent papers parameters such as power remaining,
mobility, degree node and available bandwidth are used by taking the factors for each parameter in
proportion to its influence in choosing the best path. Finally, we compare the proposed solution with the
three protocols IAOMDV-F, AODVFART and FLM-AODV with the help of OPNET simulation program
based on network throughput, routing discovery time, the average number of hops per route, network
delay.
Efficient IOT Based Sensor Data Analysis in Wireless Sensor Networks with Cloudiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Security based Clock Synchronization technique in Wireless Sensor Network for...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Adaptive Routing in Wireless Sensor Networks: QoS Optimisation for Enhanced A...M H
One of the key challenges for research in wireless sensor networks is the development of routing protocols that provide application-specific service guarantees. This paper presents a new cluster-based Route Optimisation and Load-balancing protocol, called ROL, that uses various quality of service (QoS) metrics to meet application requirements. ROL combines several application requirements, specifically it attempts to provide an inclusive solution to prolong network life, provide timely message delivery and improve network robustness. It uses a combination of routing metrics that can be configured according to the priorities of user-level applications to improve overall network performance. To this end, an optimisation tool for balancing the communication resources for the constraints and priorities of user applications has been developed and Nutrient-flow-based Distributed Clustering (NDC), an algorithm for load balancing is proposed. NDC works seamlessly with any clustering algorithm to equalise, as far as possible, the diameter and the membership of clusters. This paper presents simulation results to show that ROL/NDC gives a higher network lifetime than other similar schemes, such Mires++. In simulation, ROL/NDC maintains a maximum of 7\% variation from the optimal cluster population, reduces the total number of set-up messages by up to 60%, reduces the end-to-end delay by up to 56%, and enhances the data delivery ratio by up to 0.98% compared to Mires++.
Map as a Service: A Framework for Visualising and Maximising Information Retu...M H
This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service.
DATA FORWARDING IN OPPORTUNISTIC NETWORK USING MOBILE TRACEScscpconf
Opportunistic networks are usually formed spontaneously by mobile devices equipped with
short range wireless communication interfaces. The idea is that an end-to-end connection may
never be present. Designing and implementing a routing protocol to support both service
discovery and delivery in such kinds of networks is a challenging problem on account of
frequent disconnections and topology changes. In these networks one of the most important
issues relies on the selection of the best intermediate node to forward the messages towards the
destination. This paper presents a mobile trace based routing protocol that uses the location
information of the nodes in the network. Using the trace information, next hop is selected to forward the packets to destination. Data forwarding is done via the selected nodes. The effectiveness is shown using simulation
Information Extraction from Wireless Sensor Networks: System and ApproachesM H
Recent advances in wireless communication have made it possible to develop low-cost, and low power Wireless Sensor Networks (WSN). The WSN can be used for several application areas (e.g., habitat monitoring, forest fire detection, and health care). WSN Information Extraction (IE) techniques can be classified into four categories depending on the factors that drive data acquisition: event-driven, time-driven, query-based, and hybrid. This paper presents a survey of the state-of-the-art IE techniques in WSNs. The benefits and shortcomings of different IE approaches are presented as motivation for future work into automatic hybridization and adaptation of IE mechanisms.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Providing A Network Encryption Approach to reduce end-to-end Delay in MANETEditor IJCATR
A lot of research has been done on different coding techniques and benefits of their use in wired networks Since
network coding was raised as a basic method for increasing network outpouring and reaching the capacity of
networks. However, wireless networks are suffering from low operating power as the use of NC concept in
MANET principally improves throughput rate in the wireless network .
The delay can be considered as an important parameter in networks and system delayed is not acceptable in
these networks. However, the acceptable delay depends on the application although the efficiency and
throughput leads to an increase in network coding , a reduction in bandwidth consumption, and a delay in
sending packets is reduced by using network coding. In this study, a method is proposed for coding in the
MANET, decreasing the number of sent packets, leading to a reduction in that dela
Genetic Algorithm for Vertical Handover (GAfVH)in a Heterogeneous networksIJECEIAES
The fifth generation (5G) wireless system will deal with the growing demand of new multimedia and broadband application. The 5G network architecture is based on heterogeneous Radio Access Technologies (RATs). In such implementation the Vertical handover is a key issue. Up till now, systems are using simple mechanisms to make handover decision, based on the evaluation of the Received Signal Strength (RSS). In some cases these mechanisms are not Efficient.This paper presents a new vertical handover algorithm based on Genetic Algorithm (GAfVH). It aims to reduce the number of unnecessary handovers, and optimizes the system performance. We compare our simulation results to the Received Signal Strength (RSS) based method. The results show that the number of handovers decreases. Moreover, we demonstrate that the network selection result can differ from an application to another.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Online stream mining approach for clustering network trafficeSAT Journals
Abstract A large number of research have been proposed on intrusion detection system, which leads to the implementation of agent based intelligent IDS (IIDS), Non – intelligent IDS (NIDS), signature based IDS etc. While building such IDS models, learning algorithms from flow of network traffic plays crucial role in accuracy of IDS systems. The proposed work focuses on implementing the novel method to cluster network traffic which eliminates the limitations in existing online clustering algorithms and prove the robustness and accuracy over large stream of network traffic arriving at extremely high rate. We compare the existing algorithm with novel methods to analyse the accuracy and complexity. Keywords— NIDS, Data Stream Mining, Online Clustering, RAH algorithm, Online Efficient Incremental Clustering algorithm
Linear regression models with autoregressive integrated moving average errors...IJECEIAES
The autoregressive integrated moving average (ARIMA) method has been used to model global navigation satellite systems (GNSS) measurement errors. Most ARIMA error models describe time series data of static GNSS receivers. Its application for modeling of GNSS under dynamic tests is not evident. In this paper, we aim to describe real time kinematic-GNSS (RTKGNSS) errors during dynamic tests using linear regression with ARIMA errors to establish a proof of concept via simulation that measurement errors along a trajectory logged by the RTK-GNSS can be “filtered”, which will result in improved positioning accuracy. Three sets of trajectory data of an RTK-GNSS logged in a multipath location were collected. Preliminary analysis on the data reveals the inability of the RTK-GNSS to achieve fixed integer solution most of the time, along with the presence of correlated noise in the error residuals. The best linear regression models with ARIMA errors for each data set were identified using the Akaike information criterion (AIC). The models were implemented via simulations to predict improved coordinate points. Evaluation on model residuals using autocorrelation, partial correlation, scatter plot, quantile-quantile (QQ) plot and histogram indicated that the models fitted the data well. Mean absolute errors were improved by up to 57.35% using the developed models.
STUDY OF DISTANCE MEASUREMENT TECHNIQUES IN CONTEXT TO PREDICTION MODEL OF WE...ijscai
Internet is the boon in modern era as every organization uses it for dissemination of information and ecommerce
related applications. Sometimes people of organization feel delay while accessing internet in
spite of proper bandwidth. Prediction model of web caching and prefetching is an ideal solution of this
delay problem. Prediction model analysing history of internet user from server raw log files and determine
future sequence of web objects and placed all web objects to nearer to the user so access latency could be
reduced to some extent and problem of delay is to be solved. To determine sequence of future web objects,
it is necessary to determine proximity of one web object with other by identifying proper distance metric
technique related to web caching and prefetching. This paper studies different distance metric techniques
and concludes that bio informatics based distance metric techniques are ideal in context to Web Caching
and Web Prefetching
Improved Routing Protocol in Mobile Ad Hoc Networks Using Fuzzy LogicTELKOMNIKA JOURNAL
In mobile ad hoc networks, route selection is one of the most important issues that is studied in
these networks as a field of research. Many articles trying to provide solutions to choose the best path in
which the important parameters such as power consumption, bandwidth and mobility are used. In this
article, in order to improve the solutions presented in recent papers parameters such as power remaining,
mobility, degree node and available bandwidth are used by taking the factors for each parameter in
proportion to its influence in choosing the best path. Finally, we compare the proposed solution with the
three protocols IAOMDV-F, AODVFART and FLM-AODV with the help of OPNET simulation program
based on network throughput, routing discovery time, the average number of hops per route, network
delay.
Efficient IOT Based Sensor Data Analysis in Wireless Sensor Networks with Cloudiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Security based Clock Synchronization technique in Wireless Sensor Network for...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Adaptive Routing in Wireless Sensor Networks: QoS Optimisation for Enhanced A...M H
One of the key challenges for research in wireless sensor networks is the development of routing protocols that provide application-specific service guarantees. This paper presents a new cluster-based Route Optimisation and Load-balancing protocol, called ROL, that uses various quality of service (QoS) metrics to meet application requirements. ROL combines several application requirements, specifically it attempts to provide an inclusive solution to prolong network life, provide timely message delivery and improve network robustness. It uses a combination of routing metrics that can be configured according to the priorities of user-level applications to improve overall network performance. To this end, an optimisation tool for balancing the communication resources for the constraints and priorities of user applications has been developed and Nutrient-flow-based Distributed Clustering (NDC), an algorithm for load balancing is proposed. NDC works seamlessly with any clustering algorithm to equalise, as far as possible, the diameter and the membership of clusters. This paper presents simulation results to show that ROL/NDC gives a higher network lifetime than other similar schemes, such Mires++. In simulation, ROL/NDC maintains a maximum of 7\% variation from the optimal cluster population, reduces the total number of set-up messages by up to 60%, reduces the end-to-end delay by up to 56%, and enhances the data delivery ratio by up to 0.98% compared to Mires++.
Map as a Service: A Framework for Visualising and Maximising Information Retu...M H
This paper presents a distributed information extraction and visualisation service, called the mapping service, for maximising information return from large-scale wireless sensor networks. Such a service would greatly simplify the production of higher-level, information-rich, representations suitable for informing other network services and the delivery of field information visualisations. The mapping service utilises a blend of inductive and deductive models to map sense data accurately using externally available knowledge. It utilises the special characteristics of the application domain to render visualisations in a map format that are a precise reflection of the concrete reality. This service is suitable for visualising an arbitrary number of sense modalities. It is capable of visualising from multiple independent types of the sense data to overcome the limitations of generating visualisations from a single type of sense modality. Furthermore, the mapping service responds dynamically to changes in the environmental conditions, which may affect the visualisation performance by continuously updating the application domain model in a distributed manner. Finally, a distributed self-adaptation function is proposed with the goal of saving more power and generating more accurate data visualisation. We conduct comprehensive experimentation to evaluate the performance of our mapping service and show that it achieves low communication overhead, produces maps of high fidelity, and further minimises the mapping predictive error dynamically through integrating the application domain model in the mapping service.
DATA FORWARDING IN OPPORTUNISTIC NETWORK USING MOBILE TRACEScscpconf
Opportunistic networks are usually formed spontaneously by mobile devices equipped with
short range wireless communication interfaces. The idea is that an end-to-end connection may
never be present. Designing and implementing a routing protocol to support both service
discovery and delivery in such kinds of networks is a challenging problem on account of
frequent disconnections and topology changes. In these networks one of the most important
issues relies on the selection of the best intermediate node to forward the messages towards the
destination. This paper presents a mobile trace based routing protocol that uses the location
information of the nodes in the network. Using the trace information, next hop is selected to forward the packets to destination. Data forwarding is done via the selected nodes. The effectiveness is shown using simulation
Information Extraction from Wireless Sensor Networks: System and ApproachesM H
Recent advances in wireless communication have made it possible to develop low-cost, and low power Wireless Sensor Networks (WSN). The WSN can be used for several application areas (e.g., habitat monitoring, forest fire detection, and health care). WSN Information Extraction (IE) techniques can be classified into four categories depending on the factors that drive data acquisition: event-driven, time-driven, query-based, and hybrid. This paper presents a survey of the state-of-the-art IE techniques in WSNs. The benefits and shortcomings of different IE approaches are presented as motivation for future work into automatic hybridization and adaptation of IE mechanisms.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Providing A Network Encryption Approach to reduce end-to-end Delay in MANETEditor IJCATR
A lot of research has been done on different coding techniques and benefits of their use in wired networks Since
network coding was raised as a basic method for increasing network outpouring and reaching the capacity of
networks. However, wireless networks are suffering from low operating power as the use of NC concept in
MANET principally improves throughput rate in the wireless network .
The delay can be considered as an important parameter in networks and system delayed is not acceptable in
these networks. However, the acceptable delay depends on the application although the efficiency and
throughput leads to an increase in network coding , a reduction in bandwidth consumption, and a delay in
sending packets is reduced by using network coding. In this study, a method is proposed for coding in the
MANET, decreasing the number of sent packets, leading to a reduction in that dela
Genetic Algorithm for Vertical Handover (GAfVH)in a Heterogeneous networksIJECEIAES
The fifth generation (5G) wireless system will deal with the growing demand of new multimedia and broadband application. The 5G network architecture is based on heterogeneous Radio Access Technologies (RATs). In such implementation the Vertical handover is a key issue. Up till now, systems are using simple mechanisms to make handover decision, based on the evaluation of the Received Signal Strength (RSS). In some cases these mechanisms are not Efficient.This paper presents a new vertical handover algorithm based on Genetic Algorithm (GAfVH). It aims to reduce the number of unnecessary handovers, and optimizes the system performance. We compare our simulation results to the Received Signal Strength (RSS) based method. The results show that the number of handovers decreases. Moreover, we demonstrate that the network selection result can differ from an application to another.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Online stream mining approach for clustering network trafficeSAT Journals
Abstract A large number of research have been proposed on intrusion detection system, which leads to the implementation of agent based intelligent IDS (IIDS), Non – intelligent IDS (NIDS), signature based IDS etc. While building such IDS models, learning algorithms from flow of network traffic plays crucial role in accuracy of IDS systems. The proposed work focuses on implementing the novel method to cluster network traffic which eliminates the limitations in existing online clustering algorithms and prove the robustness and accuracy over large stream of network traffic arriving at extremely high rate. We compare the existing algorithm with novel methods to analyse the accuracy and complexity. Keywords— NIDS, Data Stream Mining, Online Clustering, RAH algorithm, Online Efficient Incremental Clustering algorithm
Linear regression models with autoregressive integrated moving average errors...IJECEIAES
The autoregressive integrated moving average (ARIMA) method has been used to model global navigation satellite systems (GNSS) measurement errors. Most ARIMA error models describe time series data of static GNSS receivers. Its application for modeling of GNSS under dynamic tests is not evident. In this paper, we aim to describe real time kinematic-GNSS (RTKGNSS) errors during dynamic tests using linear regression with ARIMA errors to establish a proof of concept via simulation that measurement errors along a trajectory logged by the RTK-GNSS can be “filtered”, which will result in improved positioning accuracy. Three sets of trajectory data of an RTK-GNSS logged in a multipath location were collected. Preliminary analysis on the data reveals the inability of the RTK-GNSS to achieve fixed integer solution most of the time, along with the presence of correlated noise in the error residuals. The best linear regression models with ARIMA errors for each data set were identified using the Akaike information criterion (AIC). The models were implemented via simulations to predict improved coordinate points. Evaluation on model residuals using autocorrelation, partial correlation, scatter plot, quantile-quantile (QQ) plot and histogram indicated that the models fitted the data well. Mean absolute errors were improved by up to 57.35% using the developed models.
Vehicle positioning in urban environments using particle filtering-based glob...IJECEIAES
This article presents a new method for land vehicle navigation using global positioning system (GPS), dead reckoning sensor (DR), and digital road map information, particularly in urban environments where GPS failures can occur. The odometer sensors and map measure can be used to provide continuous navigation and correct the vehicle location in the presence of GPS masking. To solve this estimation problem for vehicle navigation, we propose to use particle filtering for GPS/odometer/map integration. The particle filter is a method based on the Bayesian estimation technique and the Monte Carlo method, which deals with non-linear models and is not limited to Gaussian statistics. When the GPS sensor cannot provide a location due to the number of satellites in view, the filter fuses the limited GPS pseudo-range data to enhance the vehicle positioning. The developed filter is then tested in a transportation network scenario in the presence of GPS failures, which shows the advantages of the proposed approach for vehicle location compared to the extended Kalman filter.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
GPSFR: GPS-Free Routing Protocol for Vehicular Networks with Directional Ante...ijwmn
Efficient and practical communications between large numbers of vehicles are critical in providing high level of safety and convenience to drivers. Crucial real-time information on road hazard, traffic conditions and driver services must be communicated to vehicles rapidly even in adverse environments, such as “urban canyons” and tunnels. We propose a novel routing protocol in vehicular networks that does not require position information (e.g. from GPS) but instead rely on relative position that can be determined dynamically. This GPS-Free Geographic Routing (GPSFR) protocol uses the estimated relative position of vehicles and greedily chooses the best next hop neighbor based on a Balance Advance (BADV) metric which balances between proximity and link stability in order to improve routing performance. In this paper, we focuses primarily on the complexity of routing in highways and solves routing problems that arise when vehicles are near interchanges, curves, and merge or exit lanes of highways. Our simulation results show that by taking relative velocity into account, GPSFR reduces link breakage to only 27% that of GPSR in the dense network. Consequently, GPSFR outperforms GPSR in terms of higher data delivery ratio, lower delay, less sensitivity of the network density and route paths’length
Mechanization and error analysis of aiding systems in civilian and military v...ijctcm
In present scenario GPS is widely used to provide extremely accurate position information for navigation.
From, where the GPS does not give continuous localization in environments where signal blockages are
present, Inertial Navigation System comes into action. Because of sensors present in INS and time
integration process, errors get accumulated over time. Henceforth, an aiding system is integrated with INS.
The aim of this paper is to model VMS and RADAR and aid it with INS in order to overcome its errors. VMS
is aided to INS to achieve acceptable accuracy and ease of implementation, much needed in civilian
navigation. Different trajectories are generated to offer solutions in a practical scenario. Whereas, for
highly accurate positioning in military navigation a reliable aiding system, Radar has been opted. The
Kalman filter is designed and modeled as the integrating element in INS/RADAR, to provide an optimal
estimate of navigation solutions. An error analysis has been done for both INS aided VMS and INS aided
Radar systems. The navigation performance of VMS and Radar aiding system is compared and their merits
have been brought out. We besides give the readers a more honest insight of the demand for an aiding
system in different environments based on various simulation results
A dynamic cruise control system for effective navigation system IJECEIAES
With the fast development of artificial intelligence, robotics, and embedded system along with sensor technologies, the speed control mechanism is required in various other applications such as automatic or self-piloting aircraft, auto-driven vehicles, auto driven lifts and much other robotics based automation plants, etc. For each unpredictable and progressed vehicular framework accompanies a better route that is fit for utilizing the two GPS and INS related sign. There have been a noteworthy number of research works being completed towards creating sliding mode control framework. In case of inaccurate navigational data or no availability of navigational service, the cruise control could also stop working. Hence, there is a need to evolve up with a novel system offering reliable and fault tolerant navigation system in order to minimize the dependencies on GPS-based information and maximize the utilization of INS based information. This manuscript presents a dynamic cruise control system to achieve better navigation under uncertainties. The performance of the system is analyzed by incorporating sliding mode and fuzzy logic and achieves better accuracy in tracking error, computational complexity (28 sec of simulation time) under chattering and switching action operation.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper way to predict the traffic and recommend the best route considering the time factor and the people’s satisfaction on various transportation methods. Therefore, in this research using location awareness applications installed in mobile devices, data related to user mobility were collected by using crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to overcome the problem. By using this, the best transportation method can be predicted as the results of the research. Therefore, people can choose what will be the best time slots & transportation methods when planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
APPLICABILITY OF CROWD SOURCING TO DETERMINE THE BEST TRANSPORTATION METHOD B...IJDKP
Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper
way to predict the traffic and recommend the best route considering the time factor and the people’s
satisfaction on various transportation methods. Therefore, in this research using location awareness
applications installed in mobile devices, data related to user mobility were collected by using
crowdsourcing techniques and studied. Based on these observations an algorithm has been developed to
overcome the problem. By using this, the best transportation method can be predicted as the results of the
research. Therefore, people can choose what will be the best time slots & transportation methods when
planning journeys. Throughout this research it has been proven that for the Sri Lankan context, the data mining concepts together with crowdsourcing can be applied to determine the best transportation method.
Geometric sensitivity of beacon placement using airborne mobile anchorsjournalBEEI
Locating fixed sensing devices with a mobile anchor is attractive for covering larger deployment areas. However, the performance sensitivity to the geometric arrangement of anchor beacon positions remains unexplored. Therefore, localization using new RSSI-based localization algorithm, which uses a volumetric probability distribution function is proposed to find the most likely position of a node by information fusion from several mobile beacon radio packets to reduce error over deterministic approaches. This paper presents the guidelines of beacon selection that leads to design the most suitable trajectory, as a trade-off between the energy costs of travelling and transmitting the beacons versus the localization accuracy.
Performance Evaluation of GPSR Routing Protocol for VANETs using Bi-direction...CSCJournals
Routing in Vehicular Adhoc Networks is a challenging task where the nodes themselves are vehicles. The mobility factors such as beacon intervals and vehicles with different velocities may cause inaccuracy in the identification of the vehicle's position. This in turn affects the performance of the position based routing protocols. Further, there is a need to evaluate through simulations performance of the position based routing protocol, especially in urban realistic scenarios for VANETs. The work in this paper evaluates the performance of Greedy Perimeter Stateless Routing protocol (GPSR) for VANETs which is a popular position based protocol especially for routing in MANETs. In order to evaluate realistic simulation environment bi-directional coupling of OMNET++/ INET Framework and SUMO is chosen for Nagarbhavi region in Bengaluru, India. The simulations are done for various scenarios realizing the impact of mobility parameters on routing using GPSR, and performance is measured in terms of packet delivery ratio and throughput.
An Improved Greedy Parameter Stateless Routing in Vehicular Ad Hoc NetworkIJAAS Team
Congestion problem and packet delivery related issues in the vehicular ad hoc network environment is a widely researched problem in recent years. Many network designers utilize various algorithms for the design of ad hoc networks and compare their results with the existing approaches. The design of efficient network protocol is a major challenge in vehicular ad hoc network which utilizes the value of GPS and other parameters associated with the vehicles. In this paper GPSR protocol is improved and compared with the existing GPSR protocol and AODV protocol on the basis of various performance parameters like throughput of the network, delay and packet delivery ratio. The results also validate the performance of the proposed approach.
PERFORMANCE EVALUATION OF ERGR-EMHC ROUTING PROTOCOL USING LSWTS AND 3DUL LOC...IJCNCJournal
This paper studies the impact of different localization schemes on the performance of location-based
routing for UWSNs. Particularly, LSWTS and 3DUL localization schemes available in the literature are
used to study their effects on the performance of the ERGR-EMHC routing protocol. First, we assess the
performance of two localization schemes by measuring their localization coverage, accuracy, control
packets overhead, and required localization time. We then study the performance of the ERGR-EMHC
protocol using location information provided by the selected localization schemes. The results are
compared with the performance of the routing protocol when using exact nodes’ locations. The obtained
results show that LSWTS outperforms 3DUL in terms of localization accuracy by 83% and localization
overhead by 70%. In addition, the results indicate that the localization error has a significant impact on
the performance of the routing protocol. For instance, ERGR-EMHC with LSWTS is better in delivering
data packets by an average of 175% compared to 3DUL
Performance Evaluation of ERGR-EMHC Routing Protocol using LSWTS and 3DUL Loc...IJCNCJournal
This paper studies the impact of different localization schemes on the performance of location-based routing for UWSNs. Particularly, LSWTS and 3DUL localization schemes available in the literature are used to study their effects on the performance of the ERGR-EMHC routing protocol. First, we assess the performance of two localization schemes by measuring their localization coverage, accuracy, control packets overhead, and required localization time. We then study the performance of the ERGR-EMHC protocol using location information provided by the selected localization schemes. The results are compared with the performance of the routing protocol when using exact nodes’ locations. The obtained results show that LSWTS outperforms 3DUL in terms of localization accuracy by 83% and localization overhead by 70%. In addition, the results indicate that the localization error has a significant impact on the performance of the routing protocol. For instance, ERGR-EMHC with LSWTS is better in delivering data packets by an average of 175% compared to 3DUL.
International Journal of Computational Engineering Research (IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Similar to A COOPERATIVE LOCALIZATION METHOD BASED ON V2I COMMUNICATION AND DISTANCE INFORMATION IN VEHICULAR NETWORKS (20)
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
April 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF Based Intrusion Detection System for Big Data IOT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF based Intrusion Detection System for Big Data IoT TrafficIJCNCJournal
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IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
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Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
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About
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
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Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
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A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Top 10 Oil and Gas Projects in Saudi Arabia 2024.pdf
A COOPERATIVE LOCALIZATION METHOD BASED ON V2I COMMUNICATION AND DISTANCE INFORMATION IN VEHICULAR NETWORKS
1. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, November 2021
DOI: 10.5121/ijcnc.2021.13604 53
A COOPERATIVE LOCALIZATION METHOD BASED
ON V2I COMMUNICATION AND DISTANCE
INFORMATION IN VEHICULAR NETWORKS
Walaa Afifi1
, Hesham A. Hefny2
and Nagy R. Darwish1
1
Department of Information Systems and Technology, Faculty of
Graduate Studies for Statistical Research, Cairo University, Egypt
2
Department of Computer Sciences, Faculty of Graduate Studies
for Statistical Research, Cairo University, Egypt
ABSTRACT
Relative positions are recent solutions to overcome the limited accuracy of GPS in urban environment.
Vehicle positions obtained using V2I communication are more accurate because the known roadside unit
(RSU) locations help predict errors in measurements over time. The accuracy of vehicle positions depends
more on the number of RSUs; however, the high installation cost limits the use of this approach. It also
depends on nonlinear localization nature. They were neglected in several research papers. In these studies,
the accumulated errors increased with time due to the linearity localization problem. In the present study,
a cooperative localization method based on V2I communication and distance information in vehicular
networks is proposed for improving the estimates of vehicles’ initial positions. This method assumes that
the virtual RSUs based on mobility measurements help reduce installation costs and facilitate in handling
fault environments. The extended Kalman filter algorithm is a well-known estimator in nonlinear problem,
but it requires well initial vehicle position vector and adaptive noise in measurements. Using the proposed
method, vehicles’ initial positions can be estimated accurately. The experimental results confirm that the
proposed method has superior accuracy than existing methods, giving a root mean square error of
approximately 1 m. In addition, it is shown that virtual RSUs can assist in estimating initial positions in
fault environments.
KEYWORDS
Cooperative localization, Data fusion algorithms, V2X communication.
1. INTRODUCTION
Nowadays, transportation problems, including accidents and traffic jams, affect people’s lives in
many ways. Intelligent transportation systems (ITSs) can help to overcome such problems by
utilizing wireless communication between roadside units (RSUs) and onboard units (OBUs) that
are attached to vehicles, or by utilizing wireless communication between vehicles, to provide
services to drivers and passengers [1]. However, the multipath effect, the non-line-of-sight
conditions, and the presence of obstacles reduce the degree of certainty in the associated
measurements and reduce the signal strength. Therefore, range measurement methods are
characterized by a large degree of uncertainty, and there is a greater need to adapt parameters
such as the path exponent and noise parameters. A limited number of smart sensor nodes, i.e.,
inertial navigation systems (INSs), which include accelerometers, gyroscopes, compasses, and
odometers [2], are attached to vehicles to measure their speeds and directions. The accuracy of
such measurements is closely related to the cost of the sensors, which means that the price of
2. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, November 2021
54
vehicles is continuously high. The position of a vehicle is a vital element in most (ITSs) and is
required to be known so that messages and services can be delivered accurately. GPS systems are
a well-known type of absolute positioning system whose accuracy is limited to around 20 to 30 m
because of the non-line-of-sight problem and the presence of obstacles [3, 4]. In [5], the authors
enhanced the quality of service provided by the greedy perimeter stateless routing protocol
(GPSR). The quality of the GPSR depends on the accuracy of the GPS positions. They used a
Kalman filter GPSR (KF-GPSR) to improve the accuracy of the GPS positions. This led to an
enhanced packet delivery ratio and reduced overheads, meaning that the KF-GPSR outperformed
the standard GPSR protocol. Kinematic modeling or dead reckoning calculates positions based on
measurements that are obtained from INSs. The final position within each time interval is
updated based on the speed and direction of the vehicle as follows [6]:
(1)
. (2)
Here, and are the coordinates of the vehicle position at the current time k; and are
the initial coordinates at the initial time k0; is the velocity at the time step i; and is the
direction of motion of the vehicle at time i. Any inaccuracy in the final position causes errors to
accumulate over time. Some researchers have combined two existing techniques to improve the
position accuracy. INS and GPS systems are used together to measure positions in urban or
tunnel environments. Data fusion algorithms are then used to enhance these measurements.
However, this still does not provide a good enough solution over long periods due to the highly
dynamic nature of the network topology, inaccuracy initial position, noise in measurements and
nonlinearity of the problem [7, 8]. Cooperative localization is an alternative positioning method
that can be used by GPS systems and standalone INS/GPS systems. This method provides
relative positions using V2V or V2I communication. It introduces another source of collected
measurement to increase the opportunity to obtain well accurate measurements. A V2V
communication system can be used to improve the GPS positions, but the noisy environment can
still affect the accuracy. A V2I communication system can be used to estimate initial positions,
which increases the chance of obtaining more measurements that are accurate and predicting the
errors in position [9]. The large distance to RSUs and the number of RSUs have a significant
effect on the position accuracy and on attempts to convert the nonlinear problem to a linear one.
In [10], the authors used V2I and V2V communication approaches. V2I communication was used
to obtain initial vehicle positions by applying the cosine rule. The Kalman filter was then used to
increase the accuracy of the initial positions. V2V communication was used to update the vehicle
positions based on measurements of relative motion. The use of these methods did not achieve
acceptable results because the position accuracy was closely related to the amount of uncertainty
in the collected measurements and the errors accumulated over time. Data fusion algorithms such
as the Kalman filter and its variations, the particle filter algorithm, least square errors, and the
double difference method are used extensively with cooperative localization and object tracking
problems to reduce these accumulated errors [11, 12]. The localization problem is nonlinear by
nature. Linearization of this problem can lead to a loss of information and thus have an impact on
the accuracy. Data fusion algorithms are more sensitive to initial vehicle position and adaptive
noise in measurements. In [13], authors used GPS/INS standalone systems to trace the
autonomous vehicle way. This vehicle was equipped with two GPS receivers and INS (i.e. an
attempt to get more measurements). The authors used singular value decomposition method to
adapt noise covariance matrix in extended Kalman filter algorithms. However, the position
accuracy is acceptable to short period time. The degrading performance of GPS and errors to be
accumulate over time, the position accuracy was more negative affected. In this paper, a
cooperative localization method based on V2I communication and distance information from
3. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, November 2021
55
vehicular networks is proposed in which the initial vehicle positions are estimated using a general
formula for the intersection of two circles [14]. The initial positions are estimated from RSU
locations and distance information. The use of the intersection formula gives more accurate initial
positions than updating the positions based on the uncertainty in measurements of the motion as
in a kinematic model. Using the intersection method, the vertical distance intersect on road width
at point can be determined precisely. Therefore, increased road width help drawing straight line
intersect at specified point. In addition, the use of the general formula for intersecting points is
not restricted to linear motion models or linear network topology; the formula can also be applied
to other models of motion; e.g., models of vehicles moving on square roads and through
intersections. Vehicles can also change lanes without any effect on the position accuracy. If an
RSU fails, the formula for the intersection of two circles cannot be applied; in this situation, a
virtual RSU is used to replace the failed RSU. The position of the virtual RSU is estimated based
on measurements of the vehicle’s motion and the location of an active RSU. This ensures that the
virtual RSU’s location is in the same direction relative to the moving vehicle and, therefore,
allows continued use of the formula for the intersection of two circles to estimate the intersection
point, thus improving the measurement accuracy. Furthermore, the use of virtual RSUs helps to
reduce the cost of deploying RSUs on the road. To overcome the synchronization problem, noise
in radio measurement and deal with the nonlinear problems, an extended Kalman filter (EKF) can
be used to reduce inaccuracies in the distance measurements and reduce the accumulated errors.
The experimental results show that the proposed method gives a position accuracy of nearly 1 m,
which is better than that obtained using other cooperative localization methods, for which the
obtained accuracies were 13, 9, and 6 m [10, 21, 25], respectively.
The rest of this paper is organized as follows: Section 2 explains the related works with their
advantages and disadvantages. Section 3 presents the proposed cooperative localization method.
Section 4 provides the experimental results. Section 5 provides discussion and analysis to the
experimental results. Section 6 outlines the proposed cooperative localization method based on
distance information and explains the directions for future works.
2. RELATED STUDIES
Cooperative localization methods can be divided into GPS free localization (i.e., V2I
communication) and V2V cooperative localization methods. The accuracy of positions
determined using V2I communication increases with the number of roadside units, the road
width, and the distance to the RSU. If the distance to the RSU is large and the road is wide, the
RSU and the vehicle will lie nearly on the same line. Almost all related studies, it is assumed that
there is a large number of configured RSUs, or at least four received beacon messages from
RSUs are used to estimate vehicle positions. Overhead in communication and uncertainty in the
measurements reduce the position accuracy. In [15], the authors used V2I communication and the
weighted least square error method to estimate initial positions based on minimizing the errors in
the distance measurements. This required at least three messages from individual RSU to be
received. Vehicles have a fixed speed; therefore, the distance traveled in a given length of time is
fixed. In highly dynamic environments, however, it is difficult to follow the changing rate in spite
of various speed and distance, and the effect of the uncertainty in measurements is greater. In
addition, localization is an inherently nonlinear problem. In [16], the authors proposed a free GPS
localization algorithm based on a single RSU and the use of the angle of arrival (AOA) signal
range method. The vehicle’s position was estimated using the weighted least square error method.
The aim was to minimize the error between the AOA and the estimated angle using equation (6).
The authors proposed equation (3) to determine the intersection point, . This required to
keep the values of the vehicle’s speed, direction, and distance to the RSU correctly updated and
thus to determine the direction of the received signal.
4. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, November 2021
56
, (3)
Where is the direction in which the vehicle is heading, which is given by
, (4)
And
. (5)
is the assumed difference between vehicle’s x - coordinate and the RSU’s x – coordinate. It is
measured from difference in y coordinates that will be shared with point that is determined by
vehicle’s mobility parameters. and are the coordinates of the RSU, and xv(tk) and yv(tk) are
the vehicle’s coordinates at time . The calculated angle gives the estimated direction of the
received signal from the RSU without using multiple smart antennas. was estimated as
(6)
Each vehicle was equipped with a multiple smart antennas to estimate the different values of the
AOA. After this, the MUSIC algorithm was used to minimize the signal noise and obtain the
most appropriate value of the AOA [17]. The difference between the AOA and the estimated
angle was minimized using the least square error methods to find the position of the vehicle.
The AOA range method is more robust and produces smaller measurements errors; however, the
errors can still increase over time and lead to greater uncertainty in the measurements. In [18] the
authors proposed an RSU/INS-aided localization system in which each vehicle receives the
distance measurements as messages from RSU in one queue. Second queue is used to provide
new position estimates based on the INS system. Each vehicle receives at least four messages.
Vehicle estimate their initial positions using the least squares method to minimize the errors in
the distance and position. A Kalman filter is then applied to improve the position estimates, and
the position accuracy is closely related to the accuracy of the initial position. Again, errors
accumulate over time because of the nonlinear nature of the problem. In [19], the authors
proposed an RSU-based localization schema method. In this method, the vehicle receives at least
two messages from each of two RSUs, one on each side of the road, and the vehicle position is
determined as being the point where the ranges of the two transmissions intersect. The choice of
whether to use the forward or backward intersection point is determined by the direction of the
received signal. In the case of failure of one of the RSUs, a second-order equation is used to find
the position based on the distance to the currently active RSU, the previous distance, and the
previous position of the target vehicle. The point intersection method proved to be more effective
in linear vehicle mobility model and high certainty degree of distance measurement. The authors
assumed that large numbers of RSUs were placed on both roadsides. As the distance between the
RSU’s is equal to the transmission range, the cost of this set-up is high. In addition, errors can
accumulate as result of the failure of RSUs and because data fusion is not included in this
5. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, November 2021
57
method. In [20], the authors used different sources of information to localize the vehicle position:
TOA measurements, INS system and map data. Kinematic model parameters were obtained by
inertial navigation frame that attached to a vehicle. The INS’s mobility measurement was adapted
by TOA measurements upon receiving the messages from single RSU (i.e. position was updated
by distance measurement). These measurements were fused to EKF algorithm. After that, the
position was bounded to selected road boundary. The accuracy of selected road segment or line
segment method depended on the accuracy of digital map data. It was known that the accuracy of
EKF depended on the initial position and noise covariance matrix. Different sources of
measurements had limited accuracy over time. Accumulated errors increased over passed time.
Cooperative localization based on V2V communication solves the problem of having to deploy a
large number of RSUs and considers another source of exchanging motion measurements. It also
takes into account the multipath effect, the signal noise, obstacles, and the density of the network.
The position accuracy increases as the number of neighboring vehicles moving in the same
direction as the target vehicle increases. In all related studies, data fusion algorithms have been
used to handle the nonlinearity problem and signal noise. However, the acceptable position
accuracy levels are not enough. There is a direct relation between the uncertainty in measurement
and position accuracy. In [21], the authors used GPS/INS systems to obtain the initial positions.
The EKF was then used to linearize the distance function and the polar coordinates that were
estimated by the kinematic model; this also reduced the accumulated error. The EKF is closely
related to the initial parameters and adjusted noise in measurement and process. It is known that
the performance of GPSs in urban environment is limited, and INS system is benefit to small
period. The uncertainty in the measurements is produced by the range measurements techniques.
Therefore, the position accuracy increases as the number of neighbors moving in the same
direction increases. This is difficult to achieve in the case of highways and high-error urban
environments. In [22], the authors introduced the inter-vehicle communication-assisted
localization (IVCAL) algorithm. This algorithm uses more than one data fusion algorithm to
reduce the multipath effect and excludes the neighboring measurements that are more seriously
affected by the multipath effect; a neural network model is used to determine which neighbors are
most affected. The Nelder and Mead algorithm and the Kalman filter are used together to
estimate the final position and to reduce errors in measurement. The IVCAL requires a lot of
computation time, which means that, it is not suitable for application in safety-critical situations.
In [23] the authors proposed a constrained weighting scheme named inter-vehicle
communication-assisted localization (CWS–IVCAL), which is an extension of the IVCAL
algorithm. This algorithm uses the weight factor to measure the degree of certainty in the distance
measurements, and the weighted centroid method is used to determine the final position. The use
of the weight factor helps to improve the accuracy of the estimated position. The CWS–IVCAL
algorithm outperformed the IVCAL in urban areas, but the position accuracy was more seriously
affected by distance errors. In [24], the use of the vehicle location improved algorithm (VLOCI)
was proposed. In this algorithm, a weight factor is used to give the nearest neighbor more weight.
The weight is calculated as the inverse of the distance or as the exponential function of the
distance parameter, and the position is estimated by the weighted centroid method. In this paper,
the authors dealt with localization as a linear problem but used an unrealistic static network. In
[25], a cooperative vehicle localization improvement using distance information (COVALID)
algorithm was proposed. This algorithm is an improved version of the VANET location improved
algorithm (VLOCI) and uses the weighted centroid method to estimate the final position; the
target vehicle assigns a weight to each neighbor based on the measured distance. The use of both
a GPS and INS is required to obtain the initial position, and the difference in the distances
measured by the two systems is determined. The rules for similar triangles are then used to search
for neighbors that lie on the same line or have a linear relationship with the target vehicle. The
position determined by the GPS is then updated by applying the kinematic equations using the
difference between the distances measured by the INS and GPS. The COVALID algorithm was
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found to reduce the error in the locations determined by the GPS by 63%; this is still not good
enough for determining the linear relationship between neighboring vehicles, particularly in the
case of highways. The uncertainty in the distance between neighbors also affects the degree of
similarity. They give constant weight for each neighbor based on different distance ranges.
Constant weights do not describe well neighbors in uncertainty in measurements and therefore
they may lead to coordinate system outside network area. In [26], the authors proposed the use of
a localization algorithm to solve the GPS non-line-of-sight problem. In this study, errors in
measurements were minimized by weighted each vehicle neighbor based on received signal
strength (RSSI) and signal to noise ratio (SINR).GPS, RSSI and SINR measurements were fused
together to EKF algorithm enhance the vehicle position. Therefore, the position accuracy were
related with number of neighbors and certainty degree in measurements.
3. THE PROPOSED COOPERATIVE LOCALIZATION METHOD
The proposed cooperative localization method is based on V2I communication and distance
information. It aims to remove the problems encountered when installs a large number of RSUs
and provides continued estimates of vehicle positions in error environments. In addition, the
nonlinear localization problem is dealt with, and the improved initial states produce better results
than those obtained using the EKF. The proposed method is based on the idea of estimating
virtual RSUs. Inactive RSUs are substituted by virtual ones so that continuous estimates of
vehicle positions can be provided to solve the problem of having a large number of RSUs. The
initial positions are determined accurately using mathematical equations. The general equation
for the intersection of two circles is a powerful method of calculating expected vehicle positions
based on distances and the fixed locations of RSUs [14]. The use of the EKF also reduces the
uncertainty in the measurements and permits linearization of the distance function. The proposed
method consists of the following steps.
3.1. V2I Communication
As shown in figure 1, V2I communication is first used to estimate the initial position based on the
intersection method. There are two RSUs—one on each side of the road. The transmission range
of the RSUs is twice that of the vehicles’. Each RSU sends out messages periodically. These
messages include the position of each RSU, its identification number and the time of sending. To
avoid packet loss, the interval between messages can be adjusted by setting a jitter time randomly
between 0 and 1:
Time interval = time interval + jitter time (7)
Therefore, the risk of packet loss can be reduced and the number of received messages can be
increased. In figure 1, vehicle i receives messages from both RSUs and the identification number,
distance, and time of receipt for each packet.
3.2. Estimating the Vehicle Position
After receiving the messages from the RSUs, the vehicle estimates its own position using the
intersection method [14]. The two RSUs are located at fixed position and have the same y
coordinates but different x-coordinates, the difference between the x-coordinates being equal to
the road width. Each vehicle estimates the distance between itself and the RSUs based on the
time of arrival or receipt of the first signal:
(8)
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Where is the estimated distance between vehicle i and RSU j (j = 1, 2), c is speed of light (3 ×
108
m/s), and is the time at which vehicle i receives a message from RSU j. These distances
represent the transmission range of the vehicle. The distance between the two RSUs is equal to
the width of the road, . This must be less than the sum of the distances between the vehicle
and the two RSUs, + , and greater than the absolute difference between them. This condition
means that the vehicle receives messages from both RSUs and is, therefore, within the
transmission range of both RSUs:
Figure 1. Points of intersection between the transmission ranges of two different RSUs
(9)
It is equally likely that the vehicle is located at either of the two possible range intersection
points, whose coordinates are given by
(10)
And
, (11)
Where j (j = 1, 2) refers to the two possible points of intersection, P1 and P2. The coordinates of
RSU R1 are xR1 and yR1;. and represent the difference between the x and y coordinates of
the two RSUs, respectively:
(12)
(13)
(14)
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(15)
Figure 2. The rate of change in two dimensions
Where is equal to x in figure 2, which illustrates the use of the cosine rule. The difference
between the distances is given by y, and adding the distance between the RSUs, , to measure
x coordinate that equal to road width or cosine rule. is equal to the value of . It finds the
square root for the difference between distances rates and to measure the accordance to the
distance. The vehicle i then decides which of points P1 or P2 it is located that is based on the
directions
(16)
And
. (17)
Here and represent the direction or heading of the vehicle. Vehicle i chooses P1 as its
location if is less than ; it chooses P2 if is less than . In this case, it is not necessary
for the distance to the RSUs to be large to guarantee the linearity of the problem because the EKF
linearizes the nonlinear problem.
3.3. Failure of an RSU
Figure 3 illustrates the scenario where one of the RSUs has failed. The failed RSU then becomes
a virtual RSU, and its coordinates are estimated using data about the vehicle’s motion and the
location of the active RSU upon receipt of messages from the active RSU. The vehicle position is
then estimated by intersection method. To satisfy the intersection condition, the y-coordinate of
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the virtual RSU must be equal to the y-coordinate of the active RSU. The x coordinate of the
virtual RSU depends on the changes in the x coordinate with distance and velocity:
(18)
(19)
(20)
And
(21)
Here are the components of the vehicle’s velocity at time t + 1.
measures the mile in velocity vector; i.e., it gives the vehicle’s heading. If is large, this
means that there has been a large change in the y-coordinate and a small change in the x
coordinate since the last measurement. The x coordinate of the virtual RSU increases slightly
compared to the x coordinate of the active RSU; the virtual road width is small. helps to
determine point that spaced from RSU’s x- coordinate in any direction and specified distance
according to last vehicle position. The difference in distances from time (t) to (t+1) is positive or
negative to determine direction of vehicle i.e. forward or backward direction. This difference is
added to estimate changing in vehicle's x coordinate and RSU's x coordinate to measure
horizontal distance from RSU. The value of ( ) is equal to one plus the square of to
increase the horizontal dimension to get more precise location. This allows for an increased road
width but it remains within the network boundary. Once the coordinates of the virtual RSU have
been estimated, the next step is to determine the intersection point as described in subsection 3.2.
Following this, the EKF is applied, as described in the next subsection.
Figure 3. Illustration of a scenario where one RSU has failed
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3.4. Application of the Extended Kalman Filter (EKF)
The EKF is the best method of improving the accuracy of determined positions and solving
nonlinear localization problems [27, 12]. The EKF works by linearizing a nonlinear function
using the partial derivatives. It includes the main steps of the standard Kalman filter—i.e., the
time update or prediction step and the measurement update or correction step. The prediction step
is responsible for estimating the initial state based on the current state and the covariance noise.
The updated measurement step corrects the initial state based on new measurements and the
Kalman gain to obtain the final state, which then becomes the new initial state in the next
prediction step. These steps are repeated until a specified number of iterations or specified
tolerance error threshold is reached. In this paper, the emphasis is on minimizing the error in the
distance; i.e., the Euclidean distance between the RSU and the vehicle.
The prediction step makes use of the initial state vector and the initial covariance matrix. The
previous state vector, , is equal to the intersection point and the associated measurement
noise, , as determined from difference between INS measurements to position at time k-1:
(22)
The initial covariance matrix represents the error in the position vector. is the initial
covariance matrix, and
(23)
, is the noise covariance square matrix that follows a Gaussian distribution with a mean of 0
and variance .
The measurement update or correction step starts with the linearization of the function describing
the Euclidean distance function between the vehicle and the two RSUs. This linearization is
performed using a Taylor series expansion; the function f (x, y) is partially differentiated with
respect to its parameters:
i = 1, 2.
(24)
Here are the vehicle coordinates, and are the RSU coordinates. The partial
derivatives can be expressed as a Jacobian matrix H with N × 2 dimensions, where N is the
number of RSUs:
(25)
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H =
(26)
The Kalman gain, , represents the relation between the predicted state and the errors in the
measurements given by the two-dimensional matrix R:
(27)
Where is the initial covariance matrix, is the Jacobian matrix, and R is the noise covariance
matrix for the measurements. The noise equals the difference between the two estimated
positions and followed position estimated by the INS measurements (1), (2) plus an error E that
follows a Gaussian distribution with mean 0 and variance :
. (28)
If the errors in measurements given by R are small, this means that the Kalman gain (K) has a
high value and the initial state will be adjusted primarily by using the updated measurements. If R
is high, the value of K is small. The initial state will then be adjusted primarily by using the
predicted covariance matrix. If the values in the predicted covariance matrix P are small, then the
errors in the measurements can mostly be ignored and the predicted state will be close to the true
position. The final position is obtained by updating the current state, , to the posteriori state
vector, , as follows:
(29)
Where A is the square identity transition matrix, K is the Kalman gain, Y is new INS’s
measurement and represents the error in the measurements. The final step is the
updating of current covariance matrix to give posteriori covariance matrix :
(30)
Where I is the identity matrix, H is the transition matrix, and is the previous predicted
covariance matrix at time k. gives the current predicted state and covariance matrix,
respectively at time k+1that will become priori states in prediction step. The prediction and
update steps are repeated every time the vehicle’s position continues to be updated with each new
measurement. In the section describing the simulations that follows, each vehicle continues to
estimate its position each time it receives messages so that it can get accurate measurements and
make an accurate estimate of its position. The squared errors are estimated at each time, the
position estimates are repeated, and the averages of all the results are taken.
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4. SIMULATED SCENARIOS
In this section, the accuracy to which vehicle positions can be determined using the proposed
cooperative localization method based on V2I communication and distance information is
assessed and a comparison made with the methods described in other related papers [10, 21, 25].
The differences in these methods are mainly concerned with the different ways in which the
initial positions are improved using data fusion algorithms. In [10], the authors used the cosine
rule method to obtain the initial positions. To apply the cosine rule, it is necessary to use different
values of y coordinates for the two RSUs and for the values of the x-coordinates to be similar
because the resulting acute angle and large distance to the RSUs gives a better accuracy for the
estimated position. The Kalman filter is then used to improve the initial vehicle position and
solve the problem of the accumulated errors. In [21], the authors relied on GPS/INS systems to
obtain the initial positions and subsequently update them. It is well known that the accuracy of
GPS systems is limited in urban environments due to the non-line-of-sight problem and the
multipath effect [3, 4]. In addition, the errors associated with INS systems can accumulate with
time. The initial positions were thus improved by applying an EKF based on distance
measurements that were obtained by V2V communication. In [25], the authors used a weighted
centroid method to improve the positions obtained using the GPS and INS, and weight factors
were used to describe the degree of closeness between the target vehicle and its neighbors. The
authors then divided the measured distances into categories, using a fixed weight for each
category. The rules for similar triangles were used to find the neighbor for which the relationship
between the target vehicle and its neighbor was the nearest to being linear. These results were
also improved by applying an EKF algorithm. The performance of the previous methods are
evaluated by applying them to two different scenarios. The first of these concerned a one-way
road in the city of Enlargen where vehicles entered from the same point. The second scenario was
more complex and concerned different roads in the city of KarradaIn where vehicles entered from
different points; the vehicles thus approached from different directions and had different road
coordinates. Each road consisted of a single lane and single direction. For the second scenario,
comparisons were made between the proposed method and the localization methods presented in
[21, 25] to test the dependency of the EKF algorithm on the accuracy of the initial position;
adjustments to the noise were also made during the measurement process. The performance
metric used to measure the position accuracy was the root mean square error (RMSE).
The RMSE measures the difference between a real position, pi, and an estimated position, pi^:
. (31)
OMNET 5++ is an open source C++ discrete event network simulator. It applies the IEEE
802.11p standard for vehicular networks [28] and consists of different frameworks that allow the
easy development of ad hoc routing protocols such as VEINS [29]. The VEINS framework is a
specialized framework used for translating road traffic networks that are described in XML files.
These road traffic networks are generated by a SUMO framework [30, 31], which is a bi-
direction coupled program to network simulator. It is a microscopic car-forwarding model, and
consists of a set of programs that enable the creation of road traffic networks. VEINS can be
coupled with SUMO to translate actual road traffic into vehicle speeds, directions, positions, road
identifiers, traffic lights, intersections or junction nodes, etc. to allow easy implementation of
routing protocols. In other words, VEINS provides a client–server model that links OMNET 5++
and SUMO. Table 1 summarizes the simulation parameters that were used in this study.
Vehicular networks follow the IEEE 802.11p standard that is used to support ITSs, and a
lognormal shadowing propagation model with a path exponent of 1.5 is used. The noise in the
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scenarios that were investigated had a Gaussian distribution with a mean of 0 and variance A
new vehicle entered the roads every 1s. The default mobility model used in SUMO applications
is the Krauss model, which is a car-following mobility model that describes the behavior of a
following vehicle based on the behavior of the vehicle in front. The simulation time used was 60
s, and an average of the results was taken at the end of each simulation. Each scenario was run
five times, and averages were again taken.
Table 1. Simulation parameters
4.1. Scenario 1
In the Enlargen scenario, RSUs were placed on each side of the road at coordinates (0, 1500) and
(12, 1500) to test the proposed localization method. They were placed at (600, 10) and (400, 800)
in the test of the cooperative localization method based on V2I communication, KF, and V2V
communication (V2I + KF + V2V) described in [10]. The network area used was equal to 2500 m
× 2500 m. Figure 4 shows the values of the RMSE at six nodes obtained during the simulation.
The position errors obtained using the proposed method is the smallest at approximately 1 m for
all six nodes. In the test of the V2I + KF + V2V method, the authors used V2I communication,
the cosine rule, V2V communication, and the Kalman filter to improve the initial position
estimates and to reduce the accumulated errors. However, the accuracy is nearly 13 m, this
method gave the least accuracy among the methods tested. The accumulated errors increase with
time and the nature of localization is nonlinear. The KF algorithm is more sensitive to the initial
state, the noise, and the measurement covariance matrix. In addition, because of lane changes,
vehicle position is estimated by cosine rule, these angles may have to be calculated using the sine
rule to get better initial position state. One advantage of the proposed method is that a general
formula for the intersection point is used to make good estimates of initial positions; these are
then improved by applying the EKF algorithm. In [25], which describes the use of the centroid +
EKF method, the authors used the weighted centroid method to estimate positions and the rules
for similar triangles to find the neighbor that lies on the same line; however, the results here show
that this produces higher errors than the GPS/INS +EKF method [21]. Again, this is because of
the errors that accumulate during the simulation, the way of obtained initial positions and the use
of constant weight factors. In [20, 24], two methods use the same source of measurement GPS
and INS. The weight factors did not differeinate well between neighbors. Figure 5 shows the
position accuracies obtained using the different methods at different velocities ranging from 70
km/h to 120 km/h. The errors for the proposed method are the smallest and are less affected by
the speed. This demonstrates the benefit of using a virtual RSU to make continued estimates of
vehicle positions within the error environment and the use of the general formula for the
intersection of two circles to effectively increase with the road width. In addition, the nonlinear
relationships are handled by the EKF without much loss of information. For the V2I + KF + V2V
cooperative localization method, the greatest position errors occur at a speed 90 km/h; for other
speeds, the errors are almost as large. It thus appears that the use of V2V communication does not
reduce the accumulated errors because increasing uncertainty measurements upon high dynamic
network mobility and the unsuitability of the cosine rule. The values of the RMSE for the
Parameter Value
IEEE standard 802.11p standard
Number of vehicles 1 vehicle/s
Propagation model Lognormal shadowing
Mobility model Krauss
Pause time 1 s
Acceleration 2.6 m/s2
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centroid +EKF and the GPS/INS + EKF methods are similar at a speed of 90 km/h and less
different at other velocities because we assume less error in distance measurement. In addition,
the probability of finding neighbors that is moving in the same direction increases. At the end of
first scenario, the ways for obtained initial position play significant effect during the simulation
run. The effect of data fusion algorithms are limited due to initial state and noise covariance
matrix.
Figure 4. Root mean square error for a distance error of 0.5 m
Figure 5. Root mean square error at different velocities and 0.5 distance errors
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4.2. Scenario 2
The KarradaIn scenario involved a more complex dataset where vehicles traveled in different
directions and entered at different points; there were also large differences between the
coordinate systems for each road. This second scenario was used to investigate the ability of the
EKF to reduce the accumulated errors and to determine its sensitivity to the adapted noise
covariance matrix. Different speeds and different sizes of error in the distance measurements
were used in the experiment. Again, the position accuracy was measured in terms of the RMSE.
One RSU was sited at position (1000, 3000) and one at (700, 3000) in proposed method. The
width of the road was 300 m larger than that used in the first scenario. The noise had a Gaussian
distribution with a mean of 0 and a variance of . Figure 6 shows the estimated RMSE for a
scenario involving six vehicles and a distance error of 0.5 m. It can be seen that, for the proposed
method, the RMSE is almost the same at all of the nodes. The application of the general
intersection formula produces small errors at large road width. The RMSEs for the GPS/INS +
EKF method are greater than for the centroid + EKF method. Again, this is due to the uncertainty
in the angles and speeds measured by the INS, as an INS is only accurate over short periods. The
results for the centroid +EKF method demonstrate the advantages of applying the similar triangle
rules to find more neighbors that have a linear relationship with the target vehicle. Figure 7 shows
the RMSE results obtained for different speeds, also for a distance error of 0.5 m. In the case of
the proposed method, increasing the speed does not appear to affect the accuracy of the position;
again, this is because of the accuracy of the initial vehicle positions and the use of the virtual
RSU estimation method. The greatest error in the position—nearly 1 m—occurs at a speed of 80
km/h, which again is because of the lower accumulated errors that result from the use of a virtual
RSU and the increase in the virtual road width. At higher speeds, the GPS/INS+EKF method
produces smaller errors than the centroid +EKF method, which increases the probability of
finding neighbors moving in the same direction. The weighted centroid method is more affected
by the weight factors. Figure 8 illustrates the effect of uncertainties in the measurements on the
position accuracy. For all of the cooperative localization methods, the RMSE increases as the
error in the distance increases. This demonstrates the need for using accurate range measurement
techniques, accurate initial position and of the adjusted noise covariance matrix in the EKF.
Figure 6. Root mean square error for a distance error of 0.5 m
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Figure 7. Root mean square error at different speeds for a distance error of 0.5 m
Figure 8. Root mean square error for different sizes of the distance error and a speed of 90 km/h
5. DISCUSSION
The nonlinear nature of localization and measurement uncertainty increase the difficulty of
obtaining accurate vehicle positions. The relative position methods are based on communication
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between a vehicle and RSUs or with neighboring vehicles, is more affected by signal noise and
the errors are accumulated over time. Localization in V2I communication perform better than
V2V communication; the cost of the installed large number of RSU is high. V2V communication
does not involve any costs but requires very accurate measurements. In the GPS/INS + EKF
method [21], the coupled of GPS and INS systems produces positive results over short periods
with some small errors. These errors are accumulated over time. The cost of attached inertial
navigation frame affect the accuracy degree in measurements. EKF algorithms are sensitive to the
noise covariance matrix and initial states. The method proposed in this paper uses fixed RSUs to
help predict errors in the distance measurements. The initial vehicle positions are estimated using
a general formula for the intersection of two circles and this gives more accurate results than
updates derived using a kinematic model. In addition, the use of this general intersection formula
allows different vehicle mobility models to be studied without affecting the position accuracy.
The failure of an RSU affects the availability of position estimates and increases uncertainty in
the measurements. Using a virtual RSU based on motion parameters has a positive impact on the
position accuracy and increases the virtual road width. The application of the general intersection
formula is more effective where the road is wide. In addition, the intersection method depends on
the distance and, therefore, the angle has less impact on the accuracy being limited to determining
whether the signs of the two coordinates are positive or negative. In the V2I + KF + V2V method
[10], the use of two different communication methods does not appear to reduce the accumulation
errors; again, this is because of the range measurement techniques used and the application of the
KF algorithm. The KF algorithm is more applicable to linear problems. The centroid +EKF
method can also be used to estimate vehicle positions. In [25], the rules for similar triangles were
used to find neighboring vehicles with linear relations. However, this is difficult to do because of
the lane changes made by vehicles. The use of fixed weights reduces the position accuracy due to
errors and noise in the measurements. Highly accurate range measurement techniques should be
used that represent high-energy consumption. Attempts are being made to organize the types of
routing communication used in vehicular networks to decrease the uncertainty in measurements.
Weight factors should give a good indicator of closeness degree for every neighboring vehicles
and that can be used as a measure of uncertainty in measurements. This will have the benefit of
increasing the degree of certainty in measurements as the dependence on V2V communication
systems increases because of attempts to reduce the costs associated with building more RSUs.
6. CONCLUSION
In this paper, a cooperative localization method for improving position accuracy based on V2I
communication and distance information was introduced. The proposed method consists of three
steps. First, V2I communication is used to send two messages to each vehicle and to estimate the
distance to each vehicle. Second, good estimates of the vehicle positions are obtained by applying
the general equation for the intersection of two circles. These estimates are further improved by
applying an EKF to reduce the uncertainty in the measurements by linearizing the nonlinear
distance function. In case of the failure of one RSU, a virtual RSU is estimated so that estimates
of the vehicle positions can continue to be made. The experimental results showed that the
proposed method was the most efficient of the methods that were tested. The performance is
approached to 1m approximately. The use of GPS/INS, the cosine rule method and weighted
centroid method did not produce good estimates of the initial positions. Data fusion algorithms
were found to be more sensitive to the initial parameters and noise covariance matrix.
Future works, hybrid communication approach mixes the benefits of using two types of
communications as a way to reduce accumulation error and substitute the high cost deployment
of more roadside units along roads. Usage of high accurate range methods increases certainty
degree of measurements. The multi-hop or clustering routing protocols helps to find neighbour
with high accurate measurement.
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CONFLICTS OF INTEREST
The author declares no conflict of interest
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