In this paperwe present a low complexity user grouping algorithm for multi-user MIMO system employing opportunistic fair scheduling (OFS) and zero forcing beamforming (ZFB), and develop a framework for cross-layer resource scheduling. Given a particular subset of users and their channel conditions, the optimal beamforming scheme can be calculated. The multi-user esource scheduling problem then refers to the selection of the optimal subset of users for transmission at each time instant to maximize the total throughput of the system. The simulation result shows that the performance of resource scheduling algorithm based on user grouping method proposed in this paper is close to the optimal performance which used exhaustion method. In addition, user grouping does not affect the fairness among all users.
The document proposes a dynamic network selection algorithm using Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to address the problem of selecting a network for multiple simultaneous calls from a mobile terminal in heterogeneous wireless networks. The FAHP method is used to assign weights to different network selection criteria. The TOPSIS method then ranks the network alternatives based on the ideal and negative-ideal solutions to select the most suitable network. Simulation results show the proposed algorithm reduces handoffs and improves throughput compared to existing approaches.
A Text-Independent Speaker Identification System based on The Zak TransformCSCJournals
This paper presents a novel text-independent speaker identification system based on the discrete Zak transform. The system uses the Zak transform coefficients as features to model 23 speakers from the ELSDSR database. During identification, the Euclidean distance between the Zak transform of the test speech and each speaker model is calculated. The speaker with the minimum distance is identified. The system achieves an identification efficiency of 91.3% using a single test file and 100% using two test files. The Zak-based method is also faster and has comparable accuracy to MFCC-based speaker identification. The paper also explores dividing signals into segments and averaging the Zak transforms, which improves efficiency while only slightly increasing modeling time.
This document proposes using a Markov chain model and bipartite graphing to efficiently schedule spectrum in cognitive radio networks. It models the cognitive radio network as a k-connected bipartite graph and uses a Markov chain to represent the state transitions of channels between idle and busy. It then applies the Banker's algorithm to the modeled cognitive radio network to allocate spectrum to users while avoiding deadlock. The proposed approach indicates it could improve spectrum scheduling and allocation performance in cognitive radio networks.
This document discusses using Gamma tone Frequency Cepstral Coefficients (GFCC) and K-means clustering to identify singers based on their voice. It begins by explaining that MFCC is not accurate in noisy environments, while GFCC performs well in both clean and noisy audio. The process involves extracting GFCC features from the audio, using K-means clustering to group similar voices into clusters, and dynamic time warping for authentication. Feature extraction with GFCC involves preprocessing, framing, windowing, computing the discrete Fourier transform, applying a gamma tone filter bank, logarithmic compression, and discrete cosine transformation to generate feature vectors. K-means clustering is then used to group the feature vectors from similar voices into clusters to identify
Throughput in cooperative wireless networksjournalBEEI
Cognitive radio networks emerge as a solution to fixed allocation issues and spectrum scarcity through the dynamic access to spectrum. In cognitive networks, users must make intelligent decisions based on spectrum variation and actions taken by other users. Under this dynamic, cooperative systems can significantly improve quality of service parameters. This article presents the comparative study of the multi-criteria decision-making algorithms SAW and FFAHP through four levels of cooperation (10%, 20%, 50%, 80% y 100%) established between secondary users. The results show the performance evaluation obtained through of simulations and experimental measurements. The analysis is carried out based on throughput, depending on the class of service and the type of traffic.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a study that evaluates and compares the performance of two routing protocols (DSDV and DSR) in mobile ad hoc networks using network simulation. It finds that DSDV has shorter delays but higher routing load as network size increases, making it unsuitable for large, dynamic networks. DSR has moderate routing load and longer delays, making it better for medium-sized networks without high delay requirements. The study uses ns-2 simulation with varying network sizes from 10 to 50 nodes to measure metrics like end-to-end delay, jitter, and normalized routing load under different traffic patterns.
This document compares the performance of three mobile ad hoc network (MANET) routing protocols: AODV, FSR, and IERP. It uses the QualNet network simulator to evaluate these protocols based on various metrics like throughput, average jitter, average end-to-end delay, and packet delivery ratio. The protocols are evaluated under different node speeds on a grid topology network with 90 nodes over an area of 1500x1500 meters. Simulation results show that AODV generally performs best in terms of throughput and packet delivery ratio across varying node speeds, while FSR performs worst for these metrics. IERP shows the worst performance for average end-to-end delay and average jitter as node speed increases.
DSR Routing Decisions for Mobile Ad Hoc Networks using Fuzzy Inference Systemcscpconf
Mobile ad-hoc network technology has gained popularity in recent years by researchers on account of its flexibility, low cost and ease of deployment. The objective of this paper is to model the behavior of MANET for DSR protocol by considering some prominent routing metrics.These metrics ( packet delivery fraction, normalized routing load , average end- to- end delayetc.) have been generated by Network Simulator NS 2.34 tools and the node movement has beengenerated using Bonmotion 1.4.The MANET behavior for DSR protocol is hypothesized to be dependent on fuzzy variables like node density, pause time , number of packets transferred , and the number of connection. In this paper the behavior of MANET is modeled using Fuzzy Inference System for DSR (Dynamic Source Routing) protocol , Fuzzy Inference System offers a natural way of representing and reasoning the problems with uncertainty and imprecision. Fuzzy logic is found to be a suitable way in the mobile ad hoc network routing decision. A Fuzzy inference system is implemented on MATLAB 7.0 and the model is found to be satisfactory with the fuzzy input metrics and de fuzzified output metrics .
The document proposes a dynamic network selection algorithm using Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to address the problem of selecting a network for multiple simultaneous calls from a mobile terminal in heterogeneous wireless networks. The FAHP method is used to assign weights to different network selection criteria. The TOPSIS method then ranks the network alternatives based on the ideal and negative-ideal solutions to select the most suitable network. Simulation results show the proposed algorithm reduces handoffs and improves throughput compared to existing approaches.
A Text-Independent Speaker Identification System based on The Zak TransformCSCJournals
This paper presents a novel text-independent speaker identification system based on the discrete Zak transform. The system uses the Zak transform coefficients as features to model 23 speakers from the ELSDSR database. During identification, the Euclidean distance between the Zak transform of the test speech and each speaker model is calculated. The speaker with the minimum distance is identified. The system achieves an identification efficiency of 91.3% using a single test file and 100% using two test files. The Zak-based method is also faster and has comparable accuracy to MFCC-based speaker identification. The paper also explores dividing signals into segments and averaging the Zak transforms, which improves efficiency while only slightly increasing modeling time.
This document proposes using a Markov chain model and bipartite graphing to efficiently schedule spectrum in cognitive radio networks. It models the cognitive radio network as a k-connected bipartite graph and uses a Markov chain to represent the state transitions of channels between idle and busy. It then applies the Banker's algorithm to the modeled cognitive radio network to allocate spectrum to users while avoiding deadlock. The proposed approach indicates it could improve spectrum scheduling and allocation performance in cognitive radio networks.
This document discusses using Gamma tone Frequency Cepstral Coefficients (GFCC) and K-means clustering to identify singers based on their voice. It begins by explaining that MFCC is not accurate in noisy environments, while GFCC performs well in both clean and noisy audio. The process involves extracting GFCC features from the audio, using K-means clustering to group similar voices into clusters, and dynamic time warping for authentication. Feature extraction with GFCC involves preprocessing, framing, windowing, computing the discrete Fourier transform, applying a gamma tone filter bank, logarithmic compression, and discrete cosine transformation to generate feature vectors. K-means clustering is then used to group the feature vectors from similar voices into clusters to identify
Throughput in cooperative wireless networksjournalBEEI
Cognitive radio networks emerge as a solution to fixed allocation issues and spectrum scarcity through the dynamic access to spectrum. In cognitive networks, users must make intelligent decisions based on spectrum variation and actions taken by other users. Under this dynamic, cooperative systems can significantly improve quality of service parameters. This article presents the comparative study of the multi-criteria decision-making algorithms SAW and FFAHP through four levels of cooperation (10%, 20%, 50%, 80% y 100%) established between secondary users. The results show the performance evaluation obtained through of simulations and experimental measurements. The analysis is carried out based on throughput, depending on the class of service and the type of traffic.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a study that evaluates and compares the performance of two routing protocols (DSDV and DSR) in mobile ad hoc networks using network simulation. It finds that DSDV has shorter delays but higher routing load as network size increases, making it unsuitable for large, dynamic networks. DSR has moderate routing load and longer delays, making it better for medium-sized networks without high delay requirements. The study uses ns-2 simulation with varying network sizes from 10 to 50 nodes to measure metrics like end-to-end delay, jitter, and normalized routing load under different traffic patterns.
This document compares the performance of three mobile ad hoc network (MANET) routing protocols: AODV, FSR, and IERP. It uses the QualNet network simulator to evaluate these protocols based on various metrics like throughput, average jitter, average end-to-end delay, and packet delivery ratio. The protocols are evaluated under different node speeds on a grid topology network with 90 nodes over an area of 1500x1500 meters. Simulation results show that AODV generally performs best in terms of throughput and packet delivery ratio across varying node speeds, while FSR performs worst for these metrics. IERP shows the worst performance for average end-to-end delay and average jitter as node speed increases.
DSR Routing Decisions for Mobile Ad Hoc Networks using Fuzzy Inference Systemcscpconf
Mobile ad-hoc network technology has gained popularity in recent years by researchers on account of its flexibility, low cost and ease of deployment. The objective of this paper is to model the behavior of MANET for DSR protocol by considering some prominent routing metrics.These metrics ( packet delivery fraction, normalized routing load , average end- to- end delayetc.) have been generated by Network Simulator NS 2.34 tools and the node movement has beengenerated using Bonmotion 1.4.The MANET behavior for DSR protocol is hypothesized to be dependent on fuzzy variables like node density, pause time , number of packets transferred , and the number of connection. In this paper the behavior of MANET is modeled using Fuzzy Inference System for DSR (Dynamic Source Routing) protocol , Fuzzy Inference System offers a natural way of representing and reasoning the problems with uncertainty and imprecision. Fuzzy logic is found to be a suitable way in the mobile ad hoc network routing decision. A Fuzzy inference system is implemented on MATLAB 7.0 and the model is found to be satisfactory with the fuzzy input metrics and de fuzzified output metrics .
Probability Density Functions of the Packet Length for Computer Networks With...IJCNCJournal
The research on Internet traffic classification and identification, with application on prevention of attacks
and intrusions, increased considerably in the past years. Strategies based on statistical characteristics of
the Internet traffic, that use parameters such as packet length (size) and inter-arrival time and their
probability density functions, are popular. This paper presents a new statistical modeling for packet length,
which shows that it can be modeled using a probability density function that involves a normal or a beta
distribution, according to the traffic generated by the users. The proposed functions has parameters that
depend on the type of traffic and can be used as part of an Internet traffic classification and identification
strategy. The models can be used to compare, simulate and estimate the computer network traffic, as well
as to generate synthetic traffic and estimate the packets processing capacity of Internet routers
Cellular wireless systems like GSM suffer from congestion resulting in overall system degradation and poor service delivery. When the traffic demand in a geographical area is high, the input traffic rate will exceed thecapacity of the output lines. This work focused on homogenous wireless network (the network traffic and resource dimensioning that are statistically identical) such that the network performance
evaluation can be reduced to a system with single cell and a single traffic type. Such system can employa queuing model to evaluate the performance metric of a cell in terms of blocking probability.
Five congestion control models were compared in the work to ascertain their peculiarities, they are Erlang B, Erlang C, Engset (cleared), Engset (buffered), and Bernoulli. To analyze the system, an aggregate onedimensional Markov chain wasderived, such that it describes a call arrival process under the assumption
that it is Poisson distributed. The models were simulated and their results show varying performances, however the Bernoulli model (Pb5) tends to show a situation that allows more users access to the system and the congestion level remain unaffected despite increase in the number of users and the offered traffic into the system.
Distributed Spatial Modulation based Cooperative Diversity Schemeijwmn
: In this paper, a distributed spatial modulation based cooperative diversity scheme for relay
wireless networks is proposed. Where, the space-time block code is exploited to integrate with distributed
spatial modulation. Therefore, the interested transmission scheme achieves high diversity gain. By using
Monte-Carlo simulation based on computer, we showed that our proposed transmission scheme outperforms
state-of-the-art cooperative relaying schemes in terms bit error rate (BER) performance.
PERFORMANCE AND REKEYING ANALYSIS OF MULTICAST SECURITY IN LTEIJCNCJournal
This document analyzes the performance and rekeying of multicast security in LTE networks. It compares two security solutions for multimedia broadcast multicast services (MBMS) in LTE - Group Security Association (GSA) and Secure Multicast Overlay (SMO). It models parameters for different multicast services like TV channels, Twitter, and Facebook. It calculates the computational and storage costs for rekeying using logical key hierarchy (LKH) tree with and without dynamic rekeying, and for changing the tree degree or height. The goal is to assess the performance of GSA and SMO solutions and determine which is more appropriate based on different parameters and services.
Data collection scheme for wireless sensor network with mobile collectorijwmn
In this paper, we investigate the problem of designing the minimum number of required mobile elements
tours such that each sensor node is either on the tour or one hop away from the tour, and the length of the
tour to be bounded by pre-determined value L. To address this problem, we propose heuristic-based
solution. This solution works by directing the mobile element tour towards the highly dense area in the
network. The experiment results show that our scheme outperform the benchmark scheme by 10% in most
scenarios.
The document proposes a novel geographic routing protocol called Multihop Delaunay Triangulation (MDT) that has two key properties: 1) guaranteed delivery of packets for any connected graph of nodes in d-dimensional space where d is greater than or equal to 2, and 2) low routing stretch from efficient forwarding of packets out of local minima. MDT provides guaranteed delivery even when node locations are inaccurate or arbitrary. Experimental results show MDT has the lowest routing stretch compared to other geographic routing protocols and maintains close to 100% routing success during network changes.
Testing and Improving Local Adaptive Importance Sampling in LFJ Local-JT in M...csandit
Multiply Sectioned Bayesian Network (MSBN) provides
a model for probabilistic reasoning in
multi-agent systems. The exact inference is costly
and difficult to be applied in the context of
MSBNs as the size of problem domain becomes larger
and complex. So the approximate
techniques are used as an alternative in such cases
. Recently, for reasoning in MSBNs, LJF-
based Local Adaptive Importance Sampler (LLAIS) has
been developed for approximate
reasoning in MSBNs. However, the prototype of LLAIS
is tested only on Alarm Network (37
nodes). But further testing on larger networks has
not been reported yet, so the scalability and
reliability of algorithm remains questionable. Henc
e, we tested LLAIS on three large networks
(treated as local JTs) namely Hailfinder (56 nodes)
, Win95pts (76 nodes) and PathFinder(109
nodes). From the experiments done, it is seen that
LLAIS without parameters tuned shows good
convergence for Hailfinder and Win95pts but not for
Pathfinder network. Further when these
parameters are tuned the algorithm shows considerab
le improvement in its accuracy and
convergence for all the three networks tested.
This document describes a context-aware automatic traffic notification system for cell phones that can learn a user's common destinations and routes over time using location and context data. It collects GPS and other data from users, identifies important locations through clustering, learns frequent routes between locations, and can predict a user's destination and route to then notify them of any traffic conditions. The system is implemented on a mobile phone to provide automated traffic alerts to users during their daily commutes without needing to manually enter a destination.
Flexible channel allocation using best Secondary user detection algorithmijsrd.com
This document proposes a flexible channel allocation algorithm for cooperative cognitive radio networks using secondary user detection. It introduces Flexible Channel Cooperation (FLEC) which allows secondary users to optimize their use of resources including channels and time slots from primary users. The document develops efficient resource allocation algorithms for FLEC, including a distributed bargaining algorithm and centralized heuristic algorithm. It evaluates the performance of FLEC and shows it provides throughput improvements of 20-60% over conventional identical channel cooperation. A centralized heuristic algorithm achieves near-optimal performance with only 5% loss compared to the optimal centralized algorithm, providing a good tradeoff between performance and complexity.
A mobile ad-hoc network (MANET) is a self structured infrastructure less network of mobile devices
connected by wireless. Each device in a MANET is free to move independently in any direction, and will
therefore change its links to other devices frequently. Load balancing is a technique to share out workload
across network links, to achieve maximize throughput, minimize response time, and avoid overload. Load
imbalance is a one of the critical issue in the ad-hoc network. Particle Swarm Optimization (PSO) method
is used to implement our proposed technique. In this Paper two algorithms are used for balancing the
nodes in the network. Identify the unfair nodes location next allocate and balance the load between the
nodes in the network. The simulation results show that this approach is more effective in terms of packet
delivery ratio, average end-to-end delay, load distribution, packet delay variation, packet reordering, and
throughput.
Use of Hidden Markov Mobility Model for Location Based ServicesIJERA Editor
These days people prefer to use portable and wireless devices such as laptops, mobile phones, They are connected through satellites. As user moves from one point to other, task of updating stored information becomes difficult. Provision of Location based services to users, faces some challenges like limited bandwidth and limited client power. To optimize data accessibility and to minimize access cost, we can store frequently accessed data item in cache of client. So small size of cache is introduced in mobile devices. Data fetched from server is stored on cache. So requested data from user is provided from cache and not from remote server. Question arises that which data should be kept in the cache? Performance of cache majorly depends on the cache replacement policies which select data suitable for eviction from cache. This paper presents use of Hidden Markov Models(HMMs) for prediction of user‟s future location. Then data item irrelevant to this predicted location is fetched out from the cache. The proposed approach clusters location histories according to their location characteristics and also it considers each user‟s previous actions. This results in producing high packet delivery ratio and minimum delay.
Mobile ad hoc networks – dangling issues of optimal path strategyAlexander Decker
The document discusses issues related to selecting optimal paths in mobile ad hoc networks. It proposes using a random direction mobility model to detect neighborhoods and trace paths between source and destination nodes. The model represents nodes moving in random directions for periods of time before pausing. The paper also discusses calculating the probability of link availability over time between two moving nodes based on their movements and developing a link maintenance probability model. An implementation of detecting neighborhoods using this low probability mobility model in Java is also described.
Location predictionin cellular network using neural networkIAEME Publication
1. The document discusses using neural networks for location prediction in cellular networks to improve location management and reduce costs.
2. It proposes using a backpropagation multilayer neural network trained on subscriber movement patterns to predict a subscriber's new location instead of traditional location management schemes.
3. The results show over 69% correct prediction for the random walk mobility pattern, which can help reduce location management costs by knowing a subscriber's location without paging all cells.
Game-Theoretic Channel Allocation in Cognitive Radio Networks IJECEIAES
Cognitive radio networks provide dynamic spectrum access techniques to support the increase in spectrum demand. In particular, the spectrum sharing among primary and secondary users can improve spectrum utilization in unused spectrum by primary users. In this paper, we propose a novel game theoretic channel allocation framework to maximize channel utilization in cognitive radio networks. We degisn the utility function based on the cochannel interference among primary and secondary users. In addition, we embed the property of the adjacent channel intererence to consider real wireless environment. The results show that the utility function converges quickly to Nash equilibrium and achieves channel gain by up to 25 dB compared to initial assignment.
The document discusses network routing and congestion control from a game-theoretic perspective. It describes routing as a game where users determine routes to minimize individual cost, and congestion control as a game where users determine data rates. Equilibrium points like the Nash equilibrium are analyzed. Selfish routing can lead to high costs compared to optimal routing.
Performance Analysis for Parallel MRA in Heterogeneous Wireless NetworksEditor IJCATR
This document analyzes methods for optimal path selection and power allocation in heterogeneous wireless networks where a user can transmit data through multiple radio access technologies (RATs) simultaneously. It formulates the bandwidth and power allocation problem as an optimization problem to maximize total system capacity. The Newton and modified Newton methods are proposed to find the optimal solution. Simulation results show the modified Newton method achieves higher total system capacity compared to the Newton method.
Selective Green Device Discovery for Device to Device CommunicationTELKOMNIKA JOURNAL
The D2D communication is expected to improve devices’ energy-efficiency, which has become a
major requirement of the future wireless network. Before the D2D communication can be performed, the
device discovery between devices must be done. The previous works usually only assumed one mode of
device discovery, i.e. either use network-assisted (with network supervision) or independent (without
network supervision) device. Therefore, we propose a selective device discovery for device-to-device
(D2D) communication that can utilize both device discovery modes and maintain devices’ energyefficiency.
Different from previous works, our proposed method selects the best device discovery mode to
get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method
also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable
mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy
expectation. Our experiment result indicates that the proposed method provides lowest energy
consumption per new accepted device while compared with schemes with full network-assisted and
independent device discovery in low numbers of new device arrival (for the number of new devices
arrival = 1 ~ 3).
DISTRIBUTED COVERAGE AND CONNECTIVITY PRESERVING ALGORITHM WITH SUPPORT OF DI...IJCSEIT Journal
Given a 3D space where should be supervised and a group of mobile sensor actor nodes with limited
sensing and communicating capabilities, this paper aims at proposing a distributed self-deployment
algorithm for agents to cover the space as much as possible by considering non-uniform sensing coverage
degree constraint of environment while preserving connectivity. The problem is formulated as coverage
maximization subject to connectivity and sensing coverage degree constraint. Considering a desired
distance between neighbouring nodes, an error function which depends on pairwise distance between
nodes is described. The maximization is encoded to an error minimization problem that is solved using
gradient descent algorithm and will yield in moving sensors into appropriate positions. Simulation results
are presented in two different conditions that importance of sensing coverage degree support of
environment is very high and is low.
A Weighted Duality based Formulation of MIMO SystemsIJERA Editor
This work is based on the modeling and analysis of multiple-input multiple-output (MIMO) system in downlink communication system. We take into account a recent work on the ratio of quadratic forms to formulate the weight matrices of quadratic norm in a duality structure. This enables us to achieve exact solutions for MIMO system operating under Rayleigh fading channels. We outline couple of scenarios dependent on the structure of eigenvalues to investigate the system behavior. The results obtained are validated by means of Monte Carlo simulations.
Novel cell selection proceduref lte hetnets based on mathematical modelling o...ijwmn
Femtocells have been considered one of the most important technologies in LTE networks to solve indoor
coverage problem, however the randomness deployment of femtocells, leads to great challenge for selecting
optimum serving cell. In this work, a new cell selection algorithm is proposed that enables new user to
select best serving cell whereas several factors are put into consideration other than highest instantaneous
SNR or maximum RSRP such as cell load .A new prediction algorithm is designed to predict the
performance of (PF) scheduling algorithm to calculate expected number of RBs to be scheduled to new
user, then reduction in achievable data rate due to both received SNR and instant cell load is estimated.
The numerical results show that the new proposed cell selection algorithm achieves higher average cell
throughput than conventional cell selection methods and achieves less cell load variance between different
adjacent cells.
Ameliorate the performance using soft computing approaches in wireless networksIJECEIAES
Wireless sensor networks are an innovative and rapidly advanced network occupying the broad spectrum of wireless networks. It works on the principle of “use with less expense, effort and with more comfort.” In these networks, routing provides efficient and effective data transmission between different sources to access points using the clustering technique. This work addresses the low-energy adaptive clustering hierarchy (LEACH) protocol’s main backdrop of choosing head nodes based on a random value. In this, the soft computing methods are used, namely the fuzzy approach, to overcome this barrier in LEACH. Our approach’s primary goal is to extend the network lifetime with efficient energy consumption and by choosing the appropriate head node in each cluster based on the fuzzy parameters. The proposed clustering algorithm focused on two fuzzy inference structures, namely Mamdani and Sugeno fuzzy logic models in two scenarios, respectively. We compared our approach with four existing works, the conventional LEACH, LEACH using the fuzzy method, multicriteria cluster head delegation, and fuzzy-based energy efficient clustering approach (FEECA) in wireless sensor network. The proposed scenario based fuzzy LEACH protocol approaches are better than the four existing methods regarding stability, network survivability, and energy consumption.
Probability Density Functions of the Packet Length for Computer Networks With...IJCNCJournal
The research on Internet traffic classification and identification, with application on prevention of attacks
and intrusions, increased considerably in the past years. Strategies based on statistical characteristics of
the Internet traffic, that use parameters such as packet length (size) and inter-arrival time and their
probability density functions, are popular. This paper presents a new statistical modeling for packet length,
which shows that it can be modeled using a probability density function that involves a normal or a beta
distribution, according to the traffic generated by the users. The proposed functions has parameters that
depend on the type of traffic and can be used as part of an Internet traffic classification and identification
strategy. The models can be used to compare, simulate and estimate the computer network traffic, as well
as to generate synthetic traffic and estimate the packets processing capacity of Internet routers
Cellular wireless systems like GSM suffer from congestion resulting in overall system degradation and poor service delivery. When the traffic demand in a geographical area is high, the input traffic rate will exceed thecapacity of the output lines. This work focused on homogenous wireless network (the network traffic and resource dimensioning that are statistically identical) such that the network performance
evaluation can be reduced to a system with single cell and a single traffic type. Such system can employa queuing model to evaluate the performance metric of a cell in terms of blocking probability.
Five congestion control models were compared in the work to ascertain their peculiarities, they are Erlang B, Erlang C, Engset (cleared), Engset (buffered), and Bernoulli. To analyze the system, an aggregate onedimensional Markov chain wasderived, such that it describes a call arrival process under the assumption
that it is Poisson distributed. The models were simulated and their results show varying performances, however the Bernoulli model (Pb5) tends to show a situation that allows more users access to the system and the congestion level remain unaffected despite increase in the number of users and the offered traffic into the system.
Distributed Spatial Modulation based Cooperative Diversity Schemeijwmn
: In this paper, a distributed spatial modulation based cooperative diversity scheme for relay
wireless networks is proposed. Where, the space-time block code is exploited to integrate with distributed
spatial modulation. Therefore, the interested transmission scheme achieves high diversity gain. By using
Monte-Carlo simulation based on computer, we showed that our proposed transmission scheme outperforms
state-of-the-art cooperative relaying schemes in terms bit error rate (BER) performance.
PERFORMANCE AND REKEYING ANALYSIS OF MULTICAST SECURITY IN LTEIJCNCJournal
This document analyzes the performance and rekeying of multicast security in LTE networks. It compares two security solutions for multimedia broadcast multicast services (MBMS) in LTE - Group Security Association (GSA) and Secure Multicast Overlay (SMO). It models parameters for different multicast services like TV channels, Twitter, and Facebook. It calculates the computational and storage costs for rekeying using logical key hierarchy (LKH) tree with and without dynamic rekeying, and for changing the tree degree or height. The goal is to assess the performance of GSA and SMO solutions and determine which is more appropriate based on different parameters and services.
Data collection scheme for wireless sensor network with mobile collectorijwmn
In this paper, we investigate the problem of designing the minimum number of required mobile elements
tours such that each sensor node is either on the tour or one hop away from the tour, and the length of the
tour to be bounded by pre-determined value L. To address this problem, we propose heuristic-based
solution. This solution works by directing the mobile element tour towards the highly dense area in the
network. The experiment results show that our scheme outperform the benchmark scheme by 10% in most
scenarios.
The document proposes a novel geographic routing protocol called Multihop Delaunay Triangulation (MDT) that has two key properties: 1) guaranteed delivery of packets for any connected graph of nodes in d-dimensional space where d is greater than or equal to 2, and 2) low routing stretch from efficient forwarding of packets out of local minima. MDT provides guaranteed delivery even when node locations are inaccurate or arbitrary. Experimental results show MDT has the lowest routing stretch compared to other geographic routing protocols and maintains close to 100% routing success during network changes.
Testing and Improving Local Adaptive Importance Sampling in LFJ Local-JT in M...csandit
Multiply Sectioned Bayesian Network (MSBN) provides
a model for probabilistic reasoning in
multi-agent systems. The exact inference is costly
and difficult to be applied in the context of
MSBNs as the size of problem domain becomes larger
and complex. So the approximate
techniques are used as an alternative in such cases
. Recently, for reasoning in MSBNs, LJF-
based Local Adaptive Importance Sampler (LLAIS) has
been developed for approximate
reasoning in MSBNs. However, the prototype of LLAIS
is tested only on Alarm Network (37
nodes). But further testing on larger networks has
not been reported yet, so the scalability and
reliability of algorithm remains questionable. Henc
e, we tested LLAIS on three large networks
(treated as local JTs) namely Hailfinder (56 nodes)
, Win95pts (76 nodes) and PathFinder(109
nodes). From the experiments done, it is seen that
LLAIS without parameters tuned shows good
convergence for Hailfinder and Win95pts but not for
Pathfinder network. Further when these
parameters are tuned the algorithm shows considerab
le improvement in its accuracy and
convergence for all the three networks tested.
This document describes a context-aware automatic traffic notification system for cell phones that can learn a user's common destinations and routes over time using location and context data. It collects GPS and other data from users, identifies important locations through clustering, learns frequent routes between locations, and can predict a user's destination and route to then notify them of any traffic conditions. The system is implemented on a mobile phone to provide automated traffic alerts to users during their daily commutes without needing to manually enter a destination.
Flexible channel allocation using best Secondary user detection algorithmijsrd.com
This document proposes a flexible channel allocation algorithm for cooperative cognitive radio networks using secondary user detection. It introduces Flexible Channel Cooperation (FLEC) which allows secondary users to optimize their use of resources including channels and time slots from primary users. The document develops efficient resource allocation algorithms for FLEC, including a distributed bargaining algorithm and centralized heuristic algorithm. It evaluates the performance of FLEC and shows it provides throughput improvements of 20-60% over conventional identical channel cooperation. A centralized heuristic algorithm achieves near-optimal performance with only 5% loss compared to the optimal centralized algorithm, providing a good tradeoff between performance and complexity.
A mobile ad-hoc network (MANET) is a self structured infrastructure less network of mobile devices
connected by wireless. Each device in a MANET is free to move independently in any direction, and will
therefore change its links to other devices frequently. Load balancing is a technique to share out workload
across network links, to achieve maximize throughput, minimize response time, and avoid overload. Load
imbalance is a one of the critical issue in the ad-hoc network. Particle Swarm Optimization (PSO) method
is used to implement our proposed technique. In this Paper two algorithms are used for balancing the
nodes in the network. Identify the unfair nodes location next allocate and balance the load between the
nodes in the network. The simulation results show that this approach is more effective in terms of packet
delivery ratio, average end-to-end delay, load distribution, packet delay variation, packet reordering, and
throughput.
Use of Hidden Markov Mobility Model for Location Based ServicesIJERA Editor
These days people prefer to use portable and wireless devices such as laptops, mobile phones, They are connected through satellites. As user moves from one point to other, task of updating stored information becomes difficult. Provision of Location based services to users, faces some challenges like limited bandwidth and limited client power. To optimize data accessibility and to minimize access cost, we can store frequently accessed data item in cache of client. So small size of cache is introduced in mobile devices. Data fetched from server is stored on cache. So requested data from user is provided from cache and not from remote server. Question arises that which data should be kept in the cache? Performance of cache majorly depends on the cache replacement policies which select data suitable for eviction from cache. This paper presents use of Hidden Markov Models(HMMs) for prediction of user‟s future location. Then data item irrelevant to this predicted location is fetched out from the cache. The proposed approach clusters location histories according to their location characteristics and also it considers each user‟s previous actions. This results in producing high packet delivery ratio and minimum delay.
Mobile ad hoc networks – dangling issues of optimal path strategyAlexander Decker
The document discusses issues related to selecting optimal paths in mobile ad hoc networks. It proposes using a random direction mobility model to detect neighborhoods and trace paths between source and destination nodes. The model represents nodes moving in random directions for periods of time before pausing. The paper also discusses calculating the probability of link availability over time between two moving nodes based on their movements and developing a link maintenance probability model. An implementation of detecting neighborhoods using this low probability mobility model in Java is also described.
Location predictionin cellular network using neural networkIAEME Publication
1. The document discusses using neural networks for location prediction in cellular networks to improve location management and reduce costs.
2. It proposes using a backpropagation multilayer neural network trained on subscriber movement patterns to predict a subscriber's new location instead of traditional location management schemes.
3. The results show over 69% correct prediction for the random walk mobility pattern, which can help reduce location management costs by knowing a subscriber's location without paging all cells.
Game-Theoretic Channel Allocation in Cognitive Radio Networks IJECEIAES
Cognitive radio networks provide dynamic spectrum access techniques to support the increase in spectrum demand. In particular, the spectrum sharing among primary and secondary users can improve spectrum utilization in unused spectrum by primary users. In this paper, we propose a novel game theoretic channel allocation framework to maximize channel utilization in cognitive radio networks. We degisn the utility function based on the cochannel interference among primary and secondary users. In addition, we embed the property of the adjacent channel intererence to consider real wireless environment. The results show that the utility function converges quickly to Nash equilibrium and achieves channel gain by up to 25 dB compared to initial assignment.
The document discusses network routing and congestion control from a game-theoretic perspective. It describes routing as a game where users determine routes to minimize individual cost, and congestion control as a game where users determine data rates. Equilibrium points like the Nash equilibrium are analyzed. Selfish routing can lead to high costs compared to optimal routing.
Performance Analysis for Parallel MRA in Heterogeneous Wireless NetworksEditor IJCATR
This document analyzes methods for optimal path selection and power allocation in heterogeneous wireless networks where a user can transmit data through multiple radio access technologies (RATs) simultaneously. It formulates the bandwidth and power allocation problem as an optimization problem to maximize total system capacity. The Newton and modified Newton methods are proposed to find the optimal solution. Simulation results show the modified Newton method achieves higher total system capacity compared to the Newton method.
Selective Green Device Discovery for Device to Device CommunicationTELKOMNIKA JOURNAL
The D2D communication is expected to improve devices’ energy-efficiency, which has become a
major requirement of the future wireless network. Before the D2D communication can be performed, the
device discovery between devices must be done. The previous works usually only assumed one mode of
device discovery, i.e. either use network-assisted (with network supervision) or independent (without
network supervision) device. Therefore, we propose a selective device discovery for device-to-device
(D2D) communication that can utilize both device discovery modes and maintain devices’ energyefficiency.
Different from previous works, our proposed method selects the best device discovery mode to
get the best energy-efficiency. Moreover, to further improve the energy-efficiency, our proposed method
also deployed in D2D cluster with multiple cluster heads. The proposed method selects the most suitable
mode using thresholds (cluster energy consumption and new device acceptance) and cluster energy
expectation. Our experiment result indicates that the proposed method provides lowest energy
consumption per new accepted device while compared with schemes with full network-assisted and
independent device discovery in low numbers of new device arrival (for the number of new devices
arrival = 1 ~ 3).
DISTRIBUTED COVERAGE AND CONNECTIVITY PRESERVING ALGORITHM WITH SUPPORT OF DI...IJCSEIT Journal
Given a 3D space where should be supervised and a group of mobile sensor actor nodes with limited
sensing and communicating capabilities, this paper aims at proposing a distributed self-deployment
algorithm for agents to cover the space as much as possible by considering non-uniform sensing coverage
degree constraint of environment while preserving connectivity. The problem is formulated as coverage
maximization subject to connectivity and sensing coverage degree constraint. Considering a desired
distance between neighbouring nodes, an error function which depends on pairwise distance between
nodes is described. The maximization is encoded to an error minimization problem that is solved using
gradient descent algorithm and will yield in moving sensors into appropriate positions. Simulation results
are presented in two different conditions that importance of sensing coverage degree support of
environment is very high and is low.
A Weighted Duality based Formulation of MIMO SystemsIJERA Editor
This work is based on the modeling and analysis of multiple-input multiple-output (MIMO) system in downlink communication system. We take into account a recent work on the ratio of quadratic forms to formulate the weight matrices of quadratic norm in a duality structure. This enables us to achieve exact solutions for MIMO system operating under Rayleigh fading channels. We outline couple of scenarios dependent on the structure of eigenvalues to investigate the system behavior. The results obtained are validated by means of Monte Carlo simulations.
Novel cell selection proceduref lte hetnets based on mathematical modelling o...ijwmn
Femtocells have been considered one of the most important technologies in LTE networks to solve indoor
coverage problem, however the randomness deployment of femtocells, leads to great challenge for selecting
optimum serving cell. In this work, a new cell selection algorithm is proposed that enables new user to
select best serving cell whereas several factors are put into consideration other than highest instantaneous
SNR or maximum RSRP such as cell load .A new prediction algorithm is designed to predict the
performance of (PF) scheduling algorithm to calculate expected number of RBs to be scheduled to new
user, then reduction in achievable data rate due to both received SNR and instant cell load is estimated.
The numerical results show that the new proposed cell selection algorithm achieves higher average cell
throughput than conventional cell selection methods and achieves less cell load variance between different
adjacent cells.
Ameliorate the performance using soft computing approaches in wireless networksIJECEIAES
Wireless sensor networks are an innovative and rapidly advanced network occupying the broad spectrum of wireless networks. It works on the principle of “use with less expense, effort and with more comfort.” In these networks, routing provides efficient and effective data transmission between different sources to access points using the clustering technique. This work addresses the low-energy adaptive clustering hierarchy (LEACH) protocol’s main backdrop of choosing head nodes based on a random value. In this, the soft computing methods are used, namely the fuzzy approach, to overcome this barrier in LEACH. Our approach’s primary goal is to extend the network lifetime with efficient energy consumption and by choosing the appropriate head node in each cluster based on the fuzzy parameters. The proposed clustering algorithm focused on two fuzzy inference structures, namely Mamdani and Sugeno fuzzy logic models in two scenarios, respectively. We compared our approach with four existing works, the conventional LEACH, LEACH using the fuzzy method, multicriteria cluster head delegation, and fuzzy-based energy efficient clustering approach (FEECA) in wireless sensor network. The proposed scenario based fuzzy LEACH protocol approaches are better than the four existing methods regarding stability, network survivability, and energy consumption.
Performance Analysis of Massive MIMO Downlink System with Imperfect Channel S...IJRES Journal
We investigate the ergodic sum rate and required transmit power of a single-cell massive
multiple-input multiple-output (MIMO) downlink system. The system considered in this paper is based on two
linear beamforming schemes, that is, maximum ratio transmission (MRT) beamforming and zero-forcing (ZF)
beamforming. What’s more, we use minimum mean square error (MMSE) channel estimation to get imperfect
channel state information (CSI). Compared with the perfect CSI case, both theoretical analysis and simulation
results show that the system performance is different when the imperfect CSI is taken into account.
Analysis of LTE Radio Load and User ThroughputIJCNCJournal
A recurring topic in LTE radio planning pertains to the maximum acceptable LTE radio interface load, up to which a targeted user data rate can be maintained. We explore this topic by using Queuing Theory elements to express the downlink user throughput as a function of the LTE Physical Resource Block (PRB) utilization. The resulting formulas are expressed in terms of standardized 3GPP KPIs and can be readily evaluated from network performance counters. Examples from live networks are given to illustrate the results, and the suitability of a linear decrease model is quantified upon data from a commercial LTE network.
This document analyzes LTE radio load and user throughput. It explores the relationship between user throughput and LTE radio interface load (PRB utilization) using queuing theory. Formulas are presented to express downlink user throughput as a function of PRB utilization based on standardized 3GPP KPIs. Examples from live networks validate that user throughput decreases linearly with increasing PRB utilization, following a processor sharing model. The results provide a practical way to estimate user throughput from network statistics.
This document analyzes the relationship between LTE radio load and user throughput. It explores this topic using queuing theory to express downlink user throughput as a function of LTE Physical Resource Block (PRB) utilization. The resulting formulas are expressed in terms of standardized 3GPP KPIs and can be readily evaluated from network performance counters. Examples from live networks are provided to illustrate the results, and the suitability of a linear decrease model is quantified based on data from a commercial LTE network.
CONFIGURABLE TASK MAPPING FOR MULTIPLE OBJECTIVES IN MACRO-PROGRAMMING OF WIR...ijassn
Macro-programming is the new generation advanced method of using Wireless Sensor Network (WSNs), where application developers can extract data from sensor nodes through a high level abstraction of the system. Instead of developing the entire application, task graph representation of the WSN model presents simplified approach of data collection. However, mapping of tasks onto sensor nodes highlights several problems in energy consumption and routing delay. In this paper, we present an efficient hybrid approach of task mapping for WSN – Hybrid Genetic Algorithm, considering multiple objectives of optimization – energy consumption, routing delay and soft real time requirement. We also present a method to configure the algorithm as per user's need by changing the heuristics used for optimization. The trade-off analysis between energy consumption and delivery delay was performed and simulation results are presented. The algorithm is applicable during macro-programming enabling developers to choose a better mapping according to their application requirements.
CONFIGURABLE TASK MAPPING FOR MULTIPLE OBJECTIVES IN MACRO-PROGRAMMING OF WIR...ijassn
Macro-programming is the new generation advanced method of using Wireless Sensor Network (WSNs),
where application developers can extract data from sensor nodes through a high level abstraction of the
system. Instead of developing the entire application, task graph representation of the WSN model presents
simplified approach of data collection.
OPTIMIZED TASK ALLOCATION IN SENSOR NETWORKSZac Darcy
The document proposes an approach to optimize energy consumption in sensor networks. It allocates tasks to sensor nodes using a particle swarm optimization algorithm that considers energy for data communication between nodes. Simulation results show the proposed approach reduces energy consumption and increases network lifetime compared to existing approaches that only allocate tasks to cluster gateways. The key aspects of the proposed approach are using a cost function that includes communication energy in the task allocation algorithm and having nodes send combined data from neighboring nodes to reduce the number of messages.
This document proposes a heuristic algorithm for allocating users to subchannels in a large-scale non-orthogonal multiple access (NOMA) system. It uses a genetic algorithm approach where individuals represent possible user allocations, and are evaluated based on throughput. The algorithm randomly assigns initial user distances and allocations, then uses crossover to generate new allocations. Evaluation shows that throughput converges after a number of generations, and increasing the number of users increases both generations needed for convergence and execution time. Future work could use parallel processing to reduce execution time for large input scales.
Performance Analysis of Group-Blind Multiuser Detectors for Synchronous CDMAidescitation
This document analyzes the performance of group-blind multiuser detectors for synchronous CDMA systems. It presents three detectors - Direct Matrix Inversion (DMI), Subspace, and Group-Blind Multiuser Detector. Through MATLAB simulations, it compares the Signal to Interference plus Noise Ratio (SINR) and Bit Error Rate (BER) of the three detectors. The results show that the Group-Blind Multiuser Detector achieves higher SINR than the DMI and Subspace detectors, especially when more user spreading sequences are known. In general, the performance of all detectors improves with increasing SNR, number of samples, and known users, but degrades with increasing signal correlation and number of total users
Performance Analysis of Bfsk Multi-Hop Communication Systems Over K-μ Fading ...ijwmn
Multi-hop communication systems gained popularity in wireless communications; they can be used to
extend the coverage of the network and reduce the transmitted power. The transmission of data from the
source node to the destination node in multi-hop communications undergoes through intermediate relay
nodes. In this paper, we study the performance of multi-hop communication systems, in terms of average bit
error rate (BER) with Binary frequency shift keying assuming the κ-µ fading channel model. Due to the
difficulty in finding the probability density function (PDF) of the end-to-end signal to noise ratio (SNR) and
hence for the performance metrics, we use Gaussian Mixture (GM) approximation technique to
approximate the PDF of the end to end SNR assuming the κ-µ fading models as weighted sums of Gaussian
distributions. Numerical results are provided for the BER of binary frequency shift keying (BFSK) of
amplify and forward (AF) multi-hop communication systems assuming different values for the fading
parameters (, ) and for different number of hops. Numerical results are validated by comparing them
with simulation results.
Congestion control based on sliding mode control and scheduling with prioriti...eSAT Publishing House
This document presents a method for joint congestion control and scheduling in wireless networks using sliding mode control. It formulates the problem using network utility maximization to maximize total utility while satisfying capacity constraints. Dual decomposition is used to separate the problem into congestion control and scheduling subproblems. A sliding mode controller is designed for congestion control based on queue length feedback. The scheduling problem depends on Lagrangian prices from the congestion control problem. Simulation results show improved packet delivery ratio, throughput, and performance under varying signal-to-noise ratios. The method jointly optimizes congestion control and scheduling using a sliding mode approach.
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.
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.
Energy efficient resources allocations for wireless communication systemsTELKOMNIKA JOURNAL
The energy consumption level of the telecommunication process has become a new
consideration in resource management scheme. It is becoming a new parameter in the resource
management scheme besides throughput, spectral efficiency, and fairness. This work proposes a power
control scheme and user grouping method to keep the rational energy consumption level of the resource
management scheme. Inverse water-filling power allocation is a power allocation scheme that optimizes
the energy efficiency by giving the power to the user which have good channel conditions. The user
grouping method becomes the solution for carrier aggregation (CA) scheme that prevents edge cell user
get the resources from the high-frequency carrier. This can prevent energy wastage in the transmission
process. This power control scheme and user grouping method can optimize the spectral and energy
efficiency without increasing the time complexity of the system.
Capacity improvement of mimo ofdma system using adaptive resource allocation ...eSAT Publishing House
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.
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.
Rendezvous Sequence Generation Algorithm for Cognitive Radio Networks in Post...IJCNCJournal
Recent natural disasters have inflicted tremendous damage on humanity, with their scale progressively increasing and leading to numerous casualties. Events such as earthquakes can trigger secondary disasters, such as tsunamis, further complicating the situation by destroying communication infrastructures. This destruction impedes the dissemination of information about secondary disasters and complicates post-disaster rescue efforts. Consequently, there is an urgent demand for technologies capable of substituting for these destroyed communication infrastructures. This paper proposes a technique for generating rendezvous sequences to swiftly reconnect communication infrastructures in post-disaster scenarios. We compare the time required for rendezvous using the proposed technique against existing methods and analyze the average time taken to establish links with the rendezvous technique, discussing its significance. This research presents a novel approach enabling rapid recovery of destroyed communication infrastructures in disaster environments through Cognitive Radio Network (CRN) technology, showcasing the potential to significantly improve disaster response and recovery efforts. The proposed method reduces the time for the rendezvous compared to existing methods, suggesting that it can enhance the efficiency of rescue operations in post-disaster scenarios and contribute to life-saving efforts.
Blockchain Enforced Attribute based Access Control with ZKP for Healthcare Se...IJCNCJournal
The relationship between doctors and patients is reinforced through the expanded communication channels provided by remote healthcare services, resulting in heightened patient satisfaction and loyalty. Nonetheless, the growth of these services is hampered by security and privacy challenges they confront. Additionally, patient electronic health records (EHR) information is dispersed across multiple hospitals in different formats, undermining data sovereignty. It allows any service to assert authority over their EHR, effectively controlling its usage. This paper proposes a blockchain enforced attribute-based access control in healthcare service. To enhance the privacy and data-sovereignty, the proposed system employs attribute-based access control, zero-knowledge proof (ZKP) and blockchain. The role of data within our system is pivotal in defining attributes. These attributes, in turn, form the fundamental basis for access control criteria. Blockchain is used to keep hospital information in public chain but EHR related data in private chain. Furthermore, EHR provides access control by using the attributed based cryptosystem before they are stored in the blockchain. Analysis shows that the proposed system provides data sovereignty with privacy provision based on the attributed based access control.
EECRPSID: Energy-Efficient Cluster-Based Routing Protocol with a Secure Intru...IJCNCJournal
A revolutionary idea that has gained significance in technology for Internet of Things (IoT) networks backed by WSNs is the " Energy-Efficient Cluster-Based Routing Protocol with a Secure Intrusion Detection" (EECRPSID). A WSN-powered IoT infrastructure's hardware foundation is hardware with autonomous sensing capabilities. The significant features of the proposed technology are intelligent environment sensing, independent data collection, and information transfer to connected devices. However, hardware flaws and issues with energy consumption may be to blame for device failures in WSN-assisted IoT networks. This can potentially obstruct the transfer of data. A reliable route significantly reduces data retransmissions, which reduces traffic and conserves energy. The sensor hardware is often widely dispersed by IoT networks that enable WSNs. Data duplication could occur if numerous sensor devices are used to monitor a location. Finding a solution to this issue by using clustering. Clustering lessens network traffic while retaining path dependability compared to the multipath technique. To relieve duplicate data in EECRPSID, we applied the clustering technique. The multipath strategy might make the provided protocol more dependable. Using the EECRPSID algorithm, will reduce the overall energy consumption, minimize the End-to-end delay to 0.14s, achieve a 99.8% Packet Delivery Ratio, and the network's lifespan will be increased. The NS2 simulator is used to run the whole set of simulations. The EECRPSID method has been implemented in NS2, and simulated results indicate that comparing the other three technologies improves the performance measures.
Analysis and Evolution of SHA-1 Algorithm - Analytical TechniqueIJCNCJournal
A 160-bit (20-byte) hash value, sometimes called a message digest, is generated using the SHA-1 (Secure Hash Algorithm 1) hash function in cryptography. This value is commonly represented as 40 hexadecimal digits. It is a Federal Information Processing Standard in the United States and was developed by the National Security Agency. Although it has been cryptographically cracked, the technique is still in widespread usage. In this work, we conduct a detailed and practical analysis of the SHA-1 algorithm's theoretical elements and show how they have been implemented through the use of several different hash configurations.
Optimizing CNN-BiGRU Performance: Mish Activation and Comparative AnalysisIJCNCJournal
Deep learning is currently extensively employed across a range of research domains. The continuous advancements in deep learning techniques contribute to solving intricate challenges. Activation functions (AF) are fundamental components within neural networks, enabling them to capture complex patterns and relationships in the data. By introducing non-linearities, AF empowers neural networks to model and adapt to the diverse and nuanced nature of real-world data, enhancing their ability to make accurate predictions across various tasks. In the context of intrusion detection, the Mish, a recent AF, was implemented in the CNN-BiGRU model, using three datasets: ASNM-TUN, ASNM-CDX, and HOGZILLA. The comparison with Rectified Linear Unit (ReLU), a widely used AF, revealed that Mish outperforms ReLU, showcasing superior performance across the evaluated datasets. This study illuminates the effectiveness of AF in elevating the performance of intrusion detection systems.
An Hybrid Framework OTFS-OFDM Based on Mobile Speed EstimationIJCNCJournal
The Future wireless communication systems face the challenging task of simultaneously providing high-quality service (QoS) and broadband data transmission, while also minimizing power consumption, latency, and system complexity. Although Orthogonal Frequency Division Multiplexing (OFDM) has been widely adopted in 4G and 5G systems, it struggles to cope with a significant delay and Doppler spread in high mobility scenarios. To address these challenges, a novel waveform named Orthogonal Time Frequency Space (OTFS). Designers aim to outperform OFDM by closely aligning signals with the channel behaviour. In this paper, we propose a switching strategy that empowers operators to select the most appropriate waveform based on an estimated speed of the mobile user. This strategy enables the base station to dynamically choose the waveform that best suits the mobile user’s speed. Additionally, we suggest retaining an Integrated Sensing and Communication (ISAC) radar approach for accurate Doppler estimation. This provides precise information to facilitate the waveform selection procedure. By leveraging the switching strategy and harnessing the Doppler estimation capabilities of an ISAC radar.Our proposed approach aims to enhance the performance of wireless communication systems in high mobility cases. Considering the complexity of waveform processing, we introduce an optimized hybrid system that combines OTFS and OFDM, resulting in reduced complexity while still retaining performance benefits.This hybrid system presents a promising solution for improving the performance of wireless communication systems in higher mobility.The simulation results validate the effectiveness of our approach, demonstrating its potential advantages for future wireless communication systems. The effectiveness of the proposed approach is validated by simulation results as it will be illustrated.
Enhanced Traffic Congestion Management with Fog Computing - A Simulation-Base...IJCNCJournal
Accurate latency computation is essential for the Internet of Things (IoT) since the connected devices generate a vast amount of data that is processed on cloud infrastructure. However, the cloud is not an optimal solution. To overcome this issue, fog computing is used to enable processing at the edge while still allowing communication with the cloud. Many applications rely on fog computing, including traffic management. In this paper, an Intelligent Traffic Congestion Mitigation System (ITCMS) is proposed to address traffic congestion in heavily populated smart cities. The proposed system is implemented using fog computing and tested in a crowdedCairo city. The results obtained indicate that the execution time of the simulation is 4,538 seconds, and the delay in the application loop is 49.67 seconds. The paper addresses various issues, including CPU usage, heap memory usage, throughput, and the total average delay, which are essential for evaluating the performance of the ITCMS. Our system model is also compared with other models to assess its performance. A comparison is made using two parameters, namely throughput and the total average delay, between the ITCMS, IOV (Internet of Vehicle), and STL (Seasonal-Trend Decomposition Procedure based on LOESS). Consequently, the results confirm that the proposed system outperforms the others in terms of higher accuracy, lower latency, and improved traffic efficiency.
Rendezvous Sequence Generation Algorithm for Cognitive Radio Networks in Post...IJCNCJournal
Recent natural disasters have inflicted tremendous damage on humanity, with their scale progressively increasing and leading to numerous casualties. Events such as earthquakes can trigger secondary disasters, such as tsunamis, further complicating the situation by destroying communication infrastructures. This destruction impedes the dissemination of information about secondary disasters and complicates post-disaster rescue efforts. Consequently, there is an urgent demand for technologies capable of substituting for these destroyed communication infrastructures. This paper proposes a technique for generating rendezvous sequences to swiftly reconnect communication infrastructures in post-disaster scenarios. We compare the time required for rendezvous using the proposed technique against existing methods and analyze the average time taken to establish links with the rendezvous technique, discussing its significance. This research presents a novel approach enabling rapid recovery of destroyed communication infrastructures in disaster environments through Cognitive Radio Network (CRN) technology, showcasing the potential to significantly improve disaster response and recovery efforts. The proposed method reduces the time for the rendezvous compared to existing methods, suggesting that it can enhance the efficiency of rescue operations in post-disaster scenarios and contribute to life-saving efforts.
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.
May 2024, Volume 16, Number 3 - The International Journal of Computer Network...IJCNCJournal
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.
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.
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.
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.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
1. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
DOI: 10.5121/ijcnc.2017.9503 31
A LOW COMPLEXITY USER GROUPING STRATEGY
FOR DOWNLINK MULTI-USER MIMO SCHEDULING
Nguyen Ngoc Van
School of Electronics and Telecommunications, Hanoi University of Science and
Technology, No 1 , Dai Co Viet Street, Hai Ba Trung, HaNoi, Vietnam
ABSTRACT
In this paperwe present a low complexity user grouping algorithm for multi-user MIMO system employing
opportunistic fair scheduling (OFS) and zero forcing beamforming (ZFB), and develop a framework for
cross-layer resource scheduling. Given a particular subset of users and their channel conditions, the
optimal beamforming scheme can be calculated. The multi-user esource scheduling problem then refers to
the selection of the optimal subset of users for transmission at each time instant to maximize the total
throughput of the system. The simulation result shows that the performance of resource scheduling
algorithm based on user grouping method proposed in this paper is close to the optimal performance which
used exhaustion method. In addition, user grouping does not affect the fairness among all users.
KEYWORDS
Opportunistic fair scheduling (OFS); zero-forcing beamforming (ZFB);
1. INTRODUCTION
In the last mid-1990s, Telatar, Foschini and Gans proved that Multiple-Input Multiple-Output
(MIMO) techniques can notably increase the channel capacity and diversity gain under the
condition of ideal propagation channel model[1][2], theoretically MIMO channel capacity
enhances linearly with the number of transmitting and receiving antenna. Since then researchers
concentrated on digging up the potential diversity gain and multiplexing gain. Unremitting efforts
by scholars in the field of information theory[3][4], people gradually realized that capacity of
multi-user MIMO system is much more than point-to-point system.
In strategies of multi-user transmission, the uppermost one is precoding method, i.e. base-station
form a wave beam pointed to the thereby precoding can also be called beam-forming technique.
In the implementation perspective, precoding algorithms for multi-user MIMO can be sub-
divided into linear and nonlinear precoding types. Linear precoding approaches such as zero-
forcing (ZF)[5] can achieve reasonable throughput performance with low complexity relative to
nonlinear precoding approaches. Nonlinear precoding can achieve near optimal capacity at the
expense of complexity and designed based on the concept of Dirty paper coding (DPC)[6] which
shows that any known interference at the transmitter can be subtracted without the penalty of
radio resources if the optimal precoding scheme can be applied to the transmit signal.
Due to the rank condition imposed by the fact that each user’s precodingmatrix lies in the null
space of all other user’s channels[7], the number of users that can be simultaneously supported
with ZF is limited by the number of transmit antennas. For example, for a single antenna users’
caseM ≥ K has to be satisfied for complete zero forcing, where M and K denote the number of
transmit antennas at the BS and the total number of users in the system. So we have to select a
subset of users before the process of resource scheduling, and this result of selection will directly
affect the performance of the system.
Therefore, user subset selection and resource allocation are two core problems of multiuser
MIMO system resource scheduling. In this paper, we establish a general cross-layer resource
2. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
32
scheduling model. For the first problem, we propose one user subset selection algorithm with the
aim of maximizing the system utility function. For the second we adopt the Opportunistic Fair
Scheduling(OFS)[8][9] which can balance the performance of the system and the fair of users.
The rest of this paper is organized as follows. Section II describes the downlink multiuser MIMO
system including the user subset selection and beamforming scheme. Section III formulates the
user subset selection problem and proposes the low-complexity algorithm for solving it. In
section IV, we present a cross-layer resource scheduling strategy based on the OFS employing the
algorithm of section III. Simulation results are given in Section V. Section VI contains the
conclusions.
2. SYSTEM MODEL
We consider a downlink of a multiuser MIMO system as shown in Figure 1 with N transmit
antennas and N receive antennas at its mobile user. Each user estimates their respective channel
state information (CSI) and feedbacks them to BS, let H ϵ , denote the downlink channel
of the ith user. The scheduler select one subset of the user to the data according to system QoS
requirement and user’s CSI, then finish the physical layer mapping at the side BS.
We assume the frame structure of physical layer is composed of TDM slot with L assignable slots
in the system, so the maximal number of user subsets is L as described in Figure 2. It is known
that any multiuser MIMO algorithm may have some constraints of the number of transmit and
receiving antennas. Take the block diagonalizationbeamforming (DBB)[10] for example, this
algorithm demands for null space of all other users, i.e. N ∑ N, , ∀k. When the number
of transmit antenna cannot constraint, the scheduler sfirst choose a subset of users, the result of
selection will directly affect the performance of a system
Figure 1. Downlink multiuser MIMO system
Figure 2. Structure of downlink multiuser MIMO frame
User Subset
Selection&Pre_
processing
N1
N2
.
.
.
NT
User 1
User 2
User K
.
.
.
CSI
3. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
33
In a practical system, not only does scheduler consider the overall performance of the system
takes account oof the fairness among all users. We introduce the concept of utility function which
can reflect the degree of satisfaction of users to some extent, and system utility function can be
defined as the total sum of all user utilities. We suppose the transmission rate of user k is r with
corresponding utility function expressed as U (r ), then the task of schedule is select one subset
of users to maximize the system utility function, denoted as
Ω(G, r) = arg max
'⊆ ,)
* U (r )
∈'
(1)
where G is a set of users be transmitted,r = -r , … r / represents as rate allocation vector of users
concerned with the physical layer transmission scheme, K is global users, Ω(G, r) denoted as the
optimal scheduling strategy. It will theoretically be capable of finding out the best subset by the
means of exhaustion method, whereas the complexity of calculation is too high to practical
application. Consequently, low-complexity user grouping algorithm of necessity be presented.
3. USER GROUPING
We define a coefficient 012 for mutual correlations between user i and user j, expressed
as 012 = 4142, where 41 denotes the normalization factor of user i, i.e. 41 = 51/‖51‖8.
The channel state information ℋ1 can be acquired by the base-station. 012 = 0indicates
user i and user j are completely orthogonal; 012 = 1 means correlative; as a general rule,
0 < 012 < 1. Specifically, we set a threshold ρ. The user with a correlation higher than ρ
is considered as highly correlated and are assigned to the different user subset. The
correlation coefficient of any two users in one subset is lower than ρ. We next describe
the algorithm of user subset selection. In this case, the assumption of channel state
information as previously stated has already known in base-station.
The explicit steps of the algorithm are as follows:
Step1 : Construct the matrix = of mutual correlations >?@, i.e. = = ->?@/. =takes the empirical
value.
Step 2 : Search for one oftheaximum mutual correlations >AB, if >AB C, make the user A
and user B the first user of subset 1 and subset 2 respectively, represented as DE
E
and DE
F
.
Step 3 : Select users of its correlations with DE
E
smaller than G as the candidate set of subset 1,
then add the user from this set with best orthogonality to subset 1.
Step 4 : Find users of correlation with DF
E
smaller than G as the candidate set of subset 1, choose
the next user of subset 1 in the same way.
Step 5 : Repeat step 4 until the number of users in one subset is up to system constraints or the
candidate set is empty.
Step 6 : New subset will be generated, provided that there are users not assigned to any subset
and their correlations with “new user” are higher than G.
Step 7 : If the number of subsets exceeds the assignable time slot L, we may augment the value
of G in order to reduce the quantity.
4. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
34
For example, consider a five-user case. If the correlation matrix is
1 0.02 0.22 0.37 0.41
0.02 1 0.18 0.30 0.47
0.22 0.18 1 0.34 0.18
0.37 0.30 0.34 1 0.28
0.41 0.47 0.18 0.28 1
ℜ =
and ρ = 0.2, then the users are divided into three subsets, S = -2 1/, S8 = -5 3/, and
SM = -5/. Likewise, if ρ = 0.3, then the users are divided into two subsets, S =
-2 1 3/, S8 = -5 3 2 4/. If there are 16 users in one system, the relationship
between grouping number and ρ is as Figure 3.
Figure 3. Subset division results for different threshold value.
4. CROSS-LAYER RESOURCE SCHEDULING
A generalized architecture for the OFS in downlink wireless system is proposed in [13,14] and we
introduce a new user subset selection module on the basis of OFS as shown in Figure 4. Suppose
that there are in total N users in the system. Result of user subset selection is G = -G , G8, … GO},
where M is the sum of subsets.
Figure 4. Cross-layer resource scheduling based on user subset selection.
5. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
35
It is seen from Fig. 4 that at the scheduling interval corresponding to the ith time slot, the inputs
to the scheduler are data flows of selected users, and the control parameters produced by the
controller:
P i = {P i , P8 i … , P i } .
The scheduler makes the decision of the rates of selected users X i = {X i , X8 i , … X i } for
the slot i. We have XR i ≥ 0, those satisfying XR i > 0 is chosen as active users in the currently
scheduled subset. The weighted sum rate of mth subset GS is defined as
Ω GS, i = * P i X i 2
∈'T
On the other hand, the inputs to the controller corresponding to the Uth time slot are the
throughput priorities of users ∅ = W∅ , ∅8, … , ∅ X and the rate decision X i output by (2). The
deterministic fairness constraint is given by [8]
∅
Y{X i }
=
∅8
Y{X8 i }
= ⋯ =
∅
Y{X i }
3
In practical systems, Y{X i can normally be calculated as the average throughput over a finite-
length window. The least mean square-type algorithm is employed to solve the problem of
updating the fairness weights P i [9], denoted a vector as
fP i ] = ^f P i ], f8P i ], … , f P i ]_
≜
∅
∑ ∅aa
− Y c
X i, P i
∑ Xa i, P ia
d
Define the unbiased noisy observation of fP i ] as
yi, P i ] = ^y P i ], y8P i ], … , y P i ]_
≜
∅
∑ ∅aa
−
X i, P i
∑ Xa i, P ia
Then, at each control interval, the weight vector P i is updated as[12][13]
P i + 1 = P i − 4 i yi, P i ] 4
For a zero-forcing beam-forming(ZFB) system, the beam-forming vector of selected user can be
calculated as[16]
= HWHHg
Xh
D 5
where D = diag d , … , dS , d = 1/k{WHHgXh } , , m is the number of users. The minimum
SINR requirement and power allocation vector are denoted as {γS R
, … , γR
S R
}and {m , … mR},
total power meets the restraint condition that ∑ m ≤R
oSpq. Let r as the beam-forming vector
of user i, the received SINR is [16]
SINR =
m d8
σ8
6
6. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
36
The minimum constraint condition of users is expressed as η = min y yR
z{ |
}
≥ 1, we can also
obtain the conclusion that[11]
η =
PSpq
σ8 ∑
}
•€
R
7
Then, if η ≥ 1, the power allocation of users can be represented as
p = η
σ8γ
d8 , i = 1, … , m 8
In conclusion, the weighted sum rate of users is denoted as
Ω GS, i = * P i
∈'T
log8 1 + γ η
= * P i
∈'T
log8 †1 +
γ PSpq
σ8 ∑
}
•€
R
‡ 9
Finally, we propose the resource scheduling algorithm based on the user subset selection.
Step 1: Calculate ‰ according to (7), if ‰ ≥ E, turn to step 2, or else move out the newest user
of selected subset until ‰ ≥ E.
Step 2: For each subset, calculate Š ‹Œ, • according to (9), and choose the best subset to
regard as the final decision of scheduling, i.e.
Ž • = ••‘ Œ•’
‹Œ∈‹
Š ‹Œ, • 10
Step 3: Update weighs coefficients according to (4),
“ • + E = “ • − ” • ••, “ • ]
where” • is a small positive value to ensure the convergence.
5. SIMULATION RESULTS
In this section, we evaluate the performance of resource scheduling algorithm based on user
subset selection as mentioned above. The simulation conditions are as follows. The number of
transmit antennas at the BS is N = 4, N| = 1 at MS; the total number of users in the system is
N = 16; the transmit and noise power are PSpq = 1 and σ8
= 0.25; the objective SINR is
γS R = 1.
A. Efficiency Of Subset Seletion
We first compare the performance of instantaneous sum rate with the method of exhaustion. The
threshold is ρ = 0.25; simulation time is 50 slot. As depicted in Figure 5, the performance of
algorithm mentioned above is close to that of exhaustion method. It is well worth exchanging
small degradation of performance to the large reduction of computational complexity. The
principle cause of this degradation is that the period of subset selection is much longer than
scheduled, the computational complexity of grouping can be considered negligible. Under the
7. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
37
condition of this simulation, number of user subsets are 9, the corresponding calculated amount is
9, while the exhaustion method is – + –
8
+ –
M
+ –
—
= 2516.
Figure 5. The comparison of the throughput
B. Effect of threshold value G
Figure 6. Throughput changes with threshold value C
Next, we observe the system throughput while the threshold value ρ increases from 0.1 to 0.9 as
shown in Figure 6. The performance climbs when ρ is from 0.1 to 0.3, but declines in residual
value. The reason for this phenomenon is explained as follows. When ρ is very small approached
to zero, the criterion for spatial orthogonality is very strict, then there may be just one or two
users in one subset that limits the gain of multiplexing. When ρ takes a relatively large value,
more spatial correlative users access to a sub set that causes the decrease of performance.
C. Fairness of users
Thirdly, we review another crucial index of resource scheduling: fairness. The prospective
throughput proportion of the 16 users is ∅ = ∅8 = ⋯ = ∅ – = 1/16. The fairness as shown in
Fig.8 when the time slots is 1000 is better than the case in Figure 7 for 500 time slots. This result
8. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
38
corresponds with long-term fairness feature of OFS [13] and demonstrates user grouping does not
destroy the fairness between all of the users.
Figure 7. User average throughput during 500 slots
Fig.ure 8. User average throughput during 1000 slots
6. CONCLUSIONS
We have developed a framework for downlink multiuser MIMO system employing multiple
transmit antennas, beam forming, and user subset selection to achieve efficient resource
scheduling. Subset selection algorithm in this paper guarantee system satisfies the requirement for
preprocessing meanwhile not brings the system large computational amount. We present
simulation results to demonstrate that the grouping algorithm can effectively find the optimal user
9. International Journal of Computer Networks & Communications (IJCNC) Vol.9, No.5, September 2017
39
subset with good convergence performance, enhances the system spectrum efficiency and greatly
reduces the complexity of resource scheduling.
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AUTHORS
Nguyen Ngoc Van is a lecturer at School of Electronics and Telecommunications in Hanoi
University of Science and Technology (HUST). He received the degree of Bachelor and
Master in Electronics and Telecommunications from HUST, Vietnam, in 2000 and 2003.
From 2009 to 2012 he pursues his PhD degree in communication engineering at Tongji
University, Shanghai, China. His main interests are in Relaying and MIMO technologies
inbroadbandwirelesscommunication.