Wireless Sensor Networks (WSNs) are experiencing a revival of interest and a continuous advancement in various scientific and industrial fields. WSNs offer favorable low cost and readily deployable solutions to perform the monitoring, target tracking, and recognition of physical events. The foremost step required for these types of ad-hoc networks is to deploy all the sensor nodes in their positions carefully to form an efficient network. Such network should satisfy the quality of service (QoS) requirements in order to achieve high performance levels. In
this paper we address the coverage requirement and its relation with WSN nodes placement problems. In fact, we present a new optimization approach based on the Flower Pollination Algorithm (FPA) to find the best placement topologies in terms of coverage maximization. We have compared the performance of the resulting algorithm, called FPACO, with the original practical swarm optimization (PSO) and the genetic algorithm (GA). In all the test instances, FPACO performs better than all other algorithms.
ENHANCED PARTICLE SWARM OPTIMIZATION FOR EFFECTIVE RELAY NODES DEPLOYMENT IN ...IJCNCJournal
One of the critical design problems in Wireless Sensor Networks (WSNs) is the Relay Node Placement
(RNP) problem. Inefficient deployment of RNs would have adverse effects on the overall performance and
energy efficiency of WSNs. The RNP problem is a typical example of an NP-hard optimization problem
which can be addressed using metaheuristics with multi-objective formulation. In this paper, we aimed to
provide an efficient optimization approach considering the unconstrained deployment of energy-harvesting
RNs into a pre-established stationary WSN. The optimization was carried out for three different objectives:
energy consumption, network coverage, and deployment cost. This was approached using a novel
optimization approach based on the integration of the Particle Swarm Optimization (PSO) algorithm and a
greedy technique. In the optimization process, the greedy algorithm is an essential component to provide
effective guidance during PSO convergence. It supports the PSO algorithm with the required information
to efficiently alleviate the complexity of the PSO search space and locate RNs in the spots of critical
significance. The evaluation of the proposed greedy-based PSO algorithm was carried out with different
WSN scenarios of varying complexity levels. A comparison was established with two PSO variants: the
classical PSO and a PSO hybridized with the pattern search optimizer. The experimental results
demonstrated the significance of the greedy algorithm in enhancing the optimization process for all the
considered PSO variants. The results also showed how the solution quality and time efficiency were
considerably improved by the proposed optimization approach. Such improvements were achieved using a
simple integration technique without adding to the complexity of the system and introducing additional
optimization stages. This was more evident in the RNP scenarios of considerably large search spaces, even
with highly complex and challenging setups.
Wireless Sensor Network Based Clustering Architecture for Cooperative Communi...ijtsrd
We propose clusters based cooperatives based verbal architecture coop on the cellular ad hoc wireless sensor network Mawsn with the environment fading Rayleigh. The main ability and contributions of this paper are as follows. First, the proposed cage uses a cluster as a underlying system to help stable transmission services. 2D, the proposed enclosure uses a cluster based verbal cooperative exchange to effectively guide the package delivery ratio with multi hop power saving transmission. 0.33, we do not forget reasonable methods mainly based on cellular ad hoc nodes with sensing features and constant sensor nodes in the sensor field along with conventional research for the introduction of constant network sensors. Fourth, we have theoretical analysis with blackouts opportunities for proposed cooperative transmissions. Overall performance evaluation is run through simulation and evaluation. Sweeti Kumari | Dr. Ranjan Kumar Singh "Wireless Sensor Network Based Clustering Architecture for Cooperative Communication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43670.pdf Paper URL: https://www.ijtsrd.comengineering/electronics-and-communication-engineering/43670/wireless-sensor-network-based-clustering-architecture-for-cooperative-communication/sweeti-kumari
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
AN EFFICIENT INTRUSION DETECTION SYSTEM WITH CUSTOM FEATURES USING FPA-GRADIE...IJCNCJournal
An efficient Intrusion Detection System has to be given high priority while connecting systems with a network to prevent the system before an attack happens. It is a big challenge to the network security group to prevent the system from a variable types of new attacks as technology is growing in parallel. In this paper, an efficient model to detect Intrusion is proposed to predict attacks with high accuracy and less false-negative rate by deriving custom features UNSW-CF by using the benchmark intrusion dataset UNSW-NB15. To reduce the learning complexity, Custom Features are derived and then Significant Features are constructed by applying meta-heuristic FPA (Flower Pollination algorithm) and MRMR (Minimal Redundancy and Maximum Redundancy) which reduces learning time and also increases prediction accuracy. ENC (ElasicNet Classifier), KRRC (Kernel Ridge Regression Classifier), IGBC (Improved Gradient Boosting Classifier) is employed to classify the attacks in the datasets UNSW-CF, UNSW and recorded that UNSW-CF with derived custom features using IGBC integrated with FPA provided high accuracy of 97.38% and a low error rate of 2.16%. Also, the sensitivity and specificity rate for IGB attains a high rate of 97.32% and 97.50% respectively.
ON THE PERFORMANCE OF INTRUSION DETECTION SYSTEMS WITH HIDDEN MULTILAYER NEUR...IJCNCJournal
Deep learning applications, especially multilayer neural network models, result in network intrusion detection with high accuracy. This study proposes a model that combines a multilayer neural network with Dense Sparse Dense (DSD) multi-stage training to simultaneously improve the criteria related to the performance of intrusion detection systems on a comprehensive dataset UNSW-NB15. We conduct experiments on many neural network models such as Recurrent Neural Network (RNN), Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), etc. to evaluate the combined efficiency with each model through many criteria such as accuracy, detection rate, false alarm rate, precision, and F1-Score.
AN OPTIMIZED WEIGHT BASED CLUSTERING ALGORITHM IN HETEROGENEOUS WIRELESS SENS...cscpconf
The last few years have seen an increased interest in the potential use of wireless sensor networks (WSNs) in various fields like disastermanagementbattle field surveillance, and border security surveillance. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. The process of dividing the network into interconnected substructures is called clustering and the interconnected substructures are called clusters. The cluster head (CH) of each cluster act as a coordinator within the substructure. Each CH acts as a temporary base station within its zone or cluster. It also communicates with other CHs. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but
some nodes may be of different characteristics to prolong the lifetime of a WSN and its reliability. We have proposed an algorithm for better cluster head selection based on weights for different parameter that influence on energy consumption which includes distance from base station as a new parameter to reduce number of transmissions and reduce energy consumption by sensor nodes. Finally proposed algorithm compared with the WCA, IWCA algorithm in terms of number of clusters and energy consumption.
ENHANCED PARTICLE SWARM OPTIMIZATION FOR EFFECTIVE RELAY NODES DEPLOYMENT IN ...IJCNCJournal
One of the critical design problems in Wireless Sensor Networks (WSNs) is the Relay Node Placement
(RNP) problem. Inefficient deployment of RNs would have adverse effects on the overall performance and
energy efficiency of WSNs. The RNP problem is a typical example of an NP-hard optimization problem
which can be addressed using metaheuristics with multi-objective formulation. In this paper, we aimed to
provide an efficient optimization approach considering the unconstrained deployment of energy-harvesting
RNs into a pre-established stationary WSN. The optimization was carried out for three different objectives:
energy consumption, network coverage, and deployment cost. This was approached using a novel
optimization approach based on the integration of the Particle Swarm Optimization (PSO) algorithm and a
greedy technique. In the optimization process, the greedy algorithm is an essential component to provide
effective guidance during PSO convergence. It supports the PSO algorithm with the required information
to efficiently alleviate the complexity of the PSO search space and locate RNs in the spots of critical
significance. The evaluation of the proposed greedy-based PSO algorithm was carried out with different
WSN scenarios of varying complexity levels. A comparison was established with two PSO variants: the
classical PSO and a PSO hybridized with the pattern search optimizer. The experimental results
demonstrated the significance of the greedy algorithm in enhancing the optimization process for all the
considered PSO variants. The results also showed how the solution quality and time efficiency were
considerably improved by the proposed optimization approach. Such improvements were achieved using a
simple integration technique without adding to the complexity of the system and introducing additional
optimization stages. This was more evident in the RNP scenarios of considerably large search spaces, even
with highly complex and challenging setups.
Wireless Sensor Network Based Clustering Architecture for Cooperative Communi...ijtsrd
We propose clusters based cooperatives based verbal architecture coop on the cellular ad hoc wireless sensor network Mawsn with the environment fading Rayleigh. The main ability and contributions of this paper are as follows. First, the proposed cage uses a cluster as a underlying system to help stable transmission services. 2D, the proposed enclosure uses a cluster based verbal cooperative exchange to effectively guide the package delivery ratio with multi hop power saving transmission. 0.33, we do not forget reasonable methods mainly based on cellular ad hoc nodes with sensing features and constant sensor nodes in the sensor field along with conventional research for the introduction of constant network sensors. Fourth, we have theoretical analysis with blackouts opportunities for proposed cooperative transmissions. Overall performance evaluation is run through simulation and evaluation. Sweeti Kumari | Dr. Ranjan Kumar Singh "Wireless Sensor Network Based Clustering Architecture for Cooperative Communication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43670.pdf Paper URL: https://www.ijtsrd.comengineering/electronics-and-communication-engineering/43670/wireless-sensor-network-based-clustering-architecture-for-cooperative-communication/sweeti-kumari
Wireless Sensor Networks are highly distributed self-organized systems. WSN have been deployed in various fields. Now a day, Topology issues have received more and more attentions in Wireless Sensor Networks (WSN). While WSN applications are normally optimized by the given underlying network topology, another trend is to optimize WSN by means of topology control. In this area, a number of approaches have been invested, like network connectivity based topology control, cooperating schemes, topology directed routing, sensor coverage based topology control. Most of the schemes have proven to be able to provide a better network monitoring and communication performance with prolonged system lifetime. In this survey paper, I provide a full view of the studies in this area.
AN EFFICIENT INTRUSION DETECTION SYSTEM WITH CUSTOM FEATURES USING FPA-GRADIE...IJCNCJournal
An efficient Intrusion Detection System has to be given high priority while connecting systems with a network to prevent the system before an attack happens. It is a big challenge to the network security group to prevent the system from a variable types of new attacks as technology is growing in parallel. In this paper, an efficient model to detect Intrusion is proposed to predict attacks with high accuracy and less false-negative rate by deriving custom features UNSW-CF by using the benchmark intrusion dataset UNSW-NB15. To reduce the learning complexity, Custom Features are derived and then Significant Features are constructed by applying meta-heuristic FPA (Flower Pollination algorithm) and MRMR (Minimal Redundancy and Maximum Redundancy) which reduces learning time and also increases prediction accuracy. ENC (ElasicNet Classifier), KRRC (Kernel Ridge Regression Classifier), IGBC (Improved Gradient Boosting Classifier) is employed to classify the attacks in the datasets UNSW-CF, UNSW and recorded that UNSW-CF with derived custom features using IGBC integrated with FPA provided high accuracy of 97.38% and a low error rate of 2.16%. Also, the sensitivity and specificity rate for IGB attains a high rate of 97.32% and 97.50% respectively.
ON THE PERFORMANCE OF INTRUSION DETECTION SYSTEMS WITH HIDDEN MULTILAYER NEUR...IJCNCJournal
Deep learning applications, especially multilayer neural network models, result in network intrusion detection with high accuracy. This study proposes a model that combines a multilayer neural network with Dense Sparse Dense (DSD) multi-stage training to simultaneously improve the criteria related to the performance of intrusion detection systems on a comprehensive dataset UNSW-NB15. We conduct experiments on many neural network models such as Recurrent Neural Network (RNN), Long-Short Term Memory (LSTM), Gated Recurrent Unit (GRU), etc. to evaluate the combined efficiency with each model through many criteria such as accuracy, detection rate, false alarm rate, precision, and F1-Score.
AN OPTIMIZED WEIGHT BASED CLUSTERING ALGORITHM IN HETEROGENEOUS WIRELESS SENS...cscpconf
The last few years have seen an increased interest in the potential use of wireless sensor networks (WSNs) in various fields like disastermanagementbattle field surveillance, and border security surveillance. In such applications, a large number of sensor nodes are deployed, which are often unattended and work autonomously. The process of dividing the network into interconnected substructures is called clustering and the interconnected substructures are called clusters. The cluster head (CH) of each cluster act as a coordinator within the substructure. Each CH acts as a temporary base station within its zone or cluster. It also communicates with other CHs. Clustering is a key technique used to extend the lifetime of a sensor network by reducing energy consumption. It can also increase network scalability. Researchers in all fields of wireless sensor network believe that nodes are homogeneous, but
some nodes may be of different characteristics to prolong the lifetime of a WSN and its reliability. We have proposed an algorithm for better cluster head selection based on weights for different parameter that influence on energy consumption which includes distance from base station as a new parameter to reduce number of transmissions and reduce energy consumption by sensor nodes. Finally proposed algorithm compared with the WCA, IWCA algorithm in terms of number of clusters and energy consumption.
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.
IGeekS Technologies is a company located in Bangalore, India. We have being recognized as a quality provider of hardware and software solutions for the student’s in order carry out their academic Projects. We offer academic projects at various academic levels ranging from graduates to masters (Diploma, BCA, BE, M. Tech, MCA, M. Sc (CS/IT)). As a part of the development training, we offer Projects in Embedded Systems & Software to the Engineering College students in all major disciplines.
ADAPTIVE SENSOR SENSING RANGE TO MAXIMISE LIFETIME OF WIRELESS SENSOR NETWORK IJCNCJournal
Wireless Sensor Network (WSN) is commonly used to collect information from a remote area and one of the most important challenges associated with WSN is to monitor all targets in a given area while maximizing network lifetime. In wireless communication, energy consumption is proportional to the breadth of sensing range and path loss exponent. Hence, the energy consumption of communication can be minimized by varying the sensing range and decreasing the number of messages being sent. Sensing energy can be optimized by reducing the repeated coverage target. In this paper, an Adaptive Sensor Sensing Range (ASSR) technique is proposed to maximize the WSN Lifetime. This work considers a sensor network with an adaptive sensing range that are randomly deployed in the monitoring area. The sensor is adaptive in nature and can be modified in order to save power while achieving maximum time of monitoring to increase the lifetime of WSN network. The objective of ASSR is to find the best sensing range for each sensor to cover all targets in the network, which yields maximize the time of monitoring of all targets and eliminating double sensing for the same target. Experiments were conducted using an NS3 simulator to verify our proposed technique. Results show that ASSR is capable to improve the network lifetime by 20% as compared to other recent techniques in the case of a small network while achieving an 8% improvement for the case of a large networks.
Reliable and Efficient Data Acquisition in Wireless Sensor NetworkIJMTST Journal
The sensors in the WSN sense the surrounding, collects the data and transfers the data to the sink node. It
has been observed that the sensor nodes are deactivated or damaged when exposed to certain radiations or
due to energy problems. This damage leads to the temporary isolation of the nodes from the network which
results in the formation of the holes. These holes are dynamic in nature and can grow and shrink depending
upon the factors causing the damage to the sensor nodes. So a solution has been presented in the base paper
where the dual mode i.e. Radio frequency and the Acoustic mode are considered so that the data can be
transferred easily. Based on this a survey has been done where several factors are studied so that the
performance of the system can be increased.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
Sensing and Sharing Schemes for Spectral Efficiency of Cognitive Radios IJECEIAES
Increase in data traffic, number of users and their requirements laid to a necessity of more bandwidth. Cognitive radio is one of the emerging technology which addresses the spectrum scarcity issue. In this work we study the advantage of having collaboration between cognitive enabled small cell network and primary macrocell. Different from the existing works at spectrum sensing stage we are applying enhanced spectrum sensing to avoid probability of false alarms and missed detections which has impact on spec tral efficiency. Later power control optimization for secondary users known as Hybrid spectrum sharing is used for further improvement of spectral efficiency. Furthermore, the failed packets of Primary users are taken care by high ranked relays which in turn decreases the average Primary user packet delay by 20% when compared between assisted Secondary user method and non-assisted Secondary user method.
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.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Optical network is an emerging technology for data communication
inworldwide. The information is transmitted from the source to destination
through the fiber optics. All optical network (AON) provides good
transmission transparency, good expandability, large bandwidth, lower bit
error rate (BER), and high processing speed. Link failure and node failure
haveconsistently occurred in the traditional methods. In order to overcome
the above mentioned issues, this paper proposes a robust software defined
switching enabled fault localization framework (SDSFLF) to monitor the
node and link failure in an AON. In this work, a novel faulty node
localization (FNL) algorithm is exploited to locate the faulty node. Then, the
software defined faulty link detection (SDFLD) algorithm that addresses the
problem of link failure. The failures are localized in multi traffic stream
(MTS) and multi agent system (MAS). Thus, the throughput is improved in
SDSFLF compared than other existing methods like traditional routing and
wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and
biggest source-destination node degree (BND) ordering. The performance of
the proposed algorithm is evaluated in terms of network load, wavelength
utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF
assures that high performance is achieved than other traditional techniques.
Mobile Agents based Energy Efficient Routing for Wireless Sensor NetworksEswar Publications
Energy Efficiency and prolonged network lifetime are few of the major concern areas. Energy consumption rated of sensor nodes can be reduced in various ways. Data aggregation, result sharing and filtration of aggregated data among sensor nodes deployed in the unattended regions have been few of the most researched areas in the field of wireless sensor networks. While data aggregation is concerned with minimizing the information transfer from source to sink to reduce network traffic and removing congestion in network, result sharing focuses on sharing of information among agents pertinent to the tasks at hand and filtration of aggregated data so as to remove redundant information. There exist various algorithms for data aggregation and filtration using different mobile agents. In this proposed work same mobile agent is used to perform both tasks data aggregation and data filtration. This approach advocates the sharing of resources and reducing the energy consumption level of sensor nodes.
A Novel Weighted Clustering Based Approach for Improving the Wireless Sensor ...IJERA Editor
Great lifetime and reliability is the key aim of Wireless Sensor Network (WSN) design. As for prolonging
lifetime of this type of network, energy is the most important resource; all recent researches are focused on more
and more energy efficient techniques. Proposed work is Weighted Clustering Approach based on Weighted
Cluster Head Selection, which is highly energy efficient and reliable in mobile network scenario. Weight
calculation using different attributes of the nodes like SNR (Signal to Noise Ratio), Remaining Energy, Node
Degree, Mobility, and Buffer Length gives efficient Cluster Head (CH) on regular interval of time. CH rotation
helps in optimum utilization of energy available with all nodes; results in prolonged network lifetime.
Implementation is done using the NS2 network simulator and performance evaluation is carried out in terms of
PDR (Packet Delivery Ratio), End to End Delay, Throughput, and Energy Consumption. Demonstration of the
obtained results shows that proposed work is adaptable for improving the performance. In order to justify the
solution, the performance of proposed technique is compared with the performance of traditional approach. The
performance of proposed technique is found optimum as compared to the traditional techniques.
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.
IGeekS Technologies is a company located in Bangalore, India. We have being recognized as a quality provider of hardware and software solutions for the student’s in order carry out their academic Projects. We offer academic projects at various academic levels ranging from graduates to masters (Diploma, BCA, BE, M. Tech, MCA, M. Sc (CS/IT)). As a part of the development training, we offer Projects in Embedded Systems & Software to the Engineering College students in all major disciplines.
ADAPTIVE SENSOR SENSING RANGE TO MAXIMISE LIFETIME OF WIRELESS SENSOR NETWORK IJCNCJournal
Wireless Sensor Network (WSN) is commonly used to collect information from a remote area and one of the most important challenges associated with WSN is to monitor all targets in a given area while maximizing network lifetime. In wireless communication, energy consumption is proportional to the breadth of sensing range and path loss exponent. Hence, the energy consumption of communication can be minimized by varying the sensing range and decreasing the number of messages being sent. Sensing energy can be optimized by reducing the repeated coverage target. In this paper, an Adaptive Sensor Sensing Range (ASSR) technique is proposed to maximize the WSN Lifetime. This work considers a sensor network with an adaptive sensing range that are randomly deployed in the monitoring area. The sensor is adaptive in nature and can be modified in order to save power while achieving maximum time of monitoring to increase the lifetime of WSN network. The objective of ASSR is to find the best sensing range for each sensor to cover all targets in the network, which yields maximize the time of monitoring of all targets and eliminating double sensing for the same target. Experiments were conducted using an NS3 simulator to verify our proposed technique. Results show that ASSR is capable to improve the network lifetime by 20% as compared to other recent techniques in the case of a small network while achieving an 8% improvement for the case of a large networks.
Reliable and Efficient Data Acquisition in Wireless Sensor NetworkIJMTST Journal
The sensors in the WSN sense the surrounding, collects the data and transfers the data to the sink node. It
has been observed that the sensor nodes are deactivated or damaged when exposed to certain radiations or
due to energy problems. This damage leads to the temporary isolation of the nodes from the network which
results in the formation of the holes. These holes are dynamic in nature and can grow and shrink depending
upon the factors causing the damage to the sensor nodes. So a solution has been presented in the base paper
where the dual mode i.e. Radio frequency and the Acoustic mode are considered so that the data can be
transferred easily. Based on this a survey has been done where several factors are studied so that the
performance of the system can be increased.
Energy Conservation in Wireless Sensor Networks Using Cluster-Based ApproachIJRES Journal
In a wireless networking environment, the network is comprised of sensor nodes and backbones are subsets of sensors or actuators that suffice for performing basic data communication operations. They are applied for energy efficient broadcasting. In a broadcasting (also known as data dissemination) task, a message is to be sent from one node, which could be a sink or an actuator, to all the sensors or all the actuators in the network. The goal is to minimize the number of rebroadcasts while attempting to deliver messages to all sensors or actuators. Neighbor detection and route discovery algorithms that consider a realistic physical layer are described. An adaptive broadcasting protocol without parameters suitable for delay tolerant networks is further discussed. In existing solutions for minimal energy broadcasting problem, nodes can adjust their transmission powers. Wireless Sensor Networks (WSNs) are sets of many sensors that gather data and collaborate together. So, the procedures of broadcast or multicast are more important than traditional point-to-point communication in computer network. This paper focuses on broadcasting in structured WSNs. In such a kind, the procedure of network communications is easier than in unstructured WSNs. Thus, it will make an overview of Multi Point Relay (MPR) to show its weakness. Then define a cluster-based architecture for WSNs which is constructed using MPR. Next, provide a new broadcast algorithm based on the previous cluster architecture called 3B (Backbone Based Broadcasting). By the end, an illustration of 3B shows that it minimizes the energy consumption for accomplishing broadcast compared to MPR.
Sensing and Sharing Schemes for Spectral Efficiency of Cognitive Radios IJECEIAES
Increase in data traffic, number of users and their requirements laid to a necessity of more bandwidth. Cognitive radio is one of the emerging technology which addresses the spectrum scarcity issue. In this work we study the advantage of having collaboration between cognitive enabled small cell network and primary macrocell. Different from the existing works at spectrum sensing stage we are applying enhanced spectrum sensing to avoid probability of false alarms and missed detections which has impact on spec tral efficiency. Later power control optimization for secondary users known as Hybrid spectrum sharing is used for further improvement of spectral efficiency. Furthermore, the failed packets of Primary users are taken care by high ranked relays which in turn decreases the average Primary user packet delay by 20% when compared between assisted Secondary user method and non-assisted Secondary user method.
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.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Optical network is an emerging technology for data communication
inworldwide. The information is transmitted from the source to destination
through the fiber optics. All optical network (AON) provides good
transmission transparency, good expandability, large bandwidth, lower bit
error rate (BER), and high processing speed. Link failure and node failure
haveconsistently occurred in the traditional methods. In order to overcome
the above mentioned issues, this paper proposes a robust software defined
switching enabled fault localization framework (SDSFLF) to monitor the
node and link failure in an AON. In this work, a novel faulty node
localization (FNL) algorithm is exploited to locate the faulty node. Then, the
software defined faulty link detection (SDFLD) algorithm that addresses the
problem of link failure. The failures are localized in multi traffic stream
(MTS) and multi agent system (MAS). Thus, the throughput is improved in
SDSFLF compared than other existing methods like traditional routing and
wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and
biggest source-destination node degree (BND) ordering. The performance of
the proposed algorithm is evaluated in terms of network load, wavelength
utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF
assures that high performance is achieved than other traditional techniques.
Mobile Agents based Energy Efficient Routing for Wireless Sensor NetworksEswar Publications
Energy Efficiency and prolonged network lifetime are few of the major concern areas. Energy consumption rated of sensor nodes can be reduced in various ways. Data aggregation, result sharing and filtration of aggregated data among sensor nodes deployed in the unattended regions have been few of the most researched areas in the field of wireless sensor networks. While data aggregation is concerned with minimizing the information transfer from source to sink to reduce network traffic and removing congestion in network, result sharing focuses on sharing of information among agents pertinent to the tasks at hand and filtration of aggregated data so as to remove redundant information. There exist various algorithms for data aggregation and filtration using different mobile agents. In this proposed work same mobile agent is used to perform both tasks data aggregation and data filtration. This approach advocates the sharing of resources and reducing the energy consumption level of sensor nodes.
A Novel Weighted Clustering Based Approach for Improving the Wireless Sensor ...IJERA Editor
Great lifetime and reliability is the key aim of Wireless Sensor Network (WSN) design. As for prolonging
lifetime of this type of network, energy is the most important resource; all recent researches are focused on more
and more energy efficient techniques. Proposed work is Weighted Clustering Approach based on Weighted
Cluster Head Selection, which is highly energy efficient and reliable in mobile network scenario. Weight
calculation using different attributes of the nodes like SNR (Signal to Noise Ratio), Remaining Energy, Node
Degree, Mobility, and Buffer Length gives efficient Cluster Head (CH) on regular interval of time. CH rotation
helps in optimum utilization of energy available with all nodes; results in prolonged network lifetime.
Implementation is done using the NS2 network simulator and performance evaluation is carried out in terms of
PDR (Packet Delivery Ratio), End to End Delay, Throughput, and Energy Consumption. Demonstration of the
obtained results shows that proposed work is adaptable for improving the performance. In order to justify the
solution, the performance of proposed technique is compared with the performance of traditional approach. The
performance of proposed technique is found optimum as compared to the traditional techniques.
Energy-efficient data-aggregation for optimizing quality of service using mo...IJECEIAES
Quality of service (QoS) is essential for carrying out data transmission using resource-constrained sensor nodes in wireless sensor network (WSN). The introduction of mobile agent-based data aggregation is reported to offer energy efficiency; however, it has limitations, especially using a single mobile agent, where QoS optimization is not feasible. A review of existing studies showcases some dedicated attempts to use a mobile agent-based approach and address QoS enhancements. However, they were never combined studied. Therefore, this paper introduces a unique concept of retaining maximum QoS performance during data aggregation using a single mobile agent. The model introduces a unique communication framework, transmission provisioning using exceptional routine management, and simplified energy modeling. The proposed model has aimed for a lower delay and faster data aggregation speed with lower consumption of transmittance energy. The implementation and assessment of the model are carried out considering the challenging environment of WSN with multiple scales of data priority. The proposed model also contributes to evolving out with simplified communication vectors in a highly decentralized method. MATLAB's simulation outcome shows that the proposed system offers better delay performance, optimal energy management, and faster response time than existing schemes.
Concepts and evolution of research in the field of wireless sensor networksIJCNCJournal
The field of Wireless Sensor Networks (WSNs) is experiencing a resurgence of interest and a continuous evolution in the scientific and industrial community. The use of this particular type of ad hoc network is becoming increasingly important in many contexts, regardless of geographical position and so, according to a set of possible application. WSNs offer interesting low cost and easily deployable solutions to perform a remote real time monitoring, target tracking and recognition of physical phenomenon. The uses of these sensors organized into a network continue to reveal a set of research questions according to particularities target applications. Despite difficulties introduced by sensor resources constraints, research contributions in this field are growing day by day. In this paper, we present a comprehensive review of most recent literature of WSNs and outline open research issues in this field.
Hybrid Red Deer Algorithm with Physical Unclonable Function for Security Enha...IJCNCJournal
In this modern era, Wireless Sensor Network (WSNs) have turned out to be a more attractive option, because of the advancements in communication. If the network is insecure, an attacker can intercept messages and break the sensor nodes’ security; as well as duplicate the authentication codes to launch a variety of attacks. As a result, Physical Unclonable Functions (PUFs) with unpredictable features are encouraged to be used in the development of lightweight cryptographic protocols. This work introduced the Red Deer Algorithm (RDA) with PUF as a new mutual authentication system. When a sensor receives a challenge from the gateway, the inbuilt PUF generates a key and distributes it to the sensor by providing complete resilience against malicious attacks. PUF is resistant to node acquisition, cloning, and malicious attacks, as well as node physical security flaws. Key distribution is moving too quickly and the adversary won’t be able to conduct a harmful attack in time. Furthermore, PUF’s unclonability and unexpected qualities provide key uniqueness and two-way authentication for improving the security. When compared to existing Tunicate Swarm Grey Wolf optimization (TSGWO) and PUF-Based Mutual-Authenticated Key Distribution (PUF-MAKD), the proposed RDA-PUF demonstrated better results. The simulation results are obtained in terms of minimizing energy consumption as 0.7 J, end-to-end delay as 7 sec, packet delivery ratio of 97%, increasing network lifetime to 1330 sec, and improving secure connectivity to 1.211.
Hybrid Red Deer Algorithm with Physical Unclonable Function for Security Enha...IJCNCJournal
In this modern era, Wireless Sensor Network (WSNs) have turned out to be a more attractive option, because of the advancements in communication. If the network is insecure, an attacker can intercept messages and break the sensor nodes’ security; as well as duplicate the authentication codes to launch a variety of attacks. As a result, Physical Unclonable Functions (PUFs) with unpredictable features are encouraged to be used in the development of lightweight cryptographic protocols. This work introduced the Red Deer Algorithm (RDA) with PUF as a new mutual authentication system. When a sensor receives a challenge from the gateway, the inbuilt PUF generates a key and distributes it to the sensor by providing complete resilience against malicious attacks. PUF is resistant to node acquisition, cloning, and malicious attacks, as well as node physical security flaws. Key distribution is moving too quickly and the adversary won’t be able to conduct a harmful attack in time. Furthermore, PUF’s unclonability and unexpected qualities provide key uniqueness and two-way authentication for improving the security. When compared to existing Tunicate Swarm Grey Wolf optimization (TSGWO) and PUF-Based Mutual-Authenticated Key Distribution (PUF-MAKD), the proposed RDA-PUF demonstrated better results. The simulation results are obtained in terms of minimizing energy consumption as 0.7 J, end-to-end delay as 7 sec, packet delivery ratio of 97%, increasing network lifetime to 1330 sec, and improving secure connectivity to 1.211.
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.
Optimal Coverage Path Planningin a Wireless Sensor Network for Intelligent Tr...IJCNCJournal
With the enhancement of the intelligent and communication technology, an intelligent transportation plays a vital role to facilitate an essential service to many people, allowing them to travel quickly and conveniently from place to place. Wireless sensor networks (WSNs) are well-known for their ability to detect physical significant barriers due to their diverse movement, self-organizing capabilities, and the integration of this mobile node on the intelligent transportation system to gather data in WSN contexts is becoming more and more popular as these vehicles proliferate. Although these mobile devices might enhance network performance, however it is difficult to design a suitable transportation path with the limited energy resources with network connectivity. To solve this problem, we have proposed a novel itinerary planning schema data gatherer (IPS-DG) model. Furthermore, we use the path planning module (PPM) which finds the transportation path to travel the shortest distance. We have compared our results under different aspect such as life span, energy consumption, and path length with Low Energy Adaptive Clustering Hierarchy (LEACH), Multi-Hop Weighted Revenue (MWR), Single-Hop Data Gathering Procedure (SHDGP). Our model outperforms in terms of energy usage, shortest path, and longest life span of with LEACH, MWR, SHDGP routing protocols.
Optimal Coverage Path Planning in a Wireless Sensor Network for Intelligent T...IJCNCJournal
With the enhancement of the intelligent and communication technology, an intelligent transportation plays a vital role to facilitate an essential service to many people, allowing them to travel quickly and conveniently from place to place. Wireless sensor networks (WSNs) are well-known for their ability to detect physical significant barriers due to their diverse movement, self-organizing capabilities, and the integration of this mobile node on the intelligent transportation system to gather data in WSN contexts is becoming more and more popular as these vehicles proliferate. Although these mobile devices might enhance network performance, however it is difficult to design a suitable transportation path with the limited energy resources with network connectivity. To solve this problem, we have proposed a novel itinerary planning schema data gatherer (IPS-DG) model. Furthermore, we use the path planning module (PPM) which finds the transportation path to travel the shortest distance. We have compared our results under different aspect such as life span, energy consumption, and path length with Low Energy Adaptive Clustering Hierarchy (LEACH), Multi-Hop Weighted Revenue (MWR), Single-Hop Data Gathering Procedure (SHDGP). Our model outperforms in terms of energy usage, shortest path, and longest life span of with LEACH, MWR, SHDGP routing protocols.
Characterization of directed diffusion protocol in wireless sensor networkijwmn
Wireless sensor network (WSN) has enormous applications in many places for monitoring the environments
of importance. Sensor nodes are capable of sensing, computing, and communicating. These sensor nodes
are energy constraint and operated by batteries. Since energy consumption is an important issue of WSN,
there have been many energy-efficient protocols proposed for the WSN. Directed diffusion (DD) is a datacentric
protocol that focuses on the energy efficiency of the networks. Since the first proposal of DD
protocol by Deborah, there have been various versions of DD protocols proposed by many scientists across
the globe. These upgraded versions of DD protocols add on various features to the original DD protocol
such as energy, scalability, network lifetime, security, reliability, and mobility. In this paper, we discuss
and classify various characteristics of themost populardirected diffusion protocols that have been proposed
over couple of years.
An Efficient Approach for Data Gathering and Sharing with Inter Node Communi...cscpconf
In today’s era Wireless sensor networks (WSNs) have emerged as a solution for a wide range of
applications. Most of the traditional WSN architectures consist of static nodes which are densely deployed
over a sensing area. Recently, several WSN architectures based on mobile elements (MEs) have been
proposed. Most of them exploit mobility to address the problem of data collection in WSNs. The common
drawback among them is to data sharing between interconnected nodes. In this paper we propose an
Efficient Approach for Data Gathering and Sharing with Inter Node Communication in Mobile-Sink. Our
algorithm is divided into seven parts: Registration Phase, Authentication Phase, Request and Reply Phase,
Setup Phase, Setup Phase (NN), Data Gathering, and Forwarding to Sink. Our approach provides an
efficient way to handle data in between the intercommunication nodes. By the above approach we can
access the data from the node which is not in the list, by sharing the data from the node which is
approachable to the desired node. For accessing and sharing we need some security so that the data can
be shared between authenticated nodes. For this we use two way security approach one for the accessing
node and other for the sharing.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
2. 118 Computer Science & Information Technology (CS & IT)
monitored field to other networks (e.g., the internet). In WSN, sensors have limited resources,
typically the energy resources, and the calculation capabilities, as well as the storage capacity.
Therefore, most studies and researches on WSNs have focused on the optimization of resources
in order to enhance the performances and meet the quality of service (QoS) requirements.
Determining the sensor field topologies is a key challenge in sensor resource management.
Consequently, WSN performance is powerfully influenced by the deployment topology of sensor
nodes, which affect QoS metrics, such as energy consumption, sensor lifetime, and sensing
coverage equally [1].
In the literature, the deployment topology can be classified according to; the placement
methodology that can be either random placement or grid-based placement (deterministic
placement), the optimization of performance metrics such as connectivity, sensing coverage,
energy consumption and lifetime, and the roles the deployed node, which can be regular, relay,
cluster-head, or base-station, plays [2]. However, the placement techniques can be further
categorized into static and dynamic whether the optimization is performed at the time of
deployment or whiles the network is working, respectively. The choice of the deployment scheme
depends on many properties [2]. Therefore, many studies considered that for some cases random
placement becomes the only option due to the environment characteristics [3] [4] and deployment
cost, and time. Figure 1 shows the different categories of node placement strategies.
Our major focus in this paper is on how to choose the optimal nodes deployment that can achieve
maximal coverage of the monitored area [5]. Thus, optimal nodes placement issue is a problem
that has been proven NP-hard for most formulations of sensor deployment [6].
The coverage metric is a decisive metric that can be considered as a measure of permanence and
QoS for WSN. Coverage in a WSN is to ensure that the Region of Interest (RoI) is monitored
with high reliability in order to have the necessary information on the supervised phenomenon
[7]. Coverage issues can be commonly classified into two types: target coverage problem and
area coverage problem. The former ensures the monitoring of only certain specific points which
have fixed positions in the area of interest, while the latter is concerned with the supervision of
the whole deployment area. Target coverage can be categorized as Q-coverage or simple
coverage. For simple coverage, each target should be monitored by at least one sensor node. For
Q-coverage, each target has to be monitored by at least Q different working sensor nodes.
Figure 1. Sensor node placement methodologies
The connectivity metric is as important as coverage in wireless sensor networks. A WSN is
defined as connected if, and only if, there exists at least one route between each pair of nodes.
Thus, connectivity depends on the existence of paths and can therefore be directly affected by
3. Computer Science & Information Technology (CS & IT) 119
changes of topology. For this reason an optimal deployment strategy have to maximize coverage
with respect to the connectivity constraint.
Nature constantly inspires research in the field of optimization. While genetics, ants and particle
swarm algorithms are famous examples, other nature inspired optimization algorithms emerge
regularly. Flower Pollination Algorithm (FPA) is novel global optimization algorithm inspired
from pollination process of flowers. FPA is simple and very powerful; in fact, it can outperform
both genetic algorithm (GA) and particle swarm optimization (PSO) according to [8].
To find the best nodes deployment that would achieve maximal coverage of the targeted area
without affecting network connectivity, a new approach based on FPA is introduced to enhance
coverage in a wireless sensor network. We considered a centralized topology and an area
coverage problem with random sensor deployment. Here, different scenario was tested. The
proposed approach was able to maximize the total coverage area for the considered scenarios.
The remainder of this paper is organized as follows. Section 2 gives a literature survey about
different deployment algorithms. The problem formulation is presented in section 3. Section 4
specifies the proposed FPA based deployment approach. In section 5, the simulation results and
discussion are given. Finally, section 6 concludes the paper.
2. LITERATURE SURVEY
Over the last years, researchers attempted to tackle the nodes deployment problem in WSN
through various optimization processes both by mathematical programming and through nature
inspired techniques. This problem was sometimes modelled as a one single objective problem, in
special cases deal with several objectives through well selected weights.
Yu et al. proposed a node placement algorithm for mobile sensor networks based on the strength
of van der Waals in order to improve the total coverage area. In fact, the proximity relationship
of nodes is defined by the Delaunay triangulation method, the frictional force is inserted into the
equation of force, the force calculated generate an acceleration in the movement of nodes. To
evaluate whether the nodes are uniformly distributed over the deployment field an evaluation
metric named pair correlation function was introduced in [9]. The Genetic Algorithm (GA) was
introduced as a solution for coverage holes problem in WSN [10]. This approach found the
optimal positions and the number of mobile nodes that have to be added to the initial deployment
schema. Simulation results prove that this algorithm has optimized network coverage in terms of
overall coverage ratio and additional number of mobile nodes. Sengupta et al. addressed the
problem of achieving an optimal trade-off between coverage, energy consumption, and lifetime in
WSN by using the multi-objective evolutionary algorithm (MOEA). They developed an enhanced
version of Multi-objective evolutionary algorithm based on differential evolution (MOEA/D-DE)
known as MOEA/DFD which includes the fuzzy dominance [11]. Sakamoto et al. proposed a
simulation approach founded on Particle Swarm Optimization (PSO). They focused on the size of
giant component and number of covered mesh clients (NCMC), which are important objective
functions to optimize Wireless Mesh Networks (WMNs) [12]. In their work, the authors of [13]
proposed a modified version of the original artificial bee colony (ABC); in fact, they change the
updating equation of onlooker bee and scout bee [14]. Indeed, some new parameters, such as
forgetting and neighbors factor for accelerating the convergence speed and probability of mutant
for maximizing the coverage rate were introduced [15]. Comparing their approach with the
deployment topology based on the traditional ABC and PSO algorithm, they found that the
4. 120 Computer Science & Information Technology (CS & IT)
former achieved better performance in terms of coverage and speed of convergence with less
moving distance sensor.
3. PROBLEM FORMULATION
The deployment of sensor nodes in WSN is to find the placement nodes topology or find the
coordinates of the sensor nodes in the two-dimensional plane. The most important concerns for
WSN are how improving the performances and optimizing the resources. Thus, an optimal
placement strategy ought to be considered to achieve the required goal. Here our objective is to
find an optimal placement schema that maximizes the coverage area without losing network
connectivity. For this, the following different mathematical models are described.
3.1. Preliminary
Sensor nodes in WSN are characterized by their positions in the 2D plane (x, y), sensing radius
Rs, and communication radius Rc. Given a multi-hop WSN, where all nodes collaborate in order
to ensure cooperative communication. Such network, can be defined as a linked graph, G = {V,
E}, where V is the set of vertices representing sensors and E is the set of edges representing links
between the sensors. Let u ϵ V and v ϵ V, (u, v) belongs to E if, and only if, u can send a message
directly to v (we say that v is neighbor of u). We assume that Rc is identical for all nodes. Let d(u,
v) be the distance between the nodes u and v, the set E can be defined as follows:
( ){ }2
, ; d(u,v) RCE u v V= ∈ ≤
The network coverage is defined by the sensing radius of the sensor nodes, whereas the network
connectivity is specified by the communication radius of the nodes.
3.2. Connectivity
Definition 1 (Node Degree). Given an undirected graph G. The degree Deg(u), of a vertex u ϵ V
is specified as the number of a vertex u ϵ V is specified as the number of neighbors of u [16].
Definition 2 (k-Node Connectivity). A graph is considered to be connected if for every pair of
nodes, there exists a single hop or a multi-hop path connecting them; otherwise the graph is called
disconnected. A graph is considered to be Q-connected if for any pair of nodes there are at least Q
reciprocally separate paths connecting them [16].
3.3. Binary Sensing Model
The coverage in WSN defined as the total area covered by a set of sensor nodes deployed in the
region of interest (ROI). This region is considered as m × n grids, each grid point size was equal
to 1 and denoted as G(x, y) (Figure. 2).
5. Computer Science & Information Technology (CS & IT) 121
Figure 2. Sensor coverage in sensing field
Generally, the zone covered by a sensor node is a disk with radius equals to sensing radius of the
sensor. The binary sensing model considered that each grid point within the sensing radius of a
node can be considered as covered with probability equal to "1" and the point out of the sensing
range was set as "0" since it cannot be covered (Eq1). Thus, the coverage of the whole area is
proportional to the grid points that can be covered by at least one sensor Si(xi, yi) [17].
( ) ( )
2 2
1,
0,
i i sif x x y y R
P
otherwise
− − − ≤
=
4. THE PROPOSED APPROACH
This work interested by the node sensors deployment problem in WSN. In fact, we deal with area
coverage problem for random placement topology with predefined number of sensors. Here, the
main purpose was to improve the quality of coverage without affecting network connectivity
constraint. Evidently, to supply connected coverage to a zone, the set of disks used much cover
all points in that region and the connectivity graph of all the Rc-disks must form a single
connected component in a graph theoretic sense. The proposed approach, named Flower
Pollination Coverage Optimization approach (FPCOA), was a centralized approach based on
FPA, aimed to deploy all the sensor nodes in their positions carefully to form a WSN with
maximal coverage area.
4.1. Fitness function
The binary model was considered as sensing model (Section 2.3). The proposed approach is a
mono-objective deployment approach designed to optimize one objective function, namely the
ratio of total coverage target area. It is given by:
( )
1
( , , ) 1 1 ( , ,
N
i
i
P x y S P x y S
=
= − −∏
6. 122 Computer Science & Information Technology (CS & IT)
With N is the number of sensor nodes and P(x, y, Si) is the probability that a grid point G(x, y) is
covered by a sensor Si. So, the total coverage area is defined as:
1 1
( , , )
m n
x y
TotCovArea P x y S
= =
= ∑∑
And the ratio of total coverage area is given by:
TotCovArea
Total Coverage ratio
TotalGridArea
=
4.2. Constraints
The network connectivity is taken as a constraint in this optimization problem. Therefore one
path, at least, must exist from the sensor node to the sink node, to guarantee connectivity
4.3. Flower Pollination Coverage Optimization Algorithm (FPCOA)
The proposed approach composed of two main steps. The first step was the creation of the initial
population (Algorithm 1). The second step was the performing of the optimization process based
on FPA (Algorithm 2).
Initial Population. To create the initial population we considered that each individual was
represented by a vector of all sensor nodes position (x, y) in RoI. The WSN parameters are
described in Table 1.
Table 1. Parameters of WSN.
7. Computer Science & Information Technology (CS & IT) 123
To create initial population, we began by generating the position of the sink node at the centre of
RoI (i.e., at xm/2 and ym/2) for each individual. Then, we deployed the remaining sensors by
taking into consideration the connectivity constraint. Actually, network connectivity is assumed
to be full if the distance between two sensors is less than the communication radius (Rc) of the
sensor. The distance is defined as the Euclidean distance between two sensors. In addition, to
insure a sufficient distribution in RoI, we controlled the number of neighbors of each deployed
node that should be less than a predefined number Ne (see Algorithm1).
Table 2. Pseudo code of Initial Population Creation.
Flower Pollination Algorithm (FPA). metaheuristics are generic algorithms, often inspired
from nature, designed to solve challenging optimization problems [17] [18]. Here, we considered
one of the most recent metaheuristic algorithms named Flower Pollination Algorithm (FPA),
developed by Xin-She Yang in the year 2012 [8] for the global optimization problems. FPA
inspired from the flower pollination process of flowering plants. In nature, flowers pollination
process resulting from the transfer of pollen, typically, by pollinators such as insects, birds, bats
and other animals. In fact, pollination process can be commonly classified into two types: self-
pollination and cross-pollination. The former can occur by the pollen of the same flower. The
8. 124 Computer Science & Information Technology (CS & IT)
latter can take place by pollen of a flower of a different plant [20] [21]. FPA has the following
four rules:
1. Cross-pollination is considered as global pollination process with pollen carrying; pollinators
performing Lévy flights.
2. Self-pollination is considered as local pollination.
3. Flower constancy can be defined as the reproduction probability is proportional to the
similarity of the two flowers involved.
4. Global and local pollination is controlled by a switch probability p ϵ [0, 1].
Table 3. Pseudo Code of Flower Pollination Coverage Optimization.
9. Computer Science & Information Technology (CS & IT) 125
Here each flower was represented by a vector of all sensor nodes position (x, y) in RoI, fCurr1,
fCurr2, …,fCurrN was the flower population at iteration t, fNext1, fNext2, …,fNextN was the flower
population at iteration t +1, Nbflower was the total number of flower and the Current-Global -
Flower is the best solution found among all solutions at the current generation or iteration t. To
imitate the movement of pollinator [22], FPA uses Lévy flight. That is, we draw L > 0 from a
Lévy distribution:
01
( )sin( )
12~ (s s 0)L
s λ
πλ
λ λ
π +
Γ
? ?
The pseudo-code of FPA is presented in Table3.
5. SIMULATION AND RESULTS
To validate the proposed approach, some simulations were undertaken. We used a binary sensing
model the nodes are initially randomly distributed. The network is homogeneous, i.e., all sensors
have the same deployment parameters such as the sensing and communication radius.
Simulations were carried out using MATLAB R2016a. The algorithm was run a maximum
number of iterations of 3000. The average of 10 runs was recorded. For the simulations, we
considered a square area divided into a number of squares of 1 m2 each. The center of each of
these squares is taken as the demand point to detect by at least one sensor node. In this section,
the performance of the proposed FPCOA is evaluated with regard to the total coverage ratio.
Moreover, the obtained results were compared with those obtained with two metaheuristics
algorithms, namely, PSO and GA and, finally, the effect of the number of randomly deployed
sensor nodes was discussed.
5.1. Efficiency of the proposed approach
In order to test the performances of FPCOA, we considered a square area with each side 100m in
length. We considered also that the number of sensors and the communication radius Rc as well
as the sensing radius Rs as constant values. Here the number of sensors was set as 15, Rc as 15m
and Rs as 15m.
Table 4. Deployment results of FPCOA.
As seen in Table 4, the effective coverage area was improved significantly over the 3000
iterations. The decrease in the standard deviation values can be explained by the stability of the
algorithm with larger numbers of iterations. In fact, FCPOA improved the coverage ratio by
48.2% compared with the random initial distribution. To highlight this improvement, the best
10. 126 Computer Science & Information Technology (CS & IT)
deployments obtained by the FCPOA for initial and final configurations are shown in Figure 2
and Figure 3, respectively, where the colored areas represent detected coverage areas.
Figure 3. Initial configuration of Sensors Figure 4. Final configuration of Sensors
5.2. Comparison with other approaches
To evaluate the efficiency of our proposed approach we choose to compare our results with those
obtained with GA and PSO, respectively. Figure 5 gives the comparison of the coverage rate
tested on the same initial population for the three approaches.
Figure 3. Comparison of total coverage ratio with GA and PSO
From this figure, we can find that after the nodes reached stable distribution and obtained the
optimal placement topology, the proposed algorithm has better coverage rate than the other two
approaches. The results of the proposed approach clearly outperform both than GA and PSO
respectively. This figure shows that FPCOA gives a much more stable performance in total
coverage than both the two algorithms.
11. Computer Science & Information Technology (CS & IT) 127
5.3. Effect of Number of Sensor Nodes
In order to show the effect of number of sensor on the total coverage ratio for the propose
approach, we considered that the sensor nodes were randomly deployed in a 50m×50m sensor
field, the communication radius Rc was set as 5m and the sensing radius Rs was set as 5m.
Figure 4. The Coverage Ratio vs. Number of Sensor Nodes
Figure 6 shows the coverage ratio when adding sensor nodes to the network for both of FPCOA
and PSO. As shown, the coverage ratio increases as the number of deployed nodes increases. This
figure indicates that the proposed approach offers higher coverage with less sensor nodes.
FPCOA requires around 32 sensor nodes to get 100% coverage compared to PSO which requires
34 sensor nodes. Thus, it can be said that FPCOA is able to offer higher coverage with the lowest
cost.
6. CONCLUSION
In this paper, the sensor placement problem for WSN is addressed. A deployment approach based
on FPA was proposed. This approach can find the optimal placement topology in terms one QoS
metric. The simulations results of the different scenarios prove that our proposed approach
achieved the optimal placement regarding coverage maximization and connectivity constraint. In
a future work, we will incorporate other QoS metrics like energy consumption and deal with
multi-objective node placement problem for the WSNs.
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AUTHORS
Faten Hajjej received the graduate degree in Computer Engineering from the
National School of Engineers of Sfax, University of Sfax, in 2009. She has been
pursuing the Ph.D degree with the Research Group on Intelligent Machines (REGIM-
Lab), University of Sfax, under the supervision of Dr. Ridha EJBALI and Prof.
Mourad Zaied. His research interests include the internet of things, wireless sensor
network, multi objective optimization, nature inspired optimization algorithms.
Ridha Ejbali received the Ph.D degree in Computer Engineering, Master degree and
computer engineer degree from the National Engineering School of Sfax Tunisia
(ENIS) respectively in 2012, 2006 and 2004. He was assistant technologist at the
Higher Institute of Technological Studies, Kebili Tunisia since 2005. He joined the
faculty of sciences of Gabes Tunisia (FSG) where he is an assistant in the Department
computer sciences since 2012. His research area is now in pattern recognition and
machine learning using Wavelets and Wavelet networks theories.
Mourad Zaied received the HDR, the Ph.D degrees in Computer Engineering and the
Master of science from the National Engineering School of Sfax respectively in 2013,
2008 and in 2003. He obtained the degree of Computer Engineer from the National
Engineering School of Monastir in 1995. Since 1997 he served in several institutes and
faculties in university of Gabes as teaching assistant. He joined in 2007 the National
Engineering School of Gabes (ENIG) as where he is currently an associate professor in
the Department of Electrical Engineering. He is a member of the REsearch Group on
Intelligent Machines laboratory (REGIM) http://www.regim.org in the National
Engineering School of Sfax (ENIS) since 2001. His research interests include
Computer Vision and Image and video analysis. These research activities are centered on Wavelets and
Wavelet networks and their applications to data classification and approximation, pattern recognition and
image, audio and video coding and indexing.