One of the most important challenges of wireless sensor network is how to prolong its life time. The main
obstacle in these networks is the limited energy of nodes. We can overcome this problem by optimizing the
nodes' power consumption. The clustering mechanismis the one of the representative approachesto reduce
energy consumption, but optimum clustering of wireless sensor network is an NP-Hard problem. This
paper proposes a hybrid algorithm based on Imperialist competitive algorithm to overcome this clustering
problem. The proposed method, acts on one of the clusters in the network to choose the best sensor in
the cluster as a cluster head. To perform this action, the cluster is divided into several sub-clusters,
each of which has a cluster head. These cluster heads using Assimilation
policies, try to attract the regular nodes to themselves, and Using Imperialistic competition,
they compete with each other until one of these cluster heads is selected as the final cluster head. After this
stage, the algorithm work ends. This algorithm will balance the energy consumption in the network and
improve the network lifetime. To prove efficiency of proposed algorithm(CHEI), we simulated the proposed
algorithm compared with two clustering algorithms using the matlab
Energy aware clustering protocol (eacp)IJCNCJournal
Energy saving to prolong the network life is an important design issue while developing a new routing
protocol for wireless sensor network. Clustering is a key technique for this and helps in maximizing the
network lifetime and scalability. Most of the routing and data dissemination protocols of WSN assume a
homogeneous network architecture, in which all sensors have the same capabilities in terms of battery
power, communication, sensing, storage, and processing. Recently, there has been an interest in
heterogeneous sensor networks, especially for real deployments. This research paper has proposed a new
energy aware clustering protocol (EACP) for heterogeneous wireless sensor networks. Heterogeneity is
introduced in EACP by using two types of nodes: normal and advanced. In EACP cluster heads for normal
nodes are elected with the help of a probability scheme based on residual and average energy of the
normal nodes. This will ensure that only the high residual normal nodes can become the cluster head in a
round. Advanced nodes use a separate probability based scheme for cluster head election and they will
further act as a gateway for normal cluster heads and transmit their data load to base station when they
are not doing the duty of a cluster head. Finally a sleep state is suggested for some sensor nodes during
cluster formation phase to save network energy. The performance of EACP is compared with SEP and
simulation result shows the better result for stability period, network life and energy saving than SEP.
COMPARISON OF ENERGY OPTIMIZATION CLUSTERING ALGORITHMS IN WIRELESS SENSOR NE...IJCSIT Journal
In recent years, Wireless Sensor Networks have gained growing attention from both the research community and actual users. As sensor nodes are generally battery-energized devices, so the network lifetime can be widespread to sensible times.
THRESHOLD SENSITIVE HETEROGENOUS ROUTING PROTOCOL FOR BETTER ENERGY UTILIZATI...ijassn
Advancements in WSN have led to the wide applicability of sensor network in various fields. WSNs basic classification is Reactive and Proactive network. Reactive networks responds to the very immediate changes in its environment in required parameters of interest, as opposed to the Proactive network, due to continuous sensing nature of WSN. To make it more efficient and improved in terms of Energy in network’s
lifetime, we need to reduce the energy expense in the network model, which is one of the most significant issues in wireless sensor networks (WSNs) [1, 2]. In this paper, we proposed an efficient version of TSEP Protocol, which prolongs the networks lifetime by efficient utilization of sensor energy, as we have simulated. We evaluated the performance of our protocol and compared the results with the TSEP. And from the results of simulation, it can be concluded easily that our proposed efficient routing protocol performs better in terms of network lifetime and stability period
Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Netw...IJECEIAES
Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on KMeans clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime.
ENERGY EFFICIENT GRID AND TREE BASED ROUTING PROTOCOLijwmn
In Wireless Sensor Network, a large number of sensor nodes are deployed and they mainly consume energy
in transmitting data over long distances. Sensor nodes are battery powered and their energy is restricted.
Since the location of the sink is remote, considerable energy would be consumed if each node directly
transmits data to the base station. Aggregating data at the intermediate nodes and transmitting using multihops
aids in reducing energy consumption to a great extent. This paper proposes a hybrid protocol
“Energy efficient Grid and Tree based routing protocol” (EGT) in which the sensing area is divided into
grids. The nodes in the grid relay data to the cell leader which aggregates the data and transmits to the
sink using the constructed hop tree. Simulation results show that EGT performs better than LEACH.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
A Transmission Range Based Clustering Algorithm for Topology Control Manetgraphhoc
This paper presents a novel algorithm for clustering of nodes by transmission range based clustering (TRBC).This algorithm does topology management by the usage of coverage area of each node and power management based on mean transmission power within the context of wireless ad-hoc networks. By reducing the transmission range of the nodes, energy consumed by each node is decreased and topology is formed. A new algorithm is formulated that helps in reducing the system power consumption and prolonging the battery life of mobile nodes. Formation of cluster and selection of optimal cluster head and thus forming the optimal cluster taking weighted metrics like battery life, distance, position and mobility is done based on the factors such as node density, coverage area, contention index, required and current node degree of the nodes in the clusters
Energy aware clustering protocol (eacp)IJCNCJournal
Energy saving to prolong the network life is an important design issue while developing a new routing
protocol for wireless sensor network. Clustering is a key technique for this and helps in maximizing the
network lifetime and scalability. Most of the routing and data dissemination protocols of WSN assume a
homogeneous network architecture, in which all sensors have the same capabilities in terms of battery
power, communication, sensing, storage, and processing. Recently, there has been an interest in
heterogeneous sensor networks, especially for real deployments. This research paper has proposed a new
energy aware clustering protocol (EACP) for heterogeneous wireless sensor networks. Heterogeneity is
introduced in EACP by using two types of nodes: normal and advanced. In EACP cluster heads for normal
nodes are elected with the help of a probability scheme based on residual and average energy of the
normal nodes. This will ensure that only the high residual normal nodes can become the cluster head in a
round. Advanced nodes use a separate probability based scheme for cluster head election and they will
further act as a gateway for normal cluster heads and transmit their data load to base station when they
are not doing the duty of a cluster head. Finally a sleep state is suggested for some sensor nodes during
cluster formation phase to save network energy. The performance of EACP is compared with SEP and
simulation result shows the better result for stability period, network life and energy saving than SEP.
COMPARISON OF ENERGY OPTIMIZATION CLUSTERING ALGORITHMS IN WIRELESS SENSOR NE...IJCSIT Journal
In recent years, Wireless Sensor Networks have gained growing attention from both the research community and actual users. As sensor nodes are generally battery-energized devices, so the network lifetime can be widespread to sensible times.
THRESHOLD SENSITIVE HETEROGENOUS ROUTING PROTOCOL FOR BETTER ENERGY UTILIZATI...ijassn
Advancements in WSN have led to the wide applicability of sensor network in various fields. WSNs basic classification is Reactive and Proactive network. Reactive networks responds to the very immediate changes in its environment in required parameters of interest, as opposed to the Proactive network, due to continuous sensing nature of WSN. To make it more efficient and improved in terms of Energy in network’s
lifetime, we need to reduce the energy expense in the network model, which is one of the most significant issues in wireless sensor networks (WSNs) [1, 2]. In this paper, we proposed an efficient version of TSEP Protocol, which prolongs the networks lifetime by efficient utilization of sensor energy, as we have simulated. We evaluated the performance of our protocol and compared the results with the TSEP. And from the results of simulation, it can be concluded easily that our proposed efficient routing protocol performs better in terms of network lifetime and stability period
Energy-Efficient Hybrid K-Means Algorithm for Clustered Wireless Sensor Netw...IJECEIAES
Energy efficiency is the most critical challenge in wireless sensor network. The transmission energy is the most consuming task in sensor nodes, specifically in large distances. Clustered routing techniques are efficient approaches used to lower the transmission energy and maximize the network’s lifetime. In this paper, a hybrid clustered routing approach is proposed for energy optimization in WSN. This approach is based on KMeans clustering algorithm and LEACH protocol. The simulation results using MATLAB tool have shown that the proposed hybrid approach outperforms LEACH protocol and optimizes the nodes energy and the network lifetime.
ENERGY EFFICIENT GRID AND TREE BASED ROUTING PROTOCOLijwmn
In Wireless Sensor Network, a large number of sensor nodes are deployed and they mainly consume energy
in transmitting data over long distances. Sensor nodes are battery powered and their energy is restricted.
Since the location of the sink is remote, considerable energy would be consumed if each node directly
transmits data to the base station. Aggregating data at the intermediate nodes and transmitting using multihops
aids in reducing energy consumption to a great extent. This paper proposes a hybrid protocol
“Energy efficient Grid and Tree based routing protocol” (EGT) in which the sensing area is divided into
grids. The nodes in the grid relay data to the cell leader which aggregates the data and transmits to the
sink using the constructed hop tree. Simulation results show that EGT performs better than LEACH.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
A Transmission Range Based Clustering Algorithm for Topology Control Manetgraphhoc
This paper presents a novel algorithm for clustering of nodes by transmission range based clustering (TRBC).This algorithm does topology management by the usage of coverage area of each node and power management based on mean transmission power within the context of wireless ad-hoc networks. By reducing the transmission range of the nodes, energy consumed by each node is decreased and topology is formed. A new algorithm is formulated that helps in reducing the system power consumption and prolonging the battery life of mobile nodes. Formation of cluster and selection of optimal cluster head and thus forming the optimal cluster taking weighted metrics like battery life, distance, position and mobility is done based on the factors such as node density, coverage area, contention index, required and current node degree of the nodes in the clusters
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
International Journal of Advanced Smart Sensor Network Systems (IJASSN)ijcseit
The placement of base stations in wireless sensor networks affect the energy consumption for
communication between sensor node and base station. In this paper we analyzed the performance of the
zone based clustering protocol [2] under varying position of base stations, different zone sizes and the
effect on network life time with multiple base stations. While evaluating the communication overhead of
various cluster sizes, we observed that the optimal cluster size for a given network is complex, depending
on a range of parameters. Simulation results show that communication overhead decreases as we increase
the number of zone in the network. We show that placing multiple base stations in place of single base
station in zone based routing protocol enhance the network life time.
Energy Consumption Reduction in Wireless Sensor Network Based on ClusteringIJCNCJournal
ABSTRACT
One of the important issues in the routing protocol design in Wireless Sensor Networks (WSNs) is minimizing energy consumption and maximizing network lift time. Nowadays networks and information systems are one of the main parts of modern life that without them, people cannot live. On the hand, the impairment of these networks leads to great and incalculable costs. In this paper, a new method based on clustering has presented that problem of energy consumption is solved. The proposed algorithm is that energy-based clustering can create clusters of the same energy level and distribute energy efficiency across the WNS nodes. This proposed clustering protocol classify network nodes based on energy and neighbourhood criteria and attempts to better balance energy in clusters and ultimately increase network lifetime and maintain network coverage. Results are shown that the proposed algorithm is on average 40% better than LEACH algorithm and 14% better than IBLEACH algorithm.
KEYWORDS
Wireless Sensor Network, Clustering, LEACH Algorithm, IBLEACH Algorithm
Abstract Link : http://aircconline.com/abstract/ijcnc/v11n2/11219cnc03.html
Full Details : http://aircconline.com/ijcnc/V11N2/11219cnc03.pdf
Design Optimization of Energy and Delay Efficient Wireless Sensor Network wit...IOSR Journals
Abstract: In WSN sensors are randomly deployed in the sensor field which brings the coverage problem and limited energy resources. Hence energy and coverage problem are very scarce resources for such sensor systems and has to be managed wisely in order to extend the life of the sensors and maximizing coverage for the duration of a particular mission. In past a lot of cluster based algorithm and techniques were used. In this paper we propose combination of PSO based algorithm and cluster based Least Spanning Tree algorithm, which are very effective alone for WSN, and we also obtain life of sensor node and data transmission by LST based PSO algorithm. These techniques effectively overcome the problems of low energy and coverage of sensor range. Keywords: Energy efficient clustering, Least Spanning Tree algorithm, PSO algorithm, Wireless Sensor Networks.
A Novel Cluster-Based Energy Efficient Routing With Hybrid Protocol in Wirele...IJERA Editor
In wireless sensor network, lifetime of sensor nodes is the most essential parameters. sensor node's lifetime may be extended using LEACH and HEED scheme which is allowing to move the cluster head surrounded by the sensor nodes try to allocate the energy consumption over all nodes in the network. Energy efficiency is depends on the selection of cluster head. In this paper, we proposed the clustering algorithm to minimize the overhead of control packets by using LEACH and HEED and Efficient utilization of node near sink and to implements the hybrid protocol which would be better than the existing protocol.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
Ca mwsn clustering algorithm for mobile wireless senor network [graphhoc
This paper proposes a centralized algorithm for cluster-head-selection in a mobile wireless sensor network.
Before execution of algorithm in each round, Base station runs centralized localization algorithm whereby
sensors update their locations to base station and accordingly Base station performs dynamic clustering.
Afterwards Base station runs CA-MWSN for cluster-head-selection. The proposed algorithm uses three
fuzzy inputs Residual energy, Expected Residual Energy and Mobility to find Chance of nodes to be elected
as Cluster-head. The node with highest Chance is declared as a Cluster-head for that particular cluster.
Dynamic clustering provides uniform and significant distribution of energy in a non-uniform distribution of
sensors. CA-MWSN guarantees completion of the round.
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.
Data Dissemination in Wireless Sensor Networks: A State-of-the Art SurveyCSCJournals
A wireless sensor network is a network of tiny nodes with wireless sensing capacity for data collection processing and further communicating with the Base Station this paper discusses the overall mechanism of data dissemination right from data collection at the sensor nodes, clustering of sensor nodes, data aggregation at the cluster heads and disseminating data to the Base Station the overall motive of the paper is to conserve energy so that lifetime of the network is extended this paper highlights the existing algorithms and open research gaps in efficient data dissemination.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
International Journal of Advanced Smart Sensor Network Systems (IJASSN)ijcseit
The placement of base stations in wireless sensor networks affect the energy consumption for
communication between sensor node and base station. In this paper we analyzed the performance of the
zone based clustering protocol [2] under varying position of base stations, different zone sizes and the
effect on network life time with multiple base stations. While evaluating the communication overhead of
various cluster sizes, we observed that the optimal cluster size for a given network is complex, depending
on a range of parameters. Simulation results show that communication overhead decreases as we increase
the number of zone in the network. We show that placing multiple base stations in place of single base
station in zone based routing protocol enhance the network life time.
Energy Consumption Reduction in Wireless Sensor Network Based on ClusteringIJCNCJournal
ABSTRACT
One of the important issues in the routing protocol design in Wireless Sensor Networks (WSNs) is minimizing energy consumption and maximizing network lift time. Nowadays networks and information systems are one of the main parts of modern life that without them, people cannot live. On the hand, the impairment of these networks leads to great and incalculable costs. In this paper, a new method based on clustering has presented that problem of energy consumption is solved. The proposed algorithm is that energy-based clustering can create clusters of the same energy level and distribute energy efficiency across the WNS nodes. This proposed clustering protocol classify network nodes based on energy and neighbourhood criteria and attempts to better balance energy in clusters and ultimately increase network lifetime and maintain network coverage. Results are shown that the proposed algorithm is on average 40% better than LEACH algorithm and 14% better than IBLEACH algorithm.
KEYWORDS
Wireless Sensor Network, Clustering, LEACH Algorithm, IBLEACH Algorithm
Abstract Link : http://aircconline.com/abstract/ijcnc/v11n2/11219cnc03.html
Full Details : http://aircconline.com/ijcnc/V11N2/11219cnc03.pdf
Design Optimization of Energy and Delay Efficient Wireless Sensor Network wit...IOSR Journals
Abstract: In WSN sensors are randomly deployed in the sensor field which brings the coverage problem and limited energy resources. Hence energy and coverage problem are very scarce resources for such sensor systems and has to be managed wisely in order to extend the life of the sensors and maximizing coverage for the duration of a particular mission. In past a lot of cluster based algorithm and techniques were used. In this paper we propose combination of PSO based algorithm and cluster based Least Spanning Tree algorithm, which are very effective alone for WSN, and we also obtain life of sensor node and data transmission by LST based PSO algorithm. These techniques effectively overcome the problems of low energy and coverage of sensor range. Keywords: Energy efficient clustering, Least Spanning Tree algorithm, PSO algorithm, Wireless Sensor Networks.
A Novel Cluster-Based Energy Efficient Routing With Hybrid Protocol in Wirele...IJERA Editor
In wireless sensor network, lifetime of sensor nodes is the most essential parameters. sensor node's lifetime may be extended using LEACH and HEED scheme which is allowing to move the cluster head surrounded by the sensor nodes try to allocate the energy consumption over all nodes in the network. Energy efficiency is depends on the selection of cluster head. In this paper, we proposed the clustering algorithm to minimize the overhead of control packets by using LEACH and HEED and Efficient utilization of node near sink and to implements the hybrid protocol which would be better than the existing protocol.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
Ca mwsn clustering algorithm for mobile wireless senor network [graphhoc
This paper proposes a centralized algorithm for cluster-head-selection in a mobile wireless sensor network.
Before execution of algorithm in each round, Base station runs centralized localization algorithm whereby
sensors update their locations to base station and accordingly Base station performs dynamic clustering.
Afterwards Base station runs CA-MWSN for cluster-head-selection. The proposed algorithm uses three
fuzzy inputs Residual energy, Expected Residual Energy and Mobility to find Chance of nodes to be elected
as Cluster-head. The node with highest Chance is declared as a Cluster-head for that particular cluster.
Dynamic clustering provides uniform and significant distribution of energy in a non-uniform distribution of
sensors. CA-MWSN guarantees completion of the round.
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.
Data Dissemination in Wireless Sensor Networks: A State-of-the Art SurveyCSCJournals
A wireless sensor network is a network of tiny nodes with wireless sensing capacity for data collection processing and further communicating with the Base Station this paper discusses the overall mechanism of data dissemination right from data collection at the sensor nodes, clustering of sensor nodes, data aggregation at the cluster heads and disseminating data to the Base Station the overall motive of the paper is to conserve energy so that lifetime of the network is extended this paper highlights the existing algorithms and open research gaps in efficient data dissemination.
Wireless sensor networks, clustering, Energy efficient protocols, Particles S...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality.
The most important issue in this type of networks is energy constraints. In this area several researches have
been done from which clustering is one of the most effective solutions. The goal of clustering is to divide
network into sections each of which has a cluster head (CH). The task of cluster heads collection, data
aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach
for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal
fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual
energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation
results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF,
PSO-MV) in terms of network lifetime and energy consumption.
WIRELESS SENSOR NETWORK CLUSTERING USING PARTICLES SWARM OPTIMIZATION FOR RED...IJMIT JOURNAL
Wireless sensor networks (WSN) is composed of a large number of small nodes with limited functionality. The most important issue in this type of networks is energy constraints. In this area several researches have been done from which clustering is one of the most effective solutions. The goal of clustering is to divide network into sections each of which has a cluster head (CH). The task of cluster heads collection, data aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF, PSO-MV) in terms of network lifetime and energy consumption.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
Implementation of energy efficient coverage aware routing protocol for wirele...ijfcstjournal
In recent years, wireless sensor network have been used in many application such as disaster reservation,
agriculture, environmental observation and forecasting .Coverage preservation and energy consumption
are two most important issues in wireless sensor networks. To increase the network lifetime, we propose an
energy efficient coverage aware routing protocol for wireless sensor network for randomly deployed sensor
nodes. Some of the routing protocol is based on energy efficiency and some are based on coverage aware.
The proposed routing protocol is based on both the issues i.e. coverage and energy, in which we first find
the k-mean i.e. the degree of coverage, so that we can use this in the selection of cluster heads in wireless
sensor network by using Genetic Algorithm for increasing network lifetime and coverage. For cluster head
selection each node evaluates its k-mean and energy by internal function which used as fitness function in
genetic algorithm. The proposed algorithm “Implementation of energy efficient coverage aware routing
protocol for Wireless Sensor Network” is designed for homogeneous wireless sensor network. Simulations
results show that proposed algorithm increases the network lifetime by reduce the energy consumption and
preserve coverage. Simulation is done with MATLAB and a comparison of algorithm with benchmark
algorithms is also performed.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
ENERGY EFFICIENT ROUTING ALGORITHM FOR MAXIMIZING THE MINIMUM LIFETIME OF WIR...ijasuc
In wireless sensor network, devices or nodes are generally battery powered devices. These nodes have
limited amount of initial energy that are consumed at different rates, depending on the power level. The
lifetime of the network is defined as the time until the first node fails (or runs out of battery). In this paper
different type of energy efficient routing algorithms are discussed and approach of these algorithms is to
maximize the minimum lifetime of wireless sensor network. Special attention has been devoted for
algorithms formulate the routing problem as a linear programming problem, which uses the optimal flow
path for data transmission and gives the optimum results. Advantages, limitations as well as comparative
study of these algorithms are also discussed in this paper.
Energy efficient clustering in heterogeneousIJCNCJournal
Cluster head election is a key technique used to reduce energy consumption and enhancing the throughput
of wireless sensor networks. In this paper, a new energy efficient clustering (E2C) protocol for
heterogeneous wireless sensor networks is proposed. Cluster head is elected based on the predicted
residual energy of sensors, optimal probability of a sensor to become a cluster head, and its degree of
connectivity as the parameters. The probability threshold to compete for the role of cluster head is derived.
The probability threshold has been extended for multi-levels energy heterogeneity in the network. The
proposed E2C protocol is simulated in MATLAB. Results obtained in the simulationshowthat performance
of the proposed E2Cprotocol is betterthan stable election protocol (SEP), and distributed energy efficient
clustering (DEEC) protocol in terms of energy consumption, throughput, and network lifetime.
ENERGY EFFICIENT DATA COMMUNICATION APPROACH IN WIRELESS SENSOR NETWORKSijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor node creates challenges for routing in WSNs. The research work presents the organized and detailed description of energy conservation method for WSNs. In the proposed method reclustering and multihop data transmission processes are utilized for data reporting to base station by sensor node. The accurate use of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for longer times inside the cluster. The result shows that the proposed clustering approach has higher stable region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy Adaptive Clustering Hierarchy (LEACH) for WSNs.
34 9141 it ns2-tentative route selection approach for edit septianIAESIJEECS
Wireless Sensor Networks (WSNs) assume a crucial part in the field of mechanization and control where detecting of data is the initial step before any automated job could be performed. So as to encourage such perpetual assignments with less vitality utilization proportion, clustering is consolidated everywhere to upgrade the system lifetime. Unequal Cluster-based Routing (UCR) [7] is a standout amongst the most productive answers for draw out the system lifetime and to take care of the hotspot issue that is generally found in equivalent clustering method. In this paper, we propose Tentative Route (TRS) Selection approach for irregular Clustered Wireless Sensor Networks that facilitates in decision an efficient next relay to send the data cumulative by Cluster Heads to the Base Station. Simulation analysis is achieved using the network simulator to demonstrate the effectiveness of the TRS method.
A New Method for Reducing Energy Consumption in Wireless Sensor Networks usin...Editor IJCATR
Nowadays, wireless sensor networks, clustering protocol based on the neighboring nodes into separate clusters and fault
tolerance for each cluster exists for sensors to send information to the base station, to gain the best performance in terms of increased
longevity and maintain tolerance than with other routing methods. However, most clustering protocols proposed so far, only
geographical proximity (neighboring) cluster formation is considered as a parameter. In this study, a new clustering protocol and fault
tolerance based on the fuzzy algorithms are able to clustering nodes in sensor networks based on fuzzy logic and fault tolerance. This
protocol uses clustering sensor nodes and fault tolerance exist in the network to reduce energy consumption, so that faulty sensors
from neighboring nodes are used to cover the errors, work based on the most criteria overlay neighbor sensors with defective sensors,
distance neighbor sensors from fault sensor and distance neighbor sensors from central station is done. Superior performance of the
protocol can be seen in terms of increasing the network lifetime and maintain the best network tolerance in comparison with previous
protocols such as LEACH in the simulation results.
An Integrated Distributed Clustering Algorithm for Large Scale WSN...................................................1
S. R. Boselin Prabhu, S. Sophia, S. Arthi and K. Vetriselvi
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Sunghae Jun
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S. Sagayaraj and M. Poovizhi
SDI System with Scalable Filtering of XML Documents for Mobile Clients ............................................... 1
Yi Yi Myint and Hninn Aye Thant
An Easy yet Effective Method for Detecting Spatial Domain LSB Steganography .................................... 1
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IMPACTS OF STRUCTURAL FACTORS ON ENERGY CONSUMPTION IN CLUSTER-BASED WIRELESS...ijasuc
Limited energy is the major driving factor for research on wireless sensor networks. Clustering alleviates
this energy shortage problem by reducing data traffic conveyed over the network and therefore several
clustering methods are proposed in the literature. Researchers put forward their methods by making
serious assumptions such as always locating single sink at one side of the topology or making clusters near
to the sink with smaller sizes. However, to the best of our knowledge, there is no comprehensive research
that investigates the effects of various structural alternatives on energy consumption of wireless sensor
networks. In this paper, we thoroughly analyse the impact of various structural approaches such as cluster
size, number of tiers in the topology, node density, position and number of sinks. Extensive simulation
results are provided. The results show that the best performance about lifetime prolongation is achieved by
locating a sufficient number of sinks around the network area.
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Cluster head election using imperialist competitive algorithm (chei) for wireless sensor networks
1. International Journal of Mobile Network Communications & Telematics ( IJMNCT) Vol. 4, No.3, June 2014
DOI : 10.5121/ijmnct.2014.4301 01
CLUSTER HEAD ELECTION USING IMPERIALIST
COMPETITIVE ALGORITHM (CHEI) FOR WIRELESS
SENSOR NETWORKS
Moslem Afrashteh Mehr
Science and Research Khouzestan, Iran
ABSTRACT
One of the most important challenges of wireless sensor network is how to prolong its life time. The main
obstacle in these networks is the limited energy of nodes. We can overcome this problem by optimizing the
nodes' power consumption. The clustering mechanismis the one of the representative approachesto reduce
energy consumption, but optimum clustering of wireless sensor network is an NP-Hard problem. This
paper proposes a hybrid algorithm based on Imperialist competitive algorithm to overcome this clustering
problem. The proposed method, acts on one of the clusters in the network to choose the best sensor in
the cluster as a cluster head. To perform this action, the cluster is divided into several sub-clusters,
each of which has a cluster head. These cluster heads using Assimilation
policies, try to attract the regular nodes to themselves, and Using Imperialistic competition,
they compete with each other until one of these cluster heads is selected as the final cluster head. After this
stage, the algorithm work ends. This algorithm will balance the energy consumption in the network and
improve the network lifetime. To prove efficiency of proposed algorithm(CHEI), we simulated the proposed
algorithm compared with two clustering algorithms using the matlab.
KEYWORDS
Wireless Sensor Networks, Clustering, Imperialist competitive algorithm, ICA, Energy Consumption,
Cluster Head Election.
1. INTRODUCTION
Recent advances in wireless communications and electronics have enabled the development of
low cost, low-power, multifunctional sensor nodes that are small in size and communicate
untethered in short distances. These tiny sensor nodes, which consist of sensing, data processing,
and communicating components, leverage the idea of sensor networks [1].
Energy conservation is an important challenge in the design and operation of these networks. The
longer thecommunication distance, the more energy will be consumedduring transmission. So,
clustering mechanism is a key way to reduce energyconsumption.
During the last few years, many clustering algorithms have been proposed, but none of these
algorithms aim at minimizing the energy spent in the system. LEACH [2] isone of these
algorithms to achieve the energy efficiency in the communication between sensor nodes.In each
round, sensor nodes elect itself as a cluster head based on probability model. To elect a cluster
head, each sensor node generates a random number δ between 0 and 1. If the δ is smaller than the
threshold value T (n), the sensor node elects itself as a cluster head and advertises this fact to
other nodes around the cluster head. The most important problem of LEACH is exchanging
clusters and losing energy in comparison to other Algorithms. The Weighted Clustering
2. International Journal of Mobile Network Communications & Telematics ( IJMNCT) Vol. 4, No.3, June 2014
2
Algorithm (WCA) elects a node as a clusterhead based on the number of neighbors, transmission
power, battery-life and mobility rate of the node [3]. The algorithm also restricts the number of
nodes in a cluster so that the performance of the MAC protocol is not degraded. ACE [4]
isanemergentalgorithm that uses just three rounds of feedback to form an efficient cover of cluster
across the network. It uses the node degree as the main parameter to elect cluster heads. In [5], the
authors propose an algorithm that each node calculates its distance to the area centroid which will
recommend nodes close to the area centroid and not the nodes that is central to a particular
cluster, cluster centroid. Thus it leads to overall high energy consumption in the network for other
nodes to transmit data through the selected node.
[6]proposes a clustering algorithm based on ANTCLUST [7]. Using this method, the sensor
nodes with more residual energy independently become cluster heads. However, it produces much
control overhead during iterations. TPC [8] is a novel two-phase clustering (TPC) scheme for
energy-saving and delay-adaptive data gathering in wireless sensor networks. Each node
advertises for cluster head with a random delay, and the node who overhears others’
advertisement will give up its own advertisement. In such a way, the network is partitioned into
clusters in the first phase. In the second phase, each member searches for a neighbor closer to the
cluster head within the cluster to set up an energy-saving and delay-adaptive data relay link .With
the advantages of chain topology, TPC achieves a great tradeoff between energy cost and delay.
PEBECES [9] divides the network into several equally distributed sections and then categorizes
them into clusters with different sizes. In this algorithm, each node is equipped with GPS and
sends its position and remaining energy to the sink directly. In the method proposed in [10],
clusters and cluster heads are selected dynamically using genetic algorithm. This method
considers distance between nodes and the number of cluster heads as parameters for clustering but
didn’t consider the residual energy of the nodes. One of the main parameters for selecting the
cluster heads is residual energy of sensor. Gupta in [11] used fuzzy logic to find cluster heads. In
this method, during each period, the sensor that has the most chance is selected as cluster head.
Three fuzzy variables are used to calculate the chance including: residual energy of the nodes, the
number of neighbors of the nodes, and centrality. In this method, the base station determines
cluster heads.
In this paper, we propose a clustering algorithm which takes several parameters into consideration
for dynamic clustering. the proposed protocol will balance the energy consumption in the network
and prolongs the network lifetime.
The organization of the rest of this paper is as follows:In Section 2, describes the Imperialist
Competitive Algorithm. In section 3, the proposed protocol is presented. In section 4, we describe
our simulation environment and experimental results. Finally Section 5 is the conclusion.
2. IMPERIALIST COMPETITIVE ALGORITHM
Figure 1 shows the flowchart of the Imperialist Competitive Algorithm. This algorithm starts by
generating a set of candidate random solutions in the search space of the optimization problem.
The generated random points are called the initial Countries. Countries in this algorithm are the
counterpart of Chromosomes inGenetic Algorithm (GA) and Particles in Particle Swarm
Optimization (PSO) and it is an array of values of a candidate solution of optimization problem.
The cost function of the optimization problem determines the power of each country. Based on
their power, some of the best initial countries (the countries with the least cost function value),
become Imperialists and start taking control of other countries (called colonies) and form the
initialEmpires[12].
3. International Journal of Mobile Network Communications & Telematics ( IJMNCT) Vol. 4, No.3, June 2014
3
Two main operators of this algorithm are Assimilation and Revolution. Assimilation makes the
colonies of each empire get closer to the imperialist state in the space of socio-political
characteristics (optimization search space). Revolution brings about sudden random changes in
the position of some of the countries in the search space. During assimilation and revolution a
colony might reach a better position and has the chance to take the control of the entire empire
and replace the current imperialist state of the empire[13].
Imperialistic Competition is another part of this algorithm. All the empires try to win this game
and take possession of colonies of other empires. In each step of the algorithm, based on their
power, all the empires have a chance to take control of one or more of the colonies of the weakest
empire[12].
Algorithm continues with the mentioned steps (Assimilation, Revolution, Competition) until a
stop condition is satisfied.
Figure 1. Flowchart of Imperialist Competitive Algorithm (ICA)
3. PROPOSED METHOD
The proposed method, acts on one of the clusters in the network to choose the best sensor in
the cluster as a cluster head. To perform this action, the cluster is dividedinto several sub-
clusters, each of which has a cluster head. These cluster heads using Assimilation
policies, try to attract the regular nodes to themselves, and Using Imperialistic competition,
they compete with each other until one of these cluster heads is selected as the final cluster head.
4. International Journal of Mobile Network Communications & Telematics ( IJMNCT) Vol. 4, No.3, June 2014
4
After this stage, the algorithm work ends. This algorithm will balance the energy consumption in
the network and prolong the network lifetime.
3.1. Forming the initial Countries
Since our purpose is to choose sensors in a cluster to choose the best sensor as cluster
head, so possible responses on this issue, which include all sensors in the cluster and
are equivalent to the country in the ICA.
Here, in the starting, random number of these sensorsare considered as the initial Countries and
among them,the suitable numbers are considered as initial empires (which here are cluster
heads) and other sensors as a colony (which here are equivalent to regular nodes) . To divide
initial regular nodes, every cluster head is given a number of regular nodes corresponding to its
power.
Since the first time, the energy of all sensors are equal, so we only consider the
distance among sensors as the main parameter to select the initial empires:
D=∑ ሺDRSi െ ሺDRCi DCSሻሻெ
୧ୀଵ (14)
Where DRSirepresents the total distance between all regular nodes to the sink node, DRCi
represent total distance from all regular nodes toward their cluster head and DCSrepresents the
total distance from all cluster head toward the sink node.
3.2. Implementation the Assimilation Policy
Based on Assimilation Policy, cluster heads using cost function(Equation No. (14)), try to attract
regularnodes. As soon as, the sensors starting to activity, the amount of their energy will be
reduce, therefore to choose cluster heads, in addition to the distance between sensors, the value
of their energy should be taken into consideration.
So, two basic parameters "amount of energy required to send a message" and "residual energy
nodes", determine the power of a cluster head to attract regular nodes.
3.3. Exchanging positions of the cluster head and a regular node
since cluster heads use more energy than the others, after a while, their energy is reduced and can
not act as a cluster head. So, one of the regular nodes that has the normal conditions listed is
selected as a cluster head, and between the previous and the current node displacement takes
place and other nodes join the current node.
3.4.Implementation of the Imperialistic competition
According to imperialistic competition, each cluster head that can not evaluat three mentioned
basic parametersin the above, are deleted from competition and its member nodes become the
members of cluster heads which are near them. Cluster heads will be deleted step by step until we
reach one cluster head which is chosen as the final cluster head and all regular nodes will be
joined to it.
5. International Journal of Mobile Network Communications & Telematics ( IJMNCT) Vol. 4, No.3, June 2014
5
3.5. Cost Function Parameters
We use a radio model described in [8]. In this model, for a short range transmission such as
within clusters, the energy consumed by a transmit amplifier is proportional to d2
, where d is the
distance between nodes. However, for a long range transmission such as from a cluster head to
the base station, the energy consumed is proportional to d4
. Using the given radio model, the
energy consumed ETij to transmit a message of length k bits from a node i to a node j is given by
Equation 15 and Equation 16 for short and long distances, respectively.
ETij=K*Ee+K*€fs*d2
ij d < dco (15)
ETij=K*Ee+K*€amp*d4
ijd >= dco (16)
Moreover, ER, the energy consumed in receiving the k-bit message, is given by:
ER = k*Ee + k*EBF (17)
where EBF represents the cost of beam forming approach to reduce the energy consumption.
The cost of a country is designed to minimize the energy consumption and to extend the network
life time. A few cost parameters are described in this section:
1. ETdrs, represent the sum of required energy to sending one message directly from
all regular nodes toward the sink node. This required energy is defined as follows:
ETdrs=∑ ETrs m כ ER୬
୧ୀ m >= n (18)
Where ETrs represent the sum of required energy for sending one message from all regular
nodes toward the sink node and ER, is the radio energy dissipation.
.
2. ETrcs, represents the sum of required energy for sending one message from all regular
nodes in a cluster toward their cluster head and the sum of required energy for sending
one message from the cluster head toward the sink node. This required energy is
defind as follows:
ETrcs= ∑ ETrc m כ ER ETcs
ୀଵ m >= n (19)
Where ETrc represents the sum of required energy for sending one message from all regular nodes
in a cluster toward their cluster head, (m*ER) represents the sum of required energy for recieving
one message from all regular nodes in a cluster and ETcs represents the sum of required energy for
sending one message from the cluster head toward the sink node.
SE= ETdrs - ETrcs (20)
3. LE, represent the at least required energy for receiving a k-bit message by the cluster
headand send it to sink. This required energy is defined as follows:
LE= ETij +ER (21)
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3.6. Cost Function
because the purpose of this algorithm is optimizing energy consumption that results in increasing
the networks lifetime, so we have to consider the residual energy of the nodes as a main
parameter for selecting the cluster head. The second parameter that is considered is the required
energy to send a message toward the sink node. The lower the communication distance, the less
energy will be consumed during transmission. Each individual is evaluated by the following
fitness function:
Cost Function = LE + RE + SE (22)
In this function, RE represents the residual energy in the cluster head.
4. SIMULATION RESULT
We have simulated the proposed algorithm using MATLAB and compared it to LEACH protocol
and [14]. The list of the used simulation parameters and their values are shown in table 1:
TABLE 1: The values of the simulation parameters
ValuesParameters
200Initial Countries
20Initial Imperialistic
2Β
45oγ
10 mSensing range of nodes
100*100 m2
Network dimensions
1 JulesInitial energy of each node
400 BitsPacket size
100Number of Iteration
50 nj/bit/signalEe
10 pj/bit/m2
€fs
0.0013 pj/bit/m4
€amp
10mdco
1 nj/bitConsumption energy for sending a bit
In the first experiment, we compared the sum of residual energy of nodes in the proposed protocol
to LEACH protocol and [14] during different rounds. As can be seen in Figure 8, the proposed
algorithm consumes energy uniformly and so, prolongs the network lifetime.
Figure 8. Comparing sum of residual energy
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In the second experiment, we compared the number of alive nodes in our protocol to LEACH
protocol and [14] during different rounds. The results of this experiment are shown In Figure 9. It
can be observed that the proposed protocol has considerably more number of alive nodes in each
round in comparison with the LEACH protocol and [14].
Figure 9. Number of alived nodes in different rounds
In the third experiment, we compared the Response time to reach in our protocol to LEACH
protocol and [14]. The results of this experiment are shown In Figure 10. It can be observed that
the proposed protocol has considerably more number of alive nodes in each round in comparison
with the LEACH protocol and [14].
Figure 10. The time to get answers
In the four experiment, the distribution of the cluster heads in the proposed algorithm is compared
to LEACH protocol. Figure11, 12 and 13 shows the result of this comparison.
Figure 11. Improper distribution of the cluster heads in the proposed algorithm
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Figure 12. Improper distribution of the cluster heads in LEACH algorithm
Figure 13. Improper distribution of the cluster heads in [14] algorithm
5. CONCLUSION
In this paper, we proposed a cluster head election algorithm based onImperialist competitive
algorithm. The proposed algorithm takes different parameters into consideration to increase the
network lifetime. This parameters are residual energy in the cluster head, required energy to send
a message toward the sink node and the at- least required energy for receiving a k-bit message
by the cluster head and send it to sink. In order to evaluate ouralgorithm, we simulated our
protocol and compared it to LEACH protocol and [14]. The results of the simulations show
theeffectiveness of the proposed mechanism.
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Authors
Moslem Afrashteh Mehr received his M. SC. Degree in computer engineering from the
science and research Khouzestan, Iran in 2011. His main research interests is in the area of
wireless sensor network.