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A Swarm Optimization Based Power Aware Clustering Strategy for WSNs

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@article{IJASEIT1638,
   author = {Harendra S. Jangwan and Ashish Negi},
   title = {A Swarm Optimization Based Power Aware Clustering Strategy for WSNs},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {1},
   year = {2017},
   pages = {250--256},
   keywords = {Swarm Optimization, Energy Efficiency, Wireless Sensor Network, Cluster Head Selection Algorithm, Heterogeneous Environment},
   abstract = {

The technique of division of a wireless sensor network (WSN) into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS) and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH) selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP) and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP). MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1638},    doi = {10.18517/ijaseit.7.1.1638} }

EndNote

%A Jangwan, Harendra S.
%A Negi, Ashish
%D 2017
%T A Swarm Optimization Based Power Aware Clustering Strategy for WSNs
%B 2017
%9 Swarm Optimization, Energy Efficiency, Wireless Sensor Network, Cluster Head Selection Algorithm, Heterogeneous Environment
%! A Swarm Optimization Based Power Aware Clustering Strategy for WSNs
%K Swarm Optimization, Energy Efficiency, Wireless Sensor Network, Cluster Head Selection Algorithm, Heterogeneous Environment
%X 

The technique of division of a wireless sensor network (WSN) into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS) and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH) selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP) and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP). MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1638 %R doi:10.18517/ijaseit.7.1.1638 %J International Journal on Advanced Science, Engineering and Information Technology %V 7 %N 1 %@ 2088-5334

IEEE

Harendra S. Jangwan and Ashish Negi,"A Swarm Optimization Based Power Aware Clustering Strategy for WSNs," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 1, pp. 250-256, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.1.1638.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Jangwan, Harendra S.
AU  - Negi, Ashish
PY  - 2017
TI  - A Swarm Optimization Based Power Aware Clustering Strategy for WSNs
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 1
Y2  - 2017
SP  - 250
EP  - 256
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - Swarm Optimization, Energy Efficiency, Wireless Sensor Network, Cluster Head Selection Algorithm, Heterogeneous Environment
N2  - 

The technique of division of a wireless sensor network (WSN) into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS) and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH) selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP) and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP). MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1638 DO - 10.18517/ijaseit.7.1.1638

RefWorks

RT Journal Article
ID 1638
A1 Jangwan, Harendra S.
A1 Negi, Ashish
T1 A Swarm Optimization Based Power Aware Clustering Strategy for WSNs
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 1
YR 2017
SP 250
OP 256
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 Swarm Optimization, Energy Efficiency, Wireless Sensor Network, Cluster Head Selection Algorithm, Heterogeneous Environment
AB 

The technique of division of a wireless sensor network (WSN) into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS) and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH) selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP) and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP). MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1638 DO - 10.18517/ijaseit.7.1.1638