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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 8, 2018.
Abstract: Energy consumption minimization is crucial for the constrained sensors in wireless sensor networks (WSNs). Partitioning WSNs into optimal set of clusters is a promising technique utilized to minimize energy consumption and to increase the lifetime of the network. However, optimizing the network into optimal set of clusters is a non-polynomial (NP) hard problem, and the time needed to solve such problem increases exponentially as the number of sensors increases. In this paper, simulated evolution (SimE) algorithm is engineered to tackle the problem of cluster optimization in WSNs. A goodness measure is developed to measure the accuracy of assigning nodes to clusters and to evaluate the clustering quality of the overall network. SimE was developed such that the number of clusters and cluster heads are adaptive to number of alive nodes in the network. In fact, extensive simulation results demonstrate that SimE provides near optimal clustering and improves the lifetime of the network by about 21% compared to the traditional LEACH-C protocol.
Abdulaziz Alsayyari, “Adaptive Simulated Evolution based Approach for Cluster Optimization in Wireless Sensor Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 9(8), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090818
@article{Alsayyari2018,
title = {Adaptive Simulated Evolution based Approach for Cluster Optimization in Wireless Sensor Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090818},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090818},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {8},
author = {Abdulaziz Alsayyari}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.