A modified ant colony optimization algorithm (mACO) for energy efficient wireless sensor networks

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• 作者：Vishal Sharma^a ; ^{er_vishusharma@yahoo.com" class="auth_mail" title="E-mail the corresponding author} ; ^{78vishusharma@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Amit Grover^b ; ^{amitgrover_321@rediffmail.com" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Wireless sensor network ; Genetic algorithm ; Ant colony optimization
• 刊名：Optik - International Journal for Light and Electron Optics
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：127
• 期：4
• 页码：2169-2172
• 全文大小：641 K

文摘

The primary limiting factor of a wireless sensor network is the limited battery power that leads to sub-optimal utilization of the network potential. This happens because of non-uniform generation of signals by the sensor nodes through time and space that leads to over utilization of the battery power. This causes the non-functionality of the network, even though a number of nodes with near-maximal battery levels are still operational. To combat with this problem, various groups have proposed various routing strategies. In this work, an ant colony optimization algorithm is modified and is applied to the problem of finding the optimal energy efficient path for the recruitment of sensor nodes for signal transmission to prolong the network lifetime. The proposed method combines the intra-node spatial distance with the rate of battery drain out/recovery with respect to signal transmission. The results indicate the applicability of the mACO approach.