Energy efficient data collection with multiple mobile sink using artificial bee colony algorithm in large-scale WSN

In most wireless sensor networks (WSN), multi-hop routing algorithm is used to transmit the data collected by sensors to user. Multi-hop forwarding leads to energy hole problem and high transmission overhead in large scale WSN. In order to address these problems, this paper proposes multiple mobile sink based data collection algorithm, which introduces energy balanced clustering and Artificial Bee Colony based data collection. The cluster head election is based on the residual energy of the node. In this study, we focused on a large-scale and intensive WSN which allows a certain amount of data latency by investigating mobile Sink balance from three aspects: data collection maximization, mobile path length minimization, and network reliability optimization. Simulation results show that, in comparison with other algorithms such Random walk and Ant Colony Optimization, the proposed algorithm can effectively reduce data transmission, save energy, improve network data collection efficiency and reliability, and extend the network lifetime.

Abstract licence: CC BY-NC

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