Learning automaton based topology control protocol for extending wireless sensor networks lifetime

Abstract

Energy efficiency is one of the critical challenges in wireless sensor networks because the nodes in such networks have limited resources. Therefore, they should be managed efficiently in order to exploit the network's functionality for a longer period of time. Topology control mechanisms can help the nodes to leverage their resources efficiently. Several topology control protocols for WSNs have been proposed to decrease energy consumption of the nodes and increase the network capacity. Leveraging a lower transmission range can help the nodes to mitigate their energy consumptions. In this paper, we propose a topology control protocol based on learning automaton, which is named LBLATC. The learning automaton of every sensor node chooses the proper transmission range of the node using the reinforcement signal which is produced by the learning automaton of neighbor sensor nodes. The simulation runs carried out to verify the performance of the proposed protocol. It acts on average 15% better than current state-of-art in term of selecting a proper transmission range.