A Learning Based Method for Topology Control in Wireless Sensor Networks

Abstract

Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption and radio interference, The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes' transmitting range. In this paper we present a new distributed learning based method to choose nodes transmitting range, in this method we run a range adjustment mechanism periodically to choose a near optimal transmitting range, we don't need any information about location of nodes or distance between nodes or received signal strength, the communication overhead of this method is very low, performance evaluation results show that this method decrease the energy consumption and overcome other existing methods in some scenarios.