PLAER: Penalty Base Learning Automata for Energy Aware Routing in WSN

Sensors in WSN work with batteries that have limited energy capacity. Therefore, reduction in power consumption is a very important issue. In this paper, we present a new routing algorithm to reduce power consumption in wireless sensor networks. This algorithm deploys Learning automata in each node to find a suitable path for routing data packets. In order to aim this goal the algorithm uses penalty based approach in learning automata and considers energy level of nodes and latency of packet delivery as well. Performance of our new developed algorithm has been compared with LABER and BEAR protocols in OMNET++ simulator. Simulation results show that, in a network with static nodes, energy consumption and control packets reduce significantly and network lifetime increases in comparison with two other protocols.