An Ant Colony System Based Energy Prediction Routing Algorithms for Wireless Sensor Networks

Routing algorithms play important roles in wireless sensor networks (WSNs). Usually, nodes in a WSN run on battery with limited power. Hence, routing with efficient power consumption is becoming a critical issue for WSNs. In this paper, a routing algorithm, referred to as Energy Prediction and Ant Colony Optimization Routing (EPACOR), is proposed. In the EPACOR, when a node needs to deliver data to the sink, ant colony systems are used to establish the route with optimal or sub-optimal power consumption, and meanwhile, learning mechanism is embedded to predict the energy consumption of neighboring nodes when the node chooses a neighboring node added to the route. The EPACOR is compared both with the MST (Minimal Spanning Tree)-based routing algorithm following the Prim algorithm and with the Least Energy Tree (LET)-based routing algorithm following the Dijkstra algorithm. Numeric experiment shows that the EPACOR has the best network lifetime among the three while keeping energy consumption in low level.