Learning-Based Power Efficient Routing Algorithms Balancing Network Lifetime and Packet Delay for Wireless Sensor Networks

Power-saving is a critical issue for Wireless sensor networks (WSNs). A Learning-based power efficient routing (LPER) algorithm is proposed. In the LPER, a fitness function, which balances network lifetime, energy consumption, and packet delay, is constructed and used in an ant colony system to establish the optimal route. In addition, reinforcement learning is applied in predicting the energy consumption of neighboring nodes. The LPER is able to optimize network lifetime of WSNs, while keeping energy consumption and packet delay in a relative low level. Numeric experiments show the LPER outperforms the Minimal spanning tree (MST) and the Least energy tree (LET) based routing algorithms in terms of network lifetime and packet delay.