Energy efficient geographic routing algorithms in wireless sensor network

Over the past decade, energy efficiency has consistently been a critical research topic in the field of wireless sensor networks. In wireless networks, signal interference often leads to power waste in a sensor node. Several SINR-based routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or may slow in routing computation speed. In this paper, two energy efficient geographic routing algorithms (EEGRA) for wireless sensor network are proposed to address the power consumption issue while considering the routing computation speed. The first algorithm take the value of interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained optimization problem, and solves it by searching the optimal discretized interference level. We adopt four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, in EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The experimental result shows that the EEGRA algorithms reduce energy consumption by 30-50% comparing to geographic routing methods. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.