Energy-aware Dual-path Geographic Routing to Bypass Routing Holes in Wireless Sensor Networks

Abstract

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Geographic routing has been considered as an attractive approach for resource-constrained wireless sensor networks (WSNs) since it exploits local location information instead of global topology information to route data. However, this routing approach often suffers from the routing hole (i.e., an area free of nodes in the direction closer to destination) in various environments such as buildings and obstacles during data delivery, resulting in route failure. Currently, existing geographic routing protocols tend to walk along only one side of the routing holes to recover the route, thus achieving suboptimal network performance such as longer delivery delay and lower delivery ratio. Furthermore, these protocols cannot guarantee that all packets are delivered in an energy-efficient manner once encountering routing holes. In this paper, we focus on addressing these issues and propose an energy-aware dual-path geographic routing (EDGR) protocol for better route recovery from routing holes. EDGR adaptively utilizes the location information, residual energy, and the characteristics of energy consumption to make routing decisions, and dynamically exploits two node-disjoint anchor lists, passing through two sides of the routing holes, to shift routing path for load balance. Moreover, we extend EDGR into three-dimensional (3D) sensor networks to provide energy-aware routing for routing hole detour. Simulation results demonstrate that EDGR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared to other geographic routing protocols in WSNs over a variety of communication scenarios passing through routing holes. The proposed EDGR is much applicable to resource-constrained WSNs with routing holes.This work has been partially supported by the National Natural Science Foundation of China (No. 61402343, No. 61672318, No. U1504614, No. 61631013, and No. 61303241), the National Key Research and Development Program (No. 2016YFB1000102), the Natural Science Foundation of Suzhou/Jiangsu Province (No. BK20160385), the EU FP7 QUICK Project (No. PIRSESGA- 2013-612652), and the projects of Tsinghua National Laboratory for Information Science and Technology (TNList)