A general framework for efficient geographic routing in wireless networks

• Published in: Computer networks (Amsterdam, Netherlands : 1999) Vol. 54; no. 5; pp. 844 - 861
• Main Authors: Lee, Seungjoon, Bhattacharjee, Bobby, Banerjee, Suman, Han, Bo
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 08.04.2010; Elsevier; Elsevier Sequoia S.A
• Subjects: Applied sciences; Comparative analysis; Decision making models; Exact sciences and technology; Geographic routing; Link cost estimation; Miscellaneous; Routing; Routing metric; Simulation; Studies; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Teleprocessing networks. Isdn; Transmission and modulation (techniques and equipments); Wireless multihop networks; Wireless networks; Link cost estimation; Geographic routing; Routing metric; Wireless multihop networks; Test bench; Performance evaluation; Wireless telecommunication; Data transmission; Routing; Background noise; Multihop network; Wireless network; Cost estimation; Metric; Transmission loss
• ISSN: 1389-1286; 1872-7069
• DOI: 10.1016/j.comnet.2009.09.013

We propose a new link metric called normalized advance (NADV) for geographic routing in multihop wireless networks. NADV selects neighbors with the optimal trade-off between proximity and link cost. Coupled with the local next hop decision in geographic routing, NADV enables an adaptive and efficient cost-aware routing strategy. Depending on the objective or message priority, applications can use the NADV framework to minimize various types of link cost. We present efficient methods for link cost estimation and perform detailed experiments in simulated environments. Our results show that NADV outperforms current schemes in many aspects: for example, in high noise environments with frequent packet losses, the use of NADV leads to 81% higher delivery ratio. When compared to centralized routing under certain settings, geographic routing using NADV finds paths whose cost is close to the optimum. We also conducted experiments in Emulab testbed and the results demonstrate that our proposed approach performs well in practice.