Search-based Adaptive Routing Strategies for Sensor Networks

Ying Zhang and Markus P.J. Fromherz

Abstract

Real-time or agent-centered search has been an active research area in AI for the past decade. These techniques have been applied to many applications including planning in robotic systems and routing in communication networks. Sensor networks are distinguished from traditional networks by characteristics such as deeply embedded routers, highly dynamic networks, resource-constrained nodes, and unreliable and asymmetric links. In this paper, we explore the space of search-based techniques for sensor networks, including piggybacked heuristics, heuristic estimation, promiscuous learning, indirect confirmation, and forward propagation. Performance evaluations for these techniques on real application scenarios are conducted on a routing simulator for sensor networks.

PDF file

Back to the top.