TARA: Topology-Aware Resource Adaptation to Alleviate Congestion in Sensor Networks

Network congestion can be alleviated either by reducing demand (traffic control) or by increasing capacity (resource control). Unlike in traditional wired or other wireless counterparts, sensor network deployments provide elastic resource availability for satisfying the fidelity level required by applications. In many cases, using traffic control can violate fidelity requirements. Hence, we propose the use of resource control: increasing capacity by enabling more nodes to become active during periods of congestion. However, a naive approach to increase resources without a careful consideration of the type of congestion, traffic pattern, and network topology make the situation worse. In this paper, we present TARA, a topology-aware resource adaptation strategy to alleviate congestion. The core of TARA is our capacity analysis model, which can be used to estimate capacity of various topologies. Detailed performance results show that TARA can achieve data delivery rate and energy consumption that is close to an ideal offline resource control algorithm.