ELMO: Energy Aware Local Monitoring in Sensor Networks
Over the past decade, local monitoring has been shown to be a powerful technique for improving security in multihop wireless sensor networks (WSNs). Indeed, local monitoring-based security algorithms are becoming the most popular tool for providing security in WSNs. However, local monitoring as it is currently practiced is costly in terms of energy consumption, a major drawback for energy-constrained systems such as WSNs. In WSN environments, the scarce power resources are typically addressed through sleep-wake scheduling of the nodes. However, sleep-wake scheduling techniques in WSNs are vulnerable even to simple attacks. In this paper, a new technique is proposed that promises to allow operation of WSNs in a manner that is both energy-efficient and secure. The proposed technique combines local monitoring with a novel, more secure form of sleep-wake scheduling. The latter is a new methodology dubbed Elmo (Energy Aware Local MOnitoring in Sensor Networks), which enables sleep-wake management in a secure manner even in the face of adversarial nodes that choose not to awaken nodes responsible for monitoring their traffic. An analytical proof is given showing that security coverage is not weakened under ELMO. Moreover, ns-2 simulation results show that the performance of local monitoring is practically unchanged, while energy savings of 20 to 100 times are achieved, depending on the scenario.
local monitoring sensor networks sleep/wake techniques wake-up antenna malicious nodes