Optimization of an RF Sensor Network

Abstract

This case study applies Jurdak’s framework to a test-bed of sensor nodes that communicate through RF signals. In particular, we explore the benefits of this approach in reducing the idle listening at individual nodes in order to reduce the energy consumption and to balance the forwarding load among network nodes. Our study introduces Adaptive Low Power Listening (ALPL), an adaptive cross-layer mechanism that builds on BMAC [56] in order to enable individual nodes to seamlessly adapt their listening modes to their local states. The chapter identifies three state aspects that impact energy consumption: (1) number of descendants in the routing tree; (2) radio duty cycle; and (3) role. We conduct experiments on a test-bed of 14 mica 2 sensor nodes to compare the state representations and to evaluate the framework’s energy benefits. The experiments show that the degree of load balancing increases for expanded cross-layer state representations. The experiments also reveal that all state representations in Jurdak’s framework reduce global energy consumption in the range of one-third for a time-driven monitoring network, and in the range of one-fifth for an event-driven target tracking network.