Abstract:
Technological advancements in embedded systems due to Moore's law have lead to the proliferation of wireless sensor networks (WSNs) in different application domains (e.g....Show MoreMetadata
Abstract:
Technological advancements in embedded systems due to Moore's law have lead to the proliferation of wireless sensor networks (WSNs) in different application domains (e.g. defense, health care, surveillance systems) with different application requirements (e.g. lifetime, reliability). Many commercial-off-the-shelf (COTS) sensor nodes can be specialized to meet these requirements using tunable parameters (e.g. voltage, frequency) to specialize the operating state. Since a sensor node's performance depends greatly on environmental stimuli, dynamic optimizations enable sensor nodes to automatically determine their operating state in-situ. However, dynamic optimization methodology development given a large design space and resource constraints (memory and computational) is a very challenging task. In this paper, we propose a lightweight dynamic optimization methodology that intelligently selects initial tunable parameter values to produce a high-quality initial operating state in one-shot for time-critical or highly constrained applications. Further operating state improvements are made using an efficient greedy exploration algorithm, achieving optimal or near-optimal operating states while exploring only 0.04% of the design space on average.
Published in: 2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications
Date of Conference: 11-13 October 2010
Date Added to IEEE Xplore: 29 November 2010
ISBN Information: