Power-Efficient Adaptable Wireless Sensor Networks

John Lach, David Evans, Jon McCune, Jason Brandon.
Military and Aerospace Programmable Logic Devices (MAPLD) International Conference 2003
September 9-11, 2003.

Distributed wireless sensor networks are expected to have widespread applications within the coming decades, ranging from military tracking and emergency response to habitat monitoring and environmental tracking. These networks must be capable of adapting to changing environments and requirements. A sensor network application may need to alter its behavior to manage limited resources more efficiently, recover from broken network links, or change its functional behavior in response to commands issued by an operator.

Since sensor nodes (complete with sensing data collection, processing, and transmission) are untethered and typically must run on small batteries, a primary factor in determining the utility of a distributed sensor network is how well it manages energy. Hence, the adaptations considered here focus on allowing a sensor network to adapt energy consumption in ways that increase longevity in exchange for reduced fidelity, increased latency or weakened security.

Currently, most sensor nodes are software based, which provides the flexibility necessary for adaptation. A variety of programs can be stored in a node's local memory, or a base station can wirelessly distribute programs for necessary adaptations. However, a processor executing software is far less efficient (in terms of energy consumption, manufacturing cost per unit, and performance) than a fixed-logic ASIC. On the other hand, an ASIC does not have the flexibility for node-level adaptation.

This paper explores the use of field-programmable hardware in sensor nodes, which provides node flexibility with significantly greater energy efficiency than software. Just as with the software-based approach, node behavior and non-functional properties can be altered using locally stored or broadcasted configuration data. Experimental results reveal that node adaptability is maintained with significant energy efficiency improvements (and therefore increased network lifetime) over processor-based nodes.

Abstract (2 pages) [PDF]
Full Paper (8 pages) [PDF]