Energy-Scalable Protocols for Battery-Operated MicroSensor Networks
MASSACHUSETTS INST OF TECH CAMBRIDGE DEPT OF ELECTRICAL ENGINEERING
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To maximize battery lifetimes of distributed wireless sensors, network protocols and data fusion algorithms should he designed with low power techniques. Network protocols minimize energy by using localized communication and control and by exploiting computationcommunication trade-offs. In addition, data fusion algorithms such as beamforming aggregate data from multiple sources to reduce data redundancy and enhance signal-to-noise ratios, thus further reducing the required communications. We have developed a sensor network system that uses a localized clustering protocol and beamforming data fusion to enable energy-efficient collaboration. We have implemented two beamforming algorithms, the Maximum Power and the Least Mean Squares LMS beamforming algorithms, on the StrongARM SA-1100 processor. Results from our experiments show that the LMS algorithm requires less than one-fifth the energy required by the Maximum Power beamforming algorithm with only a 3 dB loss in performance. The energy requirements of the LMS algorithm was further reduced through the use of variable length filters, a variable voltage supply, and variable adaptation time.
- Computer Systems
- Command, Control and Communications Systems