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Distributed source coding for sensor networks (2004)
| Venue: | In IEEE Signal Processing Magazine |
| Citations: | 224 - 4 self |
BibTeX
@INPROCEEDINGS{Xiong04distributedsource,
author = {Zixiang Xiong and Angelos D. Liveris and Samuel Cheng},
title = {Distributed source coding for sensor networks},
booktitle = {In IEEE Signal Processing Magazine},
year = {2004},
pages = {522--533}
}
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Abstract
n recent years, sensor research has been undergoing a quiet revolution, promising to have a significant impact throughout society that could quite possibly dwarf pre-vious milestones in the information revolution. MIT Technology Review ranked wireless sensor networks that con-sist of many tiny, low-power and cheap wireless sensors as the number one emerging technology. Unlike PCs or the Internet, which are designed to support all types of applications, sensor networks are usually mission driven and application specific (be it detection of biological agents and toxic chemicals; environmental measure-ment of temperature, pressure and vibration; or real-time area video surveillance). Thus they must operate under a set of unique constraints and requirements. For example, in contrast to many other wireless devices (e.g., cellular phones, PDAs, and laptops), in which energy can be recharged from time to time, the energy provisioned for a wireless sensor node is not expected to be renewed throughout its mission. The limited amount of energy available to wireless sensors has a significant impact on all aspects of a wireless sensor network, from the amount of information that the node can process, to the volume of wireless communication it can carry across large distances. Realizing the great promise of sensor networks requires more than a mere advance in individual technologies; it relies on many com-ponents working together in an efficient, unattended, comprehensible, and trustworthy manner. One of the enabling technologies for sensor networks is distributed source coding (DSC), which refers to the compression of multiple correlated sensor out-puts [1]–[4] that do not communicate with each other (hence distributed coding). These sensors send their compressed outputs to a central point [e.g., the base station (BS)] for joint decoding. I
Keyphrases
sensor network significant impact wireless sensor network individual technology information revolution wireless communication mere advance wireless sensor wireless sensor node large distance trustworthy manner multiple correlated sensor out-puts environmental measure-ment application specific cellular phone dwarf pre-vious milestone enabling technology mission driven mit technology review base station toxic chemical cheap wireless sensor many wireless device joint decoding sensor research great promise source coding limited amount quiet revolution biological agent recent year central point real-time area video surveillance many com-ponents unique constraint
