Authors:
Daniel Graham
1
;
Arnold Yim
2
;
Gang Zhou
3
and
Weizhen Mao
3
Affiliations:
1
Department of Computer Science, University of Virginia, Charlottesville, VA and U.S.A.
;
2
Department of Mathematics and Computer Science, Bridgewater College, Bridgewater, VA and U.S.A.
;
3
College of William And Mary, Williamsburg, VA and U.S.A.
Keyword(s):
Compression Algorithm, Energy Efficient Sensing, Wireless Sensor Networks.
Related
Ontology
Subjects/Areas/Topics:
Ad Hoc Networks
;
Data Communication Networking
;
Enterprise Information Systems
;
Internet of Things
;
Power Management
;
Sensor Networks
;
Software Agents and Internet Computing
;
Software and Architectures
;
Telecommunications
;
Wireless Information Networks
;
Wireless Network Protocols
Abstract:
The length of time that a wireless sensor can be deployed is limited by its internal power supply. To increase the deployment lifetime of these sensors we must find ways to conserve power. In this paper, we propose an algorithm that reduces the amount of energy the transceiver consumes by compressing the bytes that are sent and received over the network. The algorithm compresses a data stream by exploiting its temporal locality and is designed to function efficiently on an unreliable network in real-time. A stream is compressed by using fewer bits to represent elements that frequently recur. We evaluate the proposed compression algorithm using a collection of independently collected traces from the crawdad database. We calculated the compression ratio for each trace and found that we were able to reduce the number of bytes transmitted by an average of 60%, resulting in a 30% increase in energy savings.