Toward Energy Efficient Multistream Collaborative Compression in Wireless Sensor Networks


Wireless sensor networks possess significant limitations in storage, bandwidth, and power. This has led to the development of several compression algorithms designed for sensor networks. Many of these methods exploit the correlation often present between the data on different sensor nodes in the network; however, correlation can also exist between different sensing modules on the same sensor node. Exploiting this correlation can improve compression ratios and reduce energy consumption without the cost of increased traffic in the network. We investigate and analyze approaches for compression utilizing collaboration between separate sensing modules on the same sensor node. The compression can be lossless or lossy with a parameter for maximum tolerable error. Performance evaluations over real world sensor data show increased energy efficiency and bandwidth utilization with a decrease in latency compared to some recent approaches for both lossless and loss tolerant compression.

Meeting Name

10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2014 (2014: Oct. 22-25, Miami, FL)


Computer Science

Keywords and Phrases

Bandwidth; Bandwidth compression; Compaction; Digital storage; Energy efficiency; Energy utilization; Sensor nodes; Band-width utilization; Collaborative; Compression algorithms; Energy efficient; Investigate and analyze; Multi-stream; Real time; Reduce energy consumption; Wireless sensor networks; Compression; Real-time

International Standard Book Number (ISBN)


Document Type

Article - Conference proceedings

Document Version


File Type





© 2014 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Oct 2014