DocumentCode
3541455
Title
Lossless Data Compression for Wireless Sensor Networks Based on Modified Bit-Level RLE
Author
Shengchun Long ; Pengyuan Xiang
Author_Institution
Coll. of Comput. Sci. & Technol., Zhejiang Univ. of Technol., Hangzhou, China
fYear
2012
fDate
21-23 Sept. 2012
Firstpage
1
Lastpage
4
Abstract
Energy in wireless sensor networks is one of the most important resources, most of the energy is consumed in communication. The wireless transmission of a single bit requires over thousand times energy more than a single 32-bit computation, so data compression provides a viable approach towards the preserved energy by reducing packet size. In this article, a new simple and effective lossless data compression which suited to latency tolerant transmission in environmental monitoring WSNs is proposed. The algorithm realizes data transformation and rearrange of bits at first, then RLE is used to compress the rearranged bit stream, finally Huffman coding is used to record the run-length. At last, the proposed algorithm is evaluated and compared with other algorithms. The results show that it is remarkable in reducing storage space and increasing the compression ratio.
Keywords
Huffman codes; data compression; environmental factors; runlength codes; wireless sensor networks; Huffman coding; bit stream; compression ratio; data transformation; environmental monitoring WSN; latency tolerant transmission; lossless data compression; modified bit-level RLE; packet size reduction; run-length encoding; storage space reduction; wireless sensor networks; wireless transmission; Algorithm design and analysis; Compression algorithms; Data compression; Encoding; Temperature measurement; Temperature sensors; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications, Networking and Mobile Computing (WiCOM), 2012 8th International Conference on
Conference_Location
Shanghai
ISSN
2161-9646
Print_ISBN
978-1-61284-684-2
Type
conf
DOI
10.1109/WiCOM.2012.6478565
Filename
6478565
Link To Document