DocumentCode :
3326131
Title :
CoXoH: Low cost energy efficient data compression for wireless sensor nodes using data encoding
Author :
Hussian, S.I. ; Javed, Hassan ; Ur Rehman, Waheed ; Khalil, F.N.
Author_Institution :
Dept. of Comput. Sci., Univ. of Peshawar, Peshawar, Pakistan
fYear :
2011
fDate :
11-13 July 2011
Firstpage :
149
Lastpage :
152
Abstract :
The limited resources of Wireless Sensor Networks such as battery power, storage and processing power needs to be utilized very efficiently to prolong network life. WSN operates on battery power which cannot be replaced easily. Since data transmission consumes most amount of energy, therefore data needs to be compressed before transmission. Data compression will reduce the size of data to be processed and transmitted for saving mote´s limited resources. This paper proposes a new low cost, lossless, energy efficient algorithm called CoXoH (Combined XOR and Huffman) using number encoding for data compression which guarantees the compression of at-least 50%. However the simulation results show that up-to 98% compression can also be achieved which almost double the battery life. CoXoH is the combination of two operations XOR and Huffman Algorithm. XOR operation will reduce the data to 50% followed by Huffman compression which will further compress the data. The average compression ratio is from 70% to 90%.
Keywords :
data compression; encoding; wireless sensor networks; XOR and Huffman Algorithm; battery power; data encoding; data transmission; energy efficient algorithm; low cost energy efficient data compression; storage power; wireless sensor nodes; Encoding; Energy consumption; Wireless sensor networks; CoXoH (Combined XOR and Huffman); data compression; wireless sensor network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Networks and Information Technology (ICCNIT), 2011 International Conference on
Conference_Location :
Abbottabad
ISSN :
2223-6317
Print_ISBN :
978-1-61284-940-9
Type :
conf
DOI :
10.1109/ICCNIT.2011.6020922
Filename :
6020922
Link To Document :
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