Energy Efficient Compression Technique in Wireless Sensor Network

Abstract

Abstract newline newlineIn a Wireless sensor network sensor nodes are organize in nonflexible physical field, utilized for physically monitoring the incident like temperature, vibrations, humidity, seismic events, etc. Generally, a node is small equipment that has a sensor unit to sensed data from physical close by area, a limited computing unit as well as storage of data, and transmission media is also wireless for communication and a small power unit. The power units mainly have a small battery with a restricted power and difficult to recharge or replace, as sensor nodes might be organized in a unfriendly or unpractical situation. Transmission of sensed data requires more energy as comparison to processing of data. newlineMany researchers have proposed various energy efficient schemes to increase the efficiency of network. With compression we can solve the problem of energy consumption and increase the lifetime of sensor network also. Researcher has proposed various compression algorithms. K-RLE is one of the popular algorithm proposed by Eug`ene Pamba Capo-Chichi, Herv´e Guyennet et al. enhancement of RLE With k parameter to control the compression ratio. K-RLE has efficiently increase the compression but it does not deals with redundant data problem in sensor nodes. To overcome this problem we have proposed DK-RLE and NK-RLE algorithm .In our work we do focus on data duplicity, compression ratio and energy efficiency in WSN . Various existing schemes conversed in this literature review are principal component analysis based schemes for mathematically minimizing only. Though, these schemes are too rigorous to be used for sensor nodes, As increase overhead computation memory necessities and lead to extra power utilization for data transmission from node to cluster head and further to base station .Though there is trade-off among power utilization and mathematically minimization or compression attained, there is a requirement of light weight scheme that can effectively reduces the load of node as well as cluster head we propose Nov