Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
Limited capacity and limited power efficiency are considered to be the main drawback of sensors. To improve an energy efficiency of sensor is the main focus of most of the researches. Medium access control and routing protocol are the major techniques available to improve the energy efficiency of sensors. Data compression techniques are discussed in this study as a method for improving the energy efficiency of sensors through saving processing time and saving space. Genetic algorithm for data compression is proposed in this study. The assessment of SDC (Sequence Statistical Code) and FOST (First Order Static Code) are assigned as the population. The population is found followed by evaluation, selection and generation of random number. The probability of the proposed algorithm is the random number. Once, the random number is generated, Huffman algorithm is applied. The finally achieve Huffman code in cumulative probability is the final output which is the compressed data. Processing time and computation process is lesser than the Huffman algorithm with these proposed techniques.
How to cite this article:
S. Jancy and C. Jayakumar. Sequence Statistical Code Based Data Compression Model Using
Genetic Algorithm for Wireless Sensor Networks.
DOI: https://doi.org/10.36478/jeasci.2019.831.836
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2019.831.836