TY  - JOUR
T1  - Sequence Statistical Code Based Data Compression Model Using
Genetic Algorithm for Wireless Sensor Networks
AU - Jancy, S. AU - Jayakumar, C. 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 3
SP  - 831
EP  - 836
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.831.836
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.831.836
KW  - Data compression
KW  -wireless sensor network
KW  -Huffman algorithm
KW  -Genetic algorithm
KW  -SDC
KW  -FOST
AB  - 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.
ER  -