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Modified Chorological Coded Data Compression Methodology for Wireless Sensor Networks
Author(s) -
S. Jancy,
Suji Helen,
Mercy Paul Selven,
A. Viji Amutha Mary,
M. D. Antopraveena,
M. S. Roobini
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1770/1/012026
Subject(s) - computer science , data compression , compression (physics) , sequence (biology) , wireless sensor network , compression ratio , algorithm , computer hardware , engineering , computer network , materials science , biology , automotive engineering , composite material , genetics , internal combustion engine
Wireless Sensor Network (WSN) is a fast evolving current technology which is being employed in various applications. Despite its wide usage, WSNs have a few challenges to overcome to be called as an ideal technology. Some of the challenges are battery life time, memory storage and deployment issues. Batteries are the primary source of power supply to WSN and one of the major challenges is the energy constraint. This paper aims to propose a few techniques to better the energy efficiency of the sensor networks by saving sensor energy using data compression methodology. In this paper, a modified chorological coded data compression methodology is proposed (MCDC). This algorithm deals with assigning the sequence value to the given input information. If the assigned sequence value is a double digit number, it is converted in to single digit number. Double digit numbers and single digit numbers are combined. Separate location tables are generated for all double digit and single digit numbers. This procedure continues until all the sequence values are changed in to single digit number. Then the final single digit is assign with an equivalent Sequence Code (SC). MCDC algorithm is compared with DELTA compression and RUNLENGTH compression and a better compression ratio was achieved when compared with DELTA compression and RUNLENGTH compression algorithms.

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