Data Size Reduction and Maximization of the Network Lifetime over Wireless Sensor Network

Conference proceedings article


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Publication Details

Author list: Kuthadi VM, Selvaraj R, Marwala T

Publisher: Springer Verlag (Germany)

Place: BERLIN

Publication year: 2016

Journal: Advances in Intelligent Systems and Computing (2194-5357)

Journal acronym: ADV INTELL SYST

Volume number: 433

Start page: 731

End page: 750

Number of pages: 20

ISBN: 978-81-322-2753-3

eISBN: 978-81-322-2755-7

ISSN: 2194-5357

eISSN: 2194-5365

Languages: English-Great Britain (EN-GB)


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Abstract

The main concept of this research is for increasing the network lifetime and decreases the data size over wireless sensor network. To perform this idea we proposed some novel technique which provides the reliable energy efficient routes and maximizing the network lifetime for finding the route that minimize the total energy for packet traversal. We also use the data compression model that reduce the size of data and joint balancing of nodes and optimize the dynamic compression for improving the lifetime of network. The data compression could be completed within some step, those are raw data could get broken in few branches and get compressed at distinct level of the compression, these compressed data could be decompressed at a certain level and again compressed with distinct level to forward directly or by using some base station. For transmitting the data to base station from the source node, every node has to be clustered and have to choose one cluster head in the group of every cluster, the CH (Cluster Head) is having the more energy in compared to the all other nodes. The CH (Cluster Head) is obtaining the entire message from the other neighbor's nodes and transmits it to the Base station. From source to destination data transmission, the nodes are searching shortest path that provide a high computation of complexity.


Keywords

Data compression, Dijkstra with AODV, Huffman coder, LEACH, Network Lifetime


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Last updated on 2021-07-05 at 03:59