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Modern Query Optimization Technique (Nature Inspired) for Improving Energy Efficient Data Gathering and Processing in Wireless Sensor Networks

by Komalavalli Chakravarthi, Vijay Bhushan Aggarwal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 132 - Number 2
Year of Publication: 2015
Authors: Komalavalli Chakravarthi, Vijay Bhushan Aggarwal
10.5120/ijca2015907291

Komalavalli Chakravarthi, Vijay Bhushan Aggarwal . Modern Query Optimization Technique (Nature Inspired) for Improving Energy Efficient Data Gathering and Processing in Wireless Sensor Networks. International Journal of Computer Applications. 132, 2 ( December 2015), 24-30. DOI=10.5120/ijca2015907291

@article{ 10.5120/ijca2015907291,
author = { Komalavalli Chakravarthi, Vijay Bhushan Aggarwal },
title = { Modern Query Optimization Technique (Nature Inspired) for Improving Energy Efficient Data Gathering and Processing in Wireless Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { December 2015 },
volume = { 132 },
number = { 2 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = { 24-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume132/number2/23567-2015907291/ },
doi = { 10.5120/ijca2015907291 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:28:05.447059+05:30
%A Komalavalli Chakravarthi
%A Vijay Bhushan Aggarwal
%T Modern Query Optimization Technique (Nature Inspired) for Improving Energy Efficient Data Gathering and Processing in Wireless Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 132
%N 2
%P 24-30
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the main obstacles in wireless sensor networks is limited energy and memory constraints. In wireless sensor network, communication among the nodes is the most energy consuming activity and needs to be minimized in terms of data size and number of communications. To overcome these obstacles the earlier research works introduced several techniques and methods for query optimization. Data aggregation, efficient routing, secured data transmission, secured communication, storage maintenance and various heuristics are some of the approaches introduced earlier. The main objective of this work is to accomplish better efficiency in terms of energy and data storage maintenance. To achieve this goal, a Modern Query Optimization [MQO] technique is proposed in this paper. MQO works at three levels namely (i) Monitoring the query and the path (ii) Tracking the data along with the node information and (iii) Choosing optimum nodes in a best path for data gathering based on query’s lifetime. Artificial Immune System [6] algorithm along with the proposed three modifications is used to optimize the queries. The authors have simulated this modified algorithm in MatLab and the results show enhancement in efficiency.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Wireless Sensor Network Cluster Head Energy Artificial Immune System Multiquery Optimization

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