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Successive Convex Approximation for Efficient Energy Utilisation in Wireless Sensor Network

P. Bagyalakshmi1 , R. Anitha2

  1. Department of Computer Science, Bharathiar University, Coimbatore, India.
  2. Department of MCA, Muthayammal Engineering College, Rasipuram, India.

Correspondence should be addressed to: gacbagyalakshmi@gmail.com, .

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-6 , Page no. 159-163, Jun-2017

Online published on Jun 30, 2017

Copyright © P. Bagyalakshmi, R. Anitha . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: P. Bagyalakshmi, R. Anitha, “Successive Convex Approximation for Efficient Energy Utilisation in Wireless Sensor Network,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.159-163, 2017.

MLA Style Citation: P. Bagyalakshmi, R. Anitha "Successive Convex Approximation for Efficient Energy Utilisation in Wireless Sensor Network." International Journal of Computer Sciences and Engineering 5.6 (2017): 159-163.

APA Style Citation: P. Bagyalakshmi, R. Anitha, (2017). Successive Convex Approximation for Efficient Energy Utilisation in Wireless Sensor Network. International Journal of Computer Sciences and Engineering, 5(6), 159-163.

BibTex Style Citation:
@article{Bagyalakshmi_2017,
author = {P. Bagyalakshmi, R. Anitha},
title = {Successive Convex Approximation for Efficient Energy Utilisation in Wireless Sensor Network},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2017},
volume = {5},
Issue = {6},
month = {6},
year = {2017},
issn = {2347-2693},
pages = {159-163},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1319},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1319
TI - Successive Convex Approximation for Efficient Energy Utilisation in Wireless Sensor Network
T2 - International Journal of Computer Sciences and Engineering
AU - P. Bagyalakshmi, R. Anitha
PY - 2017
DA - 2017/06/30
PB - IJCSE, Indore, INDIA
SP - 159-163
IS - 6
VL - 5
SN - 2347-2693
ER -

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Abstract

In traditional wireless sensor networks all the nodes communicate data with the central node. The path for data transmission is mainly the AODV protocol used. Each time the nodes communicate with each other before data transmission and the shortest path is selected to enable minimizing the battery usage in data transmission. This type of protocol uses considerable energy of all nodes in the network and the network traffic is increased at times depending on the number of nodes in the network. Convex approximation is introduced for overcoming this problem. In this method the nodes are grouped. Every group has a group head. Which determines the path for data transmission, also holding all the data about the nodes present under it. The group heads also communicate with other group heads to determine the path for data transmission.

Key-Words / Index Term

Convex Approximation, Network Life Time, Data path selection

References

[1]. A. Garg, N. Batra, I. Taneja, A. Bhatnagar, A. Yadav, S. Kumar, "Cluster Formation based Comparison of Genetic Algorithm and Particle swarm Optimization Algorithm in Wireless Sensor Network", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.14-20, 2017.
[2]. Jinghon. Guo; J. Yao; T. Song; J. Hu; M. Liu “A routing algorithm to long lifetime network for the intelligent power distribution network in smart grid”, IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 19 – 20 Dec. 2015, pp: 1077 – 1082.
[3]. S. Sharma, D. Kumar and K. Kishore, "Wireless Sensor Networks- A Review on Topologies and Node Architecture", International Journal of Computer Sciences and Engineering, Vol.1, Issue.2, pp.19-25, 2013.
[4]. Aditya Singh Mandloi and Vinita Choudhary, "An Efficient Clustering Technique for Deterministically Deployed Wireless Sensor Networks", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue.1, pp.6-10, 2013.
[5]. X. Chen; C. He; L. Jiang “The tradeoff between transmission cost and network lifetime of data gathering tree in Wireless Sensor Networks”, IEEE International Conference on Communications (ICC), 9 – 13 June 2013, pp: 1790 – 1794.
[6]. P. Wang; C. Li; J. Zheng “Combined Data Aggregation and Encryption Using Clustered Slepian-Wolf Coding for Wireless Sensor Networks”, IEEE Global Telecommunications Conference GLOBECOM `07, 26 – 30 Nov. 2007, pp: 920 – 925.
[7]. T. D. Ramotsoela; G. P. Hancke “Data aggregation using Homomorphic Encryption in Wireless Sensor Networks”, International Conference on Information Security for South Africa (ISSA), 16 – 18 Sept. 2011, pp: 2983 – 2986.
[8]. G.R. Shahmohammadi, Kh.Mohammadi, "Key Management in Hierarchical Sensor Networks Using Improved Evolutionary Algorithm", International Journal of Scientific Research in Network Security and Communication, Vol.4, Issue.2, pp.5-14, 2016.
[9]. G. Rohini “Dynamic router selection and encryption for data secure in Wireless Sensor Networks”, International Conference on Information Communication and Embedded Systems (ICICES) 21 – 22 Feb. 2013 pp: 256 – 259.
[10]. M. Abdallah; J. Pogge; A. Simpson “Intrinsic Cognitive Network Addressing”, IEEE International Conference on Long Island Systems, Applications and Technology Conference (LISAT), 3 May 2013 pp: 1 – 4.