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Reseach Article

Optimum Path Connectivity and Coverage in WSN to Increase Network Lifetime: A Review

by Kishu Pathania, Shilpa Mahajan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 18
Year of Publication: 2015
Authors: Kishu Pathania, Shilpa Mahajan

Kishu Pathania, Shilpa Mahajan . Optimum Path Connectivity and Coverage in WSN to Increase Network Lifetime: A Review. International Journal of Computer Applications. 115, 18 ( April 2015), 11-15. DOI=10.5120/20250-2618

@article{ 10.5120/20250-2618,
author = { Kishu Pathania, Shilpa Mahajan },
title = { Optimum Path Connectivity and Coverage in WSN to Increase Network Lifetime: A Review },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 18 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { },
doi = { 10.5120/20250-2618 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:55:12.585957+05:30
%A Kishu Pathania
%A Shilpa Mahajan
%T Optimum Path Connectivity and Coverage in WSN to Increase Network Lifetime: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 18
%P 11-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

As we all know, this age has become the age full of many different technologies which are helping each and every personality in their daily routine directly or indirectly. One of these technologies wireless sensor network has emerged in many areas and has gained a large popularity because of its great capabilities and functionalities. Wireless sensor network shortly named as WSN, is a network made by grouping some or many sensor nodes, technically known as motes, which are able to make communication with each other within the network range for performing many different tasks when needed and colleting the necessary information for achieving the purposed goal of that network and then forward that complete information to the base station of that network, technically called sink. In recent years WSN has made its presence in most of the areas for example military applications, medical applications and industrial areas. As WSN is being widely used but there is still many problems are present in WSN. Some problems of WSN are maximum target coverage problem, most energy efficient network and fault tolerant network. For effective communication it is necessary to cover most of the targets and also use optimum path to connect nodes so that network lifetime could be increased. Main concern of target coverage problem is the random deployment of the sensor network for supervising the specific targets for rising the life span of the network it also dictates that how much efficiently the monitoring and sensor tracking of any sensor network works. . To increase the lifetime of the network an optimal node deployment scheme is required that would minimize the cost of the network, reduce the energy consumption and resilient to node. In this paper we have proposed a system that can be used to solve all these issues after reviewing some previous researches in this field. In this work we will use a hybrid approach of merging some important algorithms and approaches to design a system that can solve these issues. Our system will work in two phases: First, Genetic Algorithm (GA) is applied to achieve optimum result and second, Support Vector Machine (SVM) is used to achieve a fault tolerant energy efficient network. SVM is used to detect intrusions like black hole attack and selective forwarding attack. In our approach both the phases will work in parallel for generating most efficient optimum path.

  1. "A Wireless Sensor Network- A Theoretical Review", Manoj Ahlawat, International Journal of Wired and Wireless Communications Vol. 1, Issue 2, April, 2013.
  2. "Energy Efficient Wireless Sensor Network", Mrs. Rakhi Khedikar, Dr. Avichal Kapur, Dr. M. D. Chawhan, 2014 International Conference on Electronic Systems, Signal Processing and Computing Technologies,978-1-4799-2102-7/14 © 2014 IEEE, DOI 10. 1109/ICESC. 2014. 14.
  3. "Coverage in Wireless Sensor Networks: A Survey", Raymond Mulligan, Habib M. Ammari, Network Protocols and Algorithms, 2010, Vol. 2, No. 2.
  4. "N-target Coverage in Wireless Sensor Network using DFS and Genetic Algorithms", Anudeep, Subhash Chander, International Journal of Scientific Engineering and Research (IJSER), Volume 1 Issue 2, October 2013.
  5. "Energy-Efficient Target Coverage in Wireless Sensor Networks Based on Modified Ant Colony Algorithm",Salma Begum, Nazma Tara, Sharmin Sultana, International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol. 1, No. 4, December 2010.
  6. "Maximizing Coverage in a Connected and K-Covered Wireless Sensor Network Using Genetic Algorithms", Tahir Emre Kalayc?, Kas?m Sinan Y?ld?r?m, Aybars Ugur,International Journal Of Applied Mathematics And Informatics, Issue 3, Volume 1, 2007.
  7. "Review on Coverage and Connectivity in Underwater Wireless Sensor Networks", Manisha Yadav, Dr. (Prof. ) Yusuf Mulge, International Journal of Computer Science & Engineering Technology (IJCSET), Vol. 4 No. 05 May 2013.
  8. "Connectivity Issue in Wireless Sensor Networks by Using Depth-First Search and Genetic Algorithm",GholamAli Yaghoubi, 2010 International Conference on Computational Intelligence and Communication Systems 978-0-7695-4254-6/10 © 2010 IEEE (pp 377- 381).
  9. "Malicious AODV: Implemen- tation and Analysis of Routing Attacks in MANETs", H. Ehsan and F. A. Khan, IEEE Trust, Security and Privacy in Computing and Communications Conference TRUSTCOM, Liverpool, 25-27 June 2012, pp. 1181-1187.
  10. "Research on Intrusion Detection Algorithm Based on Multi-Class SVM in Wireless Sensor Networks", Hangxia Zhou, Qian Liu, Chen Cui, Communications and Network, 2013, 5, 524-528.
  11. "Support Vector Machines Based on K Nearest Neighbor Algorithm for Outlier Detection in WSNs", S. Xu, C. Hu, L. Wang and G. Zhang, Proceedings of the 8th Wireless Communications, Networking and Mobile Com- puting International Conference WICOM, Shanghai, 21-23 September 2012, pp. 1-4.
  12. "Quarter-Sphere SVM: Attribute and Spatio-Temporal Correlations Based Outlier & Event Detection in Wireless Sensor Networks", N. Shahid, I. H. Naqvi and S. B. Qaisar, IEEE Wireless Communications and Networking Conference WCNC, Shanghai, 1-4 April 2012, pp. 2048-2053.
  13. "Security Enhancement in Wireless Sensor Networks Using Machine Learning," A. B. Raj, M. V. Ramesh, R. V. Kulkarni and T. Hema- latha, High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems HPCC-ICESS, Liverpool, 25-27 June 2012, pp. 1264- 1269.
Index Terms

Computer Science
Information Sciences


WSN Optimum path GA SVM (Support Vector Machine).