ICTACT Journal on Communication Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Swarm Optimization bsed Imposter Nodes and Resource Limitation Aware Node Failure Detection


Affiliations
1 Department of Computer Science, Providence College for Women, India
     

   Subscribe/Renew Journal


This research work studies about node failures, which can be prevented pretty good by providing the necessary resources rather than by establishing a route path again. This is done by clustering the mobile nodes in accordance with the on node significance level like it is done in the earlier work and the resources among the cluster members are shared with one another to guarantee that sufficient resources are made available. The cluster is established using the Fuzzy K-means clustering technique. The cluster head is accountable for selecting those clusters members, which can share their resources with one another whereas in this technical work, the cluster head selection is carried out with the help of Cuckoo Search based Hill climbing algorithm (CS-HC). Also, to prevent the wrong information on the node failure being spread by the imposter nodes acting as credible neighbour nodes, this work presents the Imposter Node Detection algorithm. This technique guarantees the optimum detection and suppression of node failures occurring in the mobile wireless networks by presenting effective methodologies. The overall process of realization of the proposed research approach is carried out in the NS2 simulation environment, which shows that the proposed technique ensures improved performance compared to the available research approaches.

Keywords

Wireless Sensor Network, Clustering, Node Formation, Fuzzy KMeans Clustering, Cuckoo Search Algorithm, Hill Climbing Approach.
Subscription Login to verify subscription
User
Notifications
Font Size

  • J. Yick, B. Mukherjee and D. Ghosal, “Wireless Sensor Network Survey”, Computer Networks, Vol. 52, No. 12, pp. 2292-2330, 2008.

  • Z. Rezaei and S. Mobininejad, “Energy Saving in Wireless Sensor Networks”, International Journal of Computer Science and Engineering Survey, Vol. 3, No. 1, pp. 23-37, 2012.

  • M. Parvin, E. Jafari and R. Azizi, “A Multi-Armed Bandit Problem-Based Target Coverage Protocol for Wireless Sensor Network, Computing”, Proceedings of International Conference on Communication and Networking Technologies, pp. 1-5, 2014

  • S. Getsy S.R. Kalaiarasi, S. Neelavathy Pari and D. Sridharan, “Energy Efficient Clustering and Routing in Mobile Wireless Sensor Network”, International Journal of Wireless and Mobile Networks, Vol. 2, No. 1, pp. 106-114, 2010.

  • A.A. Abbasi and M. Younis, “A Survey on Clustering Algorithms for Wireless Sensor Networks”, Computer Communication, Vol. 30, pp. 2826-2841, 2007.

  • Y.J. Oh and K.W. Lee, “A Clustering Algorithm based on Mobility Properties in Mobile Ad Hoc Networks”, International Journal of Distributed Sensor Networks, Vol. 11, No. 6, pp. 1-12, 2015.

  • X.A. Shiny and R.J. Kannan, “Energy Efficient Clustering Protocol using Self Organizing Map in MANET”, Indian Journal of Science and Technology, Vol. 8, No. 28, pp. 23-36, 2015.

  • M. Alinci, E. Spaho, A. Lala and V. Kolici, “Clustering Algorithms in MANETs: A Review”, Proceedings of IEEE International Conference on Complex, Intelligent, and Software Intensive Systems, pp. 330-335, 2015.

  • E.A. Alrashed and M.H. Karaata, “Imposter Detection in Mobile Wireless Sensor Networks”, International Journal of Computer and Communication Engineering, Vol. 3, No. 6, pp. 1-14, 2014.

  • T. Dimitriou, E.A. Alrashed, M.H. Karaata and A. Hamdan, “Imposter Detection for Replication Attacks in Mobile Sensor Networks”, Computer Networks, Vol. 108, pp. 210-222, 2016.

  • I. Bhardwaj, N.D. Londhe and S.K. Kopparapu, “Study of Imposter Attacks on Novel Fingerprint Dynamics based Verification System”, IEEE Access, Vol. 5, pp. 595-606, 2017.

  • W.T. Zhu, J. Zhou, R.H. Deng and F. Bao, “Detecting Node Replication Attacks in Wireless Sensor Networks: A Survey”, Journal of Network and Computer Applications, Vol. 35, No. 3, pp. 1022-1034, 2012.

  • A. Becher, Z. Benenson and M. Dornseif, “Tampering with Motes: Real-World Physical Attacks on Wireless Sensor Networks”, Proceedings of International Conference on Security in Pervasive Computing, pp. 104-118, 2006.

  • M.A. Simplicio, P.S. Barreto, C.B. Margi and T.C. Carvalho, “A Survey on Key Management Mechanisms for Distributed Wireless Sensor Networks”, Computer Networks, Vol. 54, No. 15, pp. 2591-2612, 2010.

  • D. Wallner, E. Harder and R. Agee, “Key Management for Multicast: Issues and Architectures”, RFC Editor, 1999.

  • X.S. Yang and S. Deb, “Cuckoo Search: Recent Advances and Applications”, Neural Computing and Applications, Vol. 24, No. 1, pp. 169-174, 2014.

  • X.S. Yang and S. Deb, “Cuckoo Search Via Levy Flights”, Proceedings of World Congress on Nature and Biologically Inspired Computing, pp. 210-214, 2009.


Abstract Views: 183

PDF Views: 0




  • Swarm Optimization bsed Imposter Nodes and Resource Limitation Aware Node Failure Detection

Abstract Views: 183  |  PDF Views: 0

Authors

K. B. Manikandan
Department of Computer Science, Providence College for Women, India

Abstract


This research work studies about node failures, which can be prevented pretty good by providing the necessary resources rather than by establishing a route path again. This is done by clustering the mobile nodes in accordance with the on node significance level like it is done in the earlier work and the resources among the cluster members are shared with one another to guarantee that sufficient resources are made available. The cluster is established using the Fuzzy K-means clustering technique. The cluster head is accountable for selecting those clusters members, which can share their resources with one another whereas in this technical work, the cluster head selection is carried out with the help of Cuckoo Search based Hill climbing algorithm (CS-HC). Also, to prevent the wrong information on the node failure being spread by the imposter nodes acting as credible neighbour nodes, this work presents the Imposter Node Detection algorithm. This technique guarantees the optimum detection and suppression of node failures occurring in the mobile wireless networks by presenting effective methodologies. The overall process of realization of the proposed research approach is carried out in the NS2 simulation environment, which shows that the proposed technique ensures improved performance compared to the available research approaches.

Keywords


Wireless Sensor Network, Clustering, Node Formation, Fuzzy KMeans Clustering, Cuckoo Search Algorithm, Hill Climbing Approach.

References