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Swarm Intelligence-based Partitioned Recovery in Wireless Sensor Networks

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The failure rate of sensor nodes in Heterogeneous Wireless Sensor Networks is high due to the use of low battery-powered sensor nodes in a hostile environment. Networks of this kind become non-operational and turn into disjoint segmented networks due to large-scale failures of sensor nodes. This may require the placement of additional highpower relay nodes. In this paper, we propose a network partition recovery solution called Grey Wolf, which is an optimizer algorithm for repairing segmented heterogeneous wireless sensor networks. The proposed solution provides not only strong bi-connectivity in the damaged area, but also distributes traffic load among the multiple deployed nodes to enhance the repaired network’s lifetime. The experiment results show that the Grey Wolf algorithm offers a considerable performance advantage over other state-of-the-art approaches.
Rocznik
Tom
Strony
70--81
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
autor
  • Department of Computer Engineering, National Institute of Technology Kurukshetra, Haryana, India
autor
  • Department of Computer Engineering, National Institute of Technology Kurukshetra, Haryana, India
Bibliografia
  • [1] V. Ranga, M. Dave, and A. K. Verma, „Network partitioning recovery mechanisms in WSANs: A survey", Wireless Personal Commun., vol. 72, no. 2, pp. 857-917, 2013 (doi: 10.1007/s11277-013-1046-7).
  • [2] V. Ranga, M. Dave, and A. K. Verma, „Relay node placement for lost connectivity restoration in partitioned wireless sensor networks", in Proc. Int. Conf. on Electron. and Commun. Syst. ECS 2015, Bacelona, Spain, 2015, pp. 170-175.
  • [3] V. Ranga, M. Dave, and A. K. Verma, „Relay node placement to heal partitioned wireless sensor networks", J. of Comp. & Elec. Engin., vol. 48, no. C, pp. 371-388, 2015 (doi: 10.1016/j.compeleceng.2015.09.014).
  • [4] G. Kumar and V. Ranga, „Meta-heuristics for relay node placement problem in wireless sensor networks", in Proc. 4th Int. Conf. on Parallel, Distrib. and Grid Comput. PDGC 2016, Waknaghat, India, 2016, pp. 375-380 (doi: 10.1109/pdgc.2016.7913180).
  • [5] J. Kennedy, „Particle swarm optimization", in Proc. of Int. Conf. on Neural Netw. ICNN'95, Perth, WA, Australia, 1995, pp. 1942-1948 (doi: 10.1109/ICNN.1995.488968).
  • [6] M. Dorigo, M. Birattari, and T. Stutzle, „Ant colony optimization", IEEE Comput. Intell. Mag., vol. 1, no. 4, pp. 28-39, 2006 (doi: 10.1109/MCI.2006.329691).
  • [7] E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm Intelligence: From Natural to Artificial Systems, 1st ed. Oxford University Press, 1999 (ISBN: 978-0195131598).
  • [8] S. Mirjalili, S. M. Mirjalili, and A. Lewis, „Grey wolf optimizer", Adv. in Engin. Software, vol. 69, pp. 46-61, 2014 (doi: 10.1016/j.advengsoft.2013.12.007).
  • [9] S. Lee and M. Younis, „Optimized relay node placement for connecting disjoint wireless sensor networks", Comp. Netw., vol. 56, no. 12, pp. 2788-2804, 2012 (doi: 10.1016/j.comnet.2012.04.019).
  • [10] J. M. Lanza-Gutierrez and J. A. Gomez-Pulido, „Assuming multiobjective metaheuristics to solve a three-objective optimisation problem for relay node deployment in wireless sensor networks", Appl. Soft Comput., vol. 30, no. C, pp. 675-687, 2015 (doi: 10.1016/j.asoc.2015.01.051).
  • [11] C. Ma, W. Liang, M. Zheng, and H. Sharif, „A connectivity-aware approximation algorithm for relay node placement in wireless sensor networks", IEEE Sensors J., vol. 16, no. 2, pp. 515-528, 2016 (doi: 10.1109/JSEN.2015.2456931).
  • [12] C. Zhao and P. Chen, „Particle swarm optimization for optimal deployment of relay nodes in hybrid sensor networks", in IEEE Congr. on Evolut. Comput. CEC 2007, Singapore, 2007, pp. 3316-3320 (doi: 10.1109/CEC.2007.4424899).
  • [13] E. L. Lloyd and G. Xue, „Relay node placement in wireless sensor networks", IEEE Trans. on Computers, vol. 56, no. 1, pp. 134-138, 2007 (doi: 10.1109/TC.2007.250629).
  • [14] I. F. Senturk, S. Yilmaz, and K. Akkaya, „A game-theoretic approach to connectivity restoration in wireless sensor and actor networks", in Proc. IEEE Int. Conf. on Commun. ICC 2012, Ottawa, ON, Canada, 2012, pp. 7110-1714 (doi: 10.1109/ICC.2012.6364848).
  • [15] P. Basu and J. Redi, „Movement control algorithms for realization of fault-tolerant ad hoc robot networks", IEEE Network, vol. 18, no. 4, pp. 36-44, 2004 (doi: 10.1109/MNET.2004.1316760).
  • [16] A. A. Abbasi, M. Younis, and K. Akkaya, „Movement-assisted connectivity restoration in wireless sensor and actor networks", IEEE Trans. on Parallel and Distrib. Syst., vol. 20, no. 9, pp. 1366-1379, 2009 (doi: 10.1109/TPDS.2008.246).
  • [17] K. Akkaya, F. Senel, A. Thimmapuram, and S. Uludag, „Distributed recovery from network partitioning in movable sensor/actor networks via controlled mobility", IEEE Trans. on Computers, vol. 59, no. 2, pp. 258-271, 2010 (doi: 10.1109/TC.2009.120).
  • [18] W. Wang, V. Srinivasan, and K.-C. Chua, „Using mobile relays to prolong the lifetime of wireless sensor networks", in Proc. 11th Ann. Int. Conf. on Mob. Comput. and Network. MobiCom 2005, Cologne, Germany, 2005, pp. 270-283 (doi: 10.1145/1080829.1080858).
  • [19] M. Y. Sir, I. F. Senturk, E. Sisikoglu, and K. Akkaya, „An optimization-based approach for connecting partitioned mobile sensor/actuator networks", in Proc. IEEE Conf. on Comp. Commun. Worksh. INFOCOM WKSHPS 2011, Shanghai, China, 2011, pp. 525-530 (doi: 10.1109/INFCOMW.2011.5928869).
  • [20] R. C. Shah, S. Roy, S. Jain, and W. Brunette, „Data MULEs: Modeling a three-tier architecture for sparse sensor networks", in Proc. of 1st IEEE Int. Worksh. on Sensor Netw. Protocols and Appl., Anchorage, AK, USA, 2003 (doi: 10.1109/SNPA.2003.1203354).
  • [21] G. Wang, G. Cao, T. La Porta, and W. Zhang, „Sensor relocation in mobile sensor networks", in Proc. IEEE 24th Ann. Joint Conf. of the IEEE Comp. and Commun. Soc. INFOCOM 2005, Miami, FL, USA, 2005, vol. 4, pp. 2302-2312 (doi: 10.1109/INFCOM.2005.1498517).
  • [22] C. Muro, R. Escobedo, L. Spector, and R. Coppinger, „Wolfpack (Canis lupus) hunting strategies emerge from simple rules in computational simulations", Behavioural Processes, vol. 88, no. 3, pp. 192-197, 2011 (doi: 10.1016/j.beproc.2011.09.006).
  • [23] R. L. Graham, „An efficient algorithm for determining the convex hull of a finite planar set", Inform. Process. Lett., vol 1, no. 4, pp. 132-133, 1972 (doi: 10.1016/0020-0190(72)90045-2).
  • [24] X. Cheng, D.-Z. Du, L. Wang, and B. Xu, „Relay sensor placement in wireless sensor networks", Wireless Networks, vol. 14, no. 3, pp. 347-355, 2008 (doi: 10.1007/s11276-006-0724-8).
  • [25] D. Yang, S. Misra, X. Fang, G. Xue, and J. Zhang, „Two-tiered constrained relay node placement in wireless sensor networks: Efficient approximations", in Proc. 7th Ann. IEEE Commun. Soc. Conf. on Sensor Mesh and Ad Hoc Commun. and Netw. SECON 2010, Boston, MA, USA, 2010, pp. 1-9 (doi: 10.1109/SECON.2010.5508241).
  • [26] G. Robins and A. Zelikovsky, „Tighter bounds for graph Steiner tree approximation", SIAM J. on Discrete Mathem., vol. 19, no. 1, pp. 122-134, 2005 (doi: 10.1137/S0895480101393155).
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e6403316-5817-44f8-9060-85236cd5b978
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