Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Genetic algorithm based fault tolerant clustering in wireless sensor network

© The Institution of Engineering and Technology
Received 17/09/2016, Accepted 09/04/2017, Revised 11/03/2017, Published 11/05/2017

In wireless sensor network (WSN), during fault detection and recovery, average energy loss, and message loss occurs including the link failure. Also, the number of faulty nodes and the traffic overhead is increased with the size of WSN. In order to overcome this issue, in this study, a cluster-based fault tolerance technique using genetic algorithm is proposed. Here the network is clustered according to energy-efficient distance-based clustering algorithm. For each cluster head, a set of backup nodes are selected using genetic algorithm based on the sponsored coverage and residual energy parameters. This helps in detecting the faults occurring in cluster members and cluster heads. Simulation results show that the proposed technique minimises the energy loss and overhead.

Inspec keywords: energy conservation; fault diagnosis; telecommunication traffic; telecommunication power management; fault tolerance; genetic algorithms; wireless sensor networks; failure analysis; telecommunication network reliability; pattern clustering

Other keywords: fault recovery; WSN; message loss; traffic overhead; fault detection; cluster-based fault tolerance technique; backup nodes; residual energy parameters; average energy loss; wireless sensor network; genetic algorithm; energy-efficient distance-based clustering algorithm; cluster members; cluster head; link failure

Subjects: Reliability; Telecommunication systems (energy utilisation); Optimisation techniques; Wireless sensor networks

References

    1. 1)
      • 3. Babaie, S., Rezaie, A.R.: ‘DFDM: decentralized fault detection mechanism to improving fault management in wireless sensor networks’, In (Eds): ‘Digital information and communication technology and its applications’ (Springer, Berlin Heidelberg, 2011), pp. 685–692.
    2. 2)
      • 9. Bagheri, T.: ‘DFMC: decentralized fault management mechanism for cluster based wireless sensor networks’. Second Int. Conf. on IEEE Digital Information and Communication Technology and it's Applications (DICTAP), 2012, 2012, pp. 67–71.
    3. 3)
      • 10. Liu, T.H., Yi, S.C., Wang, X.W.: ‘A fault management protocol for low-energy and efficient wireless sensor networks’, J. Inf. Hiding Multimed. Signal Process., 2013, 4, (1), pp. 34–45.
    4. 4)
      • 8. Liu, H., Nayak, A., Stojmenovi, I.: ‘Fault-tolerant algorithms/protocols in wireless sensor networks’, In (Eds): ‘Guide to wireless sensor networks’ (Springer, London, 2009), pp. 261–291.
    5. 5)
      • 21. Azharuddin, M., Kuila, P., Jana, P.K.: ‘Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks’, Comput. Electr. Eng., 2015, 41, pp. 177–190.
    6. 6)
      • 15. Huang, J.M., Tai, S.C., Chen, K.H.: ‘CRINet: a secure and fault-tolerant data collection scheme using 3-way forwarding and group key management in wireless sensor networks’. IEEE Wireless Telecommunications Symp., 2009, WTS 2009, 2009, pp. 1–6.
    7. 7)
      • 14. Asim, M., Mokhtar, H., Merabti, M.: ‘A fault management architecture for wireless sensor network’. IEEE Int. Wireless Communications and Mobile Computing Conf., IWCMC'08, 2008, pp. 779–785.
    8. 8)
      • 6. Chang, F.C., Huang, H.C.: ‘A survey on intelligent sensor network and its applications’, J. Netw. Intell., 2016, 1, (1), pp. 1–15.
    9. 9)
      • 1. Choi, J., Hahn, J., Ha, R.: ‘A fault-tolerant adaptive node scheduling scheme for wireless sensor networks’, J. Inf. Sci. Eng., 2009, 25.
    10. 10)
      • 26. Guo, S., Zhong, Z., He, T.: ‘FIND: faulty node detection for wireless sensor networks’. Proc. of the 7th ACM Conf. on Embedded Networked Sensor Systems, 2009, pp. 253–266.
    11. 11)
      • 13. Nguyen, T.T., Dao, T.K., Horng, M.F., et al: ‘An energy-based cluster head selection algorithm to support long-lifetime in wireless sensor networks’, J. Netw. Intell., 2016, 1, (1), pp. 23–37.
    12. 12)
      • 19. Afsar, M.M.: ‘Maximizing the reliability of clustered sensor networks by a fault-tolerant service’. IEEE 27th Canadian Conf. on Electrical and Computer Engineering (CCECE), 2014, pp. 1–8.
    13. 13)
      • 12. Huang, R., Qiu, X., Ye, L.: ‘Probability-based fault detection in wireless sensor networks’. Int. Conf. on Network and Service Management (CNSM), 2010, October 2010, pp. 218–221.
    14. 14)
      • 7. Akbari, A., Beikmahdavi, N.: ‘Cluster-based and cellular approach to fault detection and recovery in wireless sensor networks’. Third Int. Conf. on IEEE Advanced Computer Theory and Engineering (ICACTE), 2010, 2010, vol. 5, pp. V5–148.
    15. 15)
      • 17. Yu, M., Mokhtar, H., Merabti, M.: ‘Self-managed fault management in wireless sensor networks’. Mobile Ubiquitous Computing, Systems, Services and Technologies, UBICOMM'08, 2008, pp. 13–18.
    16. 16)
      • 2. Saleh, I., El-Sayed, H., Eltoweissy, M.: ‘A fault tolerance management framework for wireless sensor networks’, IEEE Innov. Inf. Technol., 2006, pp. 1–5.
    17. 17)
      • 25. Mishra, S., Jena, L., Pradhan, A.: ‘Fault tolerance in wireless sensor networks’, Int. J. Adv. Res. Comput. Sci. Softw. Eng., 2012, 2, (10), pp. 146–153.
    18. 18)
      • 16. Man, K.L., Chen, C., Hughes, D.: ‘Decentralized fault detection and management for wireless sensor networks’. Fifth Int. Conf. on IEEE Future Information Technology (FutureTech), 2010, 2010, pp. 1–6.
    19. 19)
      • 24. Network Simulator: http:///www.isi.edu/nsnam/ns.
    20. 20)
      • 4. Huangshui, H., Guihe, Q.: ‘Fault management frameworks in wireless sensor networks’. Int. Conf. on IEEE Intelligent Computation Technology and Automation (ICICTA), 2011, 2011, vol. 2, pp. 1093–1096.
    21. 21)
      • 23. Ip, W., Wang, D., Cho, V.: ‘Aircraft ground service scheduling problems and their genetic algorithm with hybrid assignment and sequence encoding scheme’, IEEE Syst. J., 2013, 7, (4), pp. 649–657.
    22. 22)
      • 20. Shih, H.C., Ho, J.H., Liao, B.Y., et al: ‘Fault node recovery algorithm for a wireless sensor network’, IEEE Sens. J., 2013, 13, (7), pp. 2683–2689.
    23. 23)
      • 18. Abbasi, A.A., Younis, M.F., Baroudi, U.A.: ‘Recovering from a node failure in wireless sensor-actor networks with minimal topology changes’, IEEE Trans. Veh. Technol., 2013, 62, (1), pp. 256–271.
    24. 24)
      • 5. Rehana, R.T., Maneesha, R.V., Sangeeth, K.: ‘Fault tolerant clustering approaches in wireless sensor network for landslide area monitoring’. ICWN, 2008, pp. 107–113.
    25. 25)
      • 11. Babaie, S., Shojaiy, M.G.: ‘Improving fault management using voting mechanism in wireless sensor networks’. Int. Conf. on IEEE Computational Intelligence and Communication Networks (CICN), 2010, 2010, pp. 359–362.
    26. 26)
      • 22. Azharuddin, M., Kuila, P., Jana, P.K.: ‘A distributed fault-tolerant clustering algorithm for wireless sensor networks’. Proc. of Int. Conf. ICACCI 2013(IEEE Xplore), 2013, pp. 997–1002.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2016.1074
Loading

Related content

content/journals/10.1049/iet-com.2016.1074
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address