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

access icon free Self-stabilising hybrid connectivity control protocol for WSNs

In this study, the authors address the problem of combining hierarchical and flat techniques to construct and maintain nodes’ connectivity as well as links’ symmetry (bidirectionality) in a wireless sensor network (WSN) comprising static nodes. They propose a localised and asynchronous self-stabilising hybrid message passing a solution that seamlessly merges three well known connectivity control techniques for such ad hoc networks, namely k-hop clustering , power control (transmission range adjustment) and sleep/wake scheduling. Their stigmergy-based strategy (i.e. inspired from ants’ pheromone-based communication, division of labour and swarming behaviours) allows a WSN to simultaneously cope with issues such as scalability, fault tolerance, transmission range minimisation, energy hole problem (i.e. premature node deaths in the vicinity of the sink), channel overhearing and signalisation reduction. To the best of their knowledge, such a solution does not exist in the literature. The few self-stabilising hybrid connectivity control protocols currently proposed use only two of the above-mentioned techniques. The authors formally prove the correctness of their scheme and its self-stabilisation property under an unfair distributed daemon. Simulation results show that the proposed scheme has a low average convergence time, is energy efficient and can prolong network lifetime.

References

    1. 1)
      • 20. Mir, Z.H., Ko, Y.-B.: ‘Collaborative topology control for many-to-one communications in wireless sensor networks’, IEEE Access., 2017, 5, pp. 1592715941.
    2. 2)
      • 6. Rossi, P.S., Ciuonzo, D., Kansanen, K., et al: ‘On energy detection for MIMO decision fusion in wireless sensor networks over NLOS fading’, IEEE Commun. Lett., 2015, 19, (2), pp. 303306.
    3. 3)
      • 50. Rahman, A.U., Alharby, A., Hasbullah, H., et al: ‘Corona based deployment strategies in wireless sensor network: a survey’, J. Netw. Comput. Appl., 2016, 64, pp. 176193.
    4. 4)
      • 49. Mahendrababu, K., Joshitha, K.L.: ‘A solution to energy hole problem in wireless sensor networks using WITRICITY’. Proc. Int. Conf. Inf. Communication and Embedded Systems (ICICES2014), Chennai, India, February 2014, pp. 16.
    5. 5)
      • 7. Ciuonzo, D., Rossi, P.S.: ‘Distributed detection of a non-cooperative target via generalized locally-optimum approaches’, Inf. Fusion, 2017, 36, pp. 261274.
    6. 6)
      • 1. Selmic, R.R., Phoha, V.V., Serwadda, A.: ‘WSN platforms’, in Selmic, R.R., Phoha, V.V., Serwadda, A. (Eds.): ‘Wireless sensor networks: security, coverage, and localization’ (Springer International Publishing, Cham, 2016), pp. 197215.
    7. 7)
      • 61. Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: ‘An application-specific protocol architecture for wireless microsensor networks’, IEEE Trans. Wirel. Commun., 2002, 1, (4), pp. 660670.
    8. 8)
      • 4. Huang, Y., Martnez, J.-F., Sendra, J., et al: ‘Resilient wireless sensor networks using topology control: a review’, Sensors, 2015, 15, (10), pp. 2473524770.
    9. 9)
      • 57. Even, S., Itai, A., Shamir, A.: ‘On the complexity of timetable and multicommodity flow problems’, SIAM J. Comput., 1976, 5, (4), pp. 691703.
    10. 10)
      • 48. Asharioun, H., Asadollahi, H., Wan, T.-C., et al: ‘A survey on analytical modeling and mitigation techniques for the energy hole problem in corona-based wireless sensor network’, Wirel. Pers. Commun., 2014, 81, (1), pp. 161187.
    11. 11)
      • 40. Ba, M.: ‘Vers une structuration auto-stabilisante des réseaux ad hoc: cas des réseaux de capteurs sans fil’, PhD thesis, Université de Reims Champagne-Ardenne, 2014.
    12. 12)
      • 27. Afsar, M.M., Tayarani-N, M.-H.: ‘Clustering in sensor networks: a literature survey’, J. Netw. Comput. Appl., 2014, 46, pp. 198226.
    13. 13)
      • 23. Datta, A.K., Devismes, S., Larmore, L.L.: ‘Self-stabilizing silent disjunction in an anonymous network’, Theor. Comput. Sci., 2017, 665, pp. 5172.
    14. 14)
      • 52. Grassé, P.-P.: ‘La reconstruction du nid et les coordinations interindividuelles chez Bellicositermes natalensis et Cubitermes sp. la théorie de la stigmergie: Essai d'interprétation du comportement des termites constructeurs’, Insectes Sociaux, 1959, 6, (1), pp. 4180.
    15. 15)
      • 8. Hamouda, E., Gerdes, J.: ‘Chapter 10: mobile wireless sensor networks: challenges and business applications’, in Mitton, N., Simplot-Ryl, D. (Eds.): ‘Wireless sensor and robot networks’ (World Scientific, Lille, 2014), pp. 249265.
    16. 16)
      • 13. Li, M., Li, Z., Vasilakos, A.V.: ‘‘A survey on topology control in wireless sensor networks: taxonomy, comparative study, and open issues’’, Proc. IEEE, 2013, 101, (12), pp. 25382557.
    17. 17)
      • 59. Varga, A.: 2016. Available at ‘https://omnetpp.org, accessed March 2016.
    18. 18)
      • 37. Erciyes, K.: ‘Self-stabilization’, in ‘Distributed graph algorithms for computer networks’ (Springer, London, 2013), pp. 97104.
    19. 19)
      • 14. Shahid, A., Qureshi, H.K.: ‘A survey on topology maintenance techniques to extend the lifetime of wireless sensor networks’, in Shaikh, F.K., Chowdhry, B.S., Zeadally, S., et al (Eds.): ‘Communications in computer and information science’ (Springer, Berlin, 2013), pp. 96107.
    20. 20)
      • 36. Dijkstra, E.W.: ‘Self-stabilizing systems in spite of distributed control’, Commun. ACM, 1974, 17, (11), pp. 643644.
    21. 21)
      • 16. Aziz, A.A., Sekercioglu, Y.A., Fitzpatrick, P., et al: ‘A survey on distributed topology control techniques for extending the lifetime of battery powered wireless sensor networks’, IEEE Commun. Surv. Tutor., 2013, 15, (1), pp. 121144.
    22. 22)
      • 31. Krishnan, R., Perumal, G.: ‘H2b2h protocol for addressing link failure in WSN’, Cluster Comput., 2017, pp. 110.
    23. 23)
      • 26. Pundir, P., Ramakrishna, G.: ‘On minimum average stretch spanning trees in grid graphs’, Electron. Notes Discrete Math., 2016, 55, pp. 131134.
    24. 24)
      • 46. Afsar, M.M., Tayarani-N., M.-H.: ‘A novel energy-efficient and distance-based clustering approach for wireless sensor networks’, in Snasel, V., et al (Ed.): ‘Advances in intelligent systems and computing’ (Springer, Cham, 2013), pp. 177186.
    25. 25)
      • 63. Baccour, N., Koubâa, A., Noda, C., et al: ‘Radio link quality estimation in low-power wireless networks’ (Springer International Publishing, London, 2013).
    26. 26)
      • 2. Younis, M., Senturk, I.F., Akkaya, K., et al: ‘Topology management techniques for tolerating node failures in wireless sensor networks: a survey’, Comput. Netw., 2014, 58, pp. 254283.
    27. 27)
      • 18. Xu, Z.-Y., Zhao, S.-G., Jing, Z.-J.: ‘A clustering sleep scheduling mechanism based on Sentinel nodes monitor for WSN’, Int. J. Smart Home, 2015, 9, (1), pp. 2332.
    28. 28)
      • 21. Dolev, S.: ‘Self-stabilization’ (The MIT Press, Cambridge, 2000).
    29. 29)
      • 47. Li, J., Mohapatra, P.: ‘Analytical modeling and mitigation techniques for the energy hole problem in sensor networks’, Pervasive Mob. Comput., 2007, 3, (3), pp. 233254.
    30. 30)
      • 45. Afsar, M., Tayarani-N., M.-H., Aziz, M.: ‘An adaptive competition-based clustering approach for wireless sensor networks’, Telecommun. Syst., 2015, 61, (1), pp. 181204.
    31. 31)
      • 19. Yetgin, H., Cheung, K.T.K., El-Hajjar, M., et al: ‘A survey of network lifetime maximization techniques in wireless sensor networks’, IEEE Commun. Surv. Tutor., 2017, 19, (2), pp. 828854.
    32. 32)
      • 58. Glover, F.: ‘Future paths for integer programming and links to artificial intelligence’, Comput. Oper. Res., 1986, 13, (5), pp. 533549.
    33. 33)
      • 43. Kuang, X.-H., Liu, L., Liu, Q., et al: ‘A clustering approach based on convergence degree chain for wireless sensor networks’, Secur. Commun. Netw., 2014, 8, (10), pp. 18781889.
    34. 34)
      • 39. Ba, M., Flauzac, O., Makhloufi, R., et al: ‘Fault-tolerant and energy-efficient generic clustering protocol for heterogeneous WSNs’, Int. J. Adv. Netw. Serv., 2013, 6, (3–4), pp. 235245.
    35. 35)
      • 35. Chen, H., Lv, Z., Tang, R., et al: ‘Clustering energy-efficient transmission protocol for wireless sensor networks based on ant colony path optimization’. Proc. Int. Conf. Computer, Information and Telecommunication Systems (CITS), Dalian, China, July 2017, pp. 1519.
    36. 36)
      • 17. Blin, L., Potop-Butucaru, M., Rovedakis, S.: ‘A super-stabilizing-approximation algorithm for dynamic Steiner trees’, Theor. Comput. Sci., 2013, 500, pp. 90112.
    37. 37)
      • 28. Bhowmik, S., Basu, D., Giri, C.: k-Fault tolerant topology control in wireless sensor network’, in Thampi, S.M., et al (Eds.): ‘Advances in intelligent systems and computing’, (Springer International Publishing, Cham, 2014), pp. 371377.
    38. 38)
      • 34. Oladimeji, M.O., Turkey, M., Dudley, S.: ‘HACH: heuristic algorithm for clustering hierarchy protocol in wireless sensor networks’, Appl. Soft Comput., 2017, 55, pp. 452461.
    39. 39)
      • 30. Mazumdar, N., Om, H.: ‘A distributed fault-tolerant multi-objective clustering algorithm for wireless sensor networks’, in Nath, V. (Ed.): ‘Lecture notes in electrical engineering’ (Springer, Singapore, 2017), pp. 125137.
    40. 40)
      • 10. Rashid, B., Rehmani, M.H.: ‘Applications of wireless sensor networks for urban areas: a survey’, J. Netw. Comput. Appl., 2016, 60, pp. 192219.
    41. 41)
      • 3. Kakamanshadi, G., Gupta, S., Singh, S.: ‘A survey on fault tolerance techniques in wireless sensor networks’. Proc. Int. Conf. Green Computing and Internet of Things (ICGCIoT), Noida, India, October 2015, pp. 168173.
    42. 42)
      • 25. Elkin, M., Emek, Y., Spielman, D.A., et al: ‘Lower-stretch spanning trees’, SIAM J. Comput., 2008, 38, (2), pp. 608628.
    43. 43)
      • 38. Ba, M., Flauzac, O., Haggar, B.S., et al: ‘Self-stabilizing k-hops clustering algorithm for wireless ad hoc networks’. Proc. Seventh Int. Conf. Ubiquitous Information Management and Communication – ICUIMC 13, Kota Kinabalu, Malaysia, January 2013, pp. 38:138:10.
    44. 44)
      • 9. Ojha, T., Misra, S., Raghuwanshi, N.S.: ‘Wireless sensor networks for agriculture: the state-of-the-art in practice and future challenges’, Comput. Electron. Agric., 2015, 118, pp. 6684.
    45. 45)
      • 24. Peleg, D.: ‘Low stretch spanning trees’, in Diks, K., et al (Eds.): ‘Lecture notes in computer science’ (Springer, Berlin, Heidelberg, 2002), pp. 6880.
    46. 46)
      • 12. Pule, M., Yahya, A., Chuma, J.: ‘Wireless sensor networks: a survey on monitoring water quality’, J. Appl. Res. Technol., 2017, 15, (6), pp. 562570.
    47. 47)
      • 64. Bas, C.U., Ergen, S.C.: ‘Spatio-temporal characteristics of link quality in wireless sensor networks’. Proc. IEEE Wireless Communications and Networking Conf. (WCNC), Shanghai, China, April 2012, pp. 11521157.
    48. 48)
      • 44. Boucetta, C., Idoudi, H., Saidane, L.A.: ‘Adaptive scheduling with fault tolerance for wireless sensor networks’. Proc. 81st Vehicular Technology Conf. (VTC Spring), Glasgow, UK, May 2015, pp. 15.
    49. 49)
      • 54. Khuong, A., Gautrais, J., Perna, A., et al: ‘Stigmergic construction and topochemical information shape ant nest architecture’, Proc. Natl. Acad. Sci., 2016, 113, (5), pp. 13031308.
    50. 50)
      • 22. Devismes, S., Ilcinkas, D., Johnen, C.: ‘Self-stabilizing disconnected components detection and rooted shortest-path tree maintenance in polynomial steps’. Proc. 20th Int. Conf. Principles of Distributed Systems (OPODIS 2016), Leibniz Int. Proc. Informatics (LIPIcs), Madrid, Spain, December 2016, pp. 10:110:16.
    51. 51)
      • 41. Guizani, B., Ayeb, B., Koukam, A.: ‘A stable k-hop clustering algorithm for routing in mobile ad hoc networks’. Proc. Int. Wireless Communications and Mobile Computing Conf. (IWCMC), Dubrovnik, Croatia, August 2015, pp. 659664.
    52. 52)
      • 51. Salehi_Panahi, M., Abbaszadeh, M.: ‘Proposing a method to solve energy hole problem in wireless sensor networks’, Alexandria Eng. J., 2017.
    53. 53)
      • 53. Dorigo, M., Bonabeau, E., Theraulaz, G.: ‘Ant algorithms and stigmergy’, Future Gener. Comput. Syst., 2000, 16, (8), pp. 851871.
    54. 54)
      • 33. Zebbane, B., Chenait, M., Badache, N.: ‘A group-based energy-saving algorithm for sleep/wake scheduling and topology control in wireless sensor networks’, Wirel. Pers. Commun., 2015, 84, (2), pp. 959983.
    55. 55)
      • 5. Rossi, P.S., Ciuonzo, D., Ekman, T.: ‘HMM-based decision fusion in wireless sensor networks with noncoherent multiple access’, IEEE Commun. Lett., 2015, 19, (5), pp. 871874.
    56. 56)
      • 56. Miyajima, K., Sakuragawa, T.: ‘Continuous and robust clustering coefficients for weighted and directed networks’, 2014.
    57. 57)
      • 29. Singh, S.K., Kumar, P., Singh, J.P.: ‘A survey on successors of LEACH protocol’, IEEE. Access., 2017, 5, pp. 42984328.
    58. 58)
      • 15. Mao, G.: ‘Connectivity of dynamic networks’, ‘Connectivity of communication networks’, (Springer International Publishing, Cham, 2017), pp. 201211.
    59. 59)
      • 62. Afsar, M.: ‘A comprehensive fault-tolerant framework for wireless sensor networks’, Secur. Commun. Netw., 2015, 8, (17), pp. 32473261.
    60. 60)
      • 32. Tseng, C.C., Ting, K.C., Wang, H.C., et al: ‘Construction and analysis of a green clustered architecture for RNG-based wireless ad hoc networks’, Int. J. Ad Hoc Ubiquit. Comput., 2015, 19, (1/2), pp. 6274.
    61. 61)
      • 11. Fahmy, H.M.A.: ‘WSNs applications’, in (Eds.): ‘Wireless sensor networks: concepts, applications, experimentation and analysis’ (Springer, Singapore, 2016), pp. 69213.
    62. 62)
      • 42. Ben-Othman, J., Bessaoud, K., Bui, A., et al: ‘Self-stabilizing algorithm for efficient topology control in wireless sensor networks’, J. Comput. Sci., 2013, 4, (4), pp. 199208.
    63. 63)
      • 55. Jain, A., Reddy, B.: ‘Sink as cluster head: an energy efficient clustering method for wireless sensor networks’. Proc. Int. Conf. Data Mining and Intelligent Computing (ICDMIC), New Delhi, India, September 2014, pp. 16.
    64. 64)
      • 60. NICTA: 2016. Available at ‘http://castalia.npc.nicta.com.au, accessed March 2016.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-wss.2018.5116
Loading

Related content

content/journals/10.1049/iet-wss.2018.5116
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address