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access icon free Metaheuristics-based energy efficient clustering in WSNs: challenges and research contributions

© The Institution of Engineering and Technology
Received 28/07/2020, Accepted 29/09/2020, Revised 07/09/2020, Published 02/10/2020

In past few years, wireless sensor network (WSN) is considered as an essential and imperative way for efficient data communication in ubiquitous computing environment along with the fulfilment of objectives such as (i) lifetime enhancement and (ii) energy conservation. Till date, the research findings demonstrate that clustering of WSNs is an effective and pertinent approach. Moreover, designing of energy-aware routing schemes for clustered WSNs is a basic necessity due to resource-restricted nature of these sensor nodes. This study has a twofold contribution. First, the research dimensions of WSNs are explained by incorporating recent work carried out as per findings in real scenarios. Secondly, this study presents a comprehensive survey of existing clustering schemes for WSNs based on metaheuristic techniques. This study is beneficial for researchers of this domain as it surveys the literature over the period 2000–2020 on energy efficiency in clustered WSNs.

Inspec keywords: wireless sensor networks; telecommunication network routing; energy conservation; pattern clustering; telecommunication power management; data communication

Other keywords: metaheuristics-based energy efficient clustering; clustered WSNs; wireless sensor network; energy-aware routing schemes; ubiquitous computing environment; lifetime enhancement; metaheuristic techniques; sensor nodes; clustering schemes; efficient data communication; energy conservation

Subjects: Communication network design, planning and routing; Wireless sensor networks; Telecommunication systems (energy utilisation)

References

    1. 1)
      • 3. Patil, R., Kohir, V.V.: ‘Energy efficient flat and hierarchical routing protocols in wireless sensor networks: a survey’, IOSR J. Electron. Commun. Eng., 2016, 1, (6), pp. 24–32.
    2. 2)
      • 86. Mittal, N.: ‘Moth flame optimization based energy efficient stable clustered routing approach for wireless sensor networks’, Wirel. Pers. Commun., 2019, 104, (2), pp. 677–694.
    3. 3)
      • 56. Agrawal, D., Pandey, S.: ‘FLIHSBC: fuzzy logic and improved harmony search based clustering algorithm for wireless sensor networks to prolong the network lifetime’. Int. Conf. on Ubiquitous Computing and Ambient Intelligence, Springer, Cham, Philadelphia, PA, USA., 2017, pp. 570–578.
    4. 4)
      • 63. Katiyar, V., Chand, N., Soni, S.: ‘Clustering algorithms for heterogeneous wireless sensor network: a survey’, Int. J. Appl. Eng. Res., 2010, 1, (2), p. 273.
    5. 5)
      • 9. Sadagopan, N., Krishnamachari, B., Helmy, A.: ‘Active query forwarding in sensor networks’, Ad Hoc Netw., 2005, 3, (1), pp. 91–113.
    6. 6)
      • 51. Li, H., Liu, Y., Chen, W., et al: ‘COCA: constructing optimal clustering architecture to maximize sensor network lifetime’, Comput. Commun., 2013, 36, (3), pp. 256–268.
    7. 7)
      • 20. Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: ‘Energy-efficient communication protocol for wireless microsensor networks’. Proc. of the 33rd Annual Hawaii Int. Conf. on System Sciences, Maui, Hawaii, USA., 2000, p. 10.
    8. 8)
      • 79. Sharma, R., Vashisht, V., Singh, A.V., et al: ‘Analysis of existing clustering algorithms for wireless sensor networks’. System Performance and Management Analytics, Springer, Singapore, February, 2017, pp. 259–277.
    9. 9)
    10. 10)
      • 23. Manjeshwar, A., Agrawal, D.P.: ‘APTEEN: a hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks’. Proc. 16th Int. Parallel and Distributed Processing Symp. IPDPS, Ft. Lauderdale, FL, USA., 2002, p. 0195b.
    11. 11)
      • 69. Jindal, P., Gupta, V.: ‘Study of energy efficient routing protocols of wireless sensor networks and their further researches: a survey’, J. Comput. Sci. Commun. Eng., 2013, 2, pp. 57–62.
    12. 12)
      • 81. Tabatabaei, S., Rajaei, A., Rigi, A.M.: ‘A novel energy-aware clustering method via lion pride optimizer algorithm (LPO) and fuzzy logic in wireless sensor networks (WSNs)’, Wirel. Pers. Commun., 2019, 108, pp. 1803–1825.
    13. 13)
      • 62. Boyinbode, O., Le, H., Mbogho, A., et al: ‘A survey on clustering algorithms for wireless sensor networks’. 2010 13th Int. Conf. on Network-based Information Systems, Takayama, Gifu, Japan, September 2010, pp. 358–364.
    14. 14)
      • 66. Wei, C., Yang, J., Gao, Y., et al: ‘Cluster-based routing protocols in wireless sensor networks: a survey’. Proc. of 2011 Int. Conf. on Computer Science and Network Technology, Harbin, China, December 2011, Vol. 3, pp. 1659–1663.
    15. 15)
      • 53. Liu, J.L., Ravishankar, C.V.: ‘LEACH-GA: genetic algorithm-based energy-efficient adaptive clustering protocol for wireless sensor networks’, Int. J. Mach. Learn. Comput., 2011, 1, (1), p. 79.
    16. 16)
      • 78. Rai, R., Rai, P.: ‘Survey on energy-efficient routing protocols in wireless sensor networks using game theory’. Advances in Communication, Cloud, and Big Data, Springer, Singapore, 2019, pp. 1–9.
    17. 17)
      • 61. Jiang, C., Yuan, D., Zhao, Y.: ‘Towards clustering algorithms in wireless sensor networks – a survey’. 2009 IEEE Wireless Communications and Networking Conf., Budapest, Hungary, 2009, pp. 1–6.
    18. 18)
      • 48. Rajagopal, A., Somasundaram, S., Sowmya, B., et al: ‘Soft computing based cluster head selection in wireless sensor network using bacterial foraging optimization algorithm’, Int. J. Electron. Commun. Eng., 2015, 9, (3), pp. 379–384.
    19. 19)
      • 36. Gherbi, C., Aliouat, Z., Benmohammed, M.: ‘Distributed energy efficient adaptive clustering protocol with data gathering for large scale wireless sensor networks’. 2015 12th Int. Symp. on Programming and Systems (ISPS), Algiers, Algeria, 2015, pp. 1–7.
    20. 20)
      • 64. Lotf, J.J., Hosseinzadeh, M., Alguliev, R.M.: ‘Hierarchical routing in wireless sensor networks: a survey’. 2010 2nd Int. Conf. on Computer Engineering and Technology, Chengdu, April 2010, Vol. 3, p. 650.
    21. 21)
      • 45. Zhang, X., Chen, H., Lin, K., et al: ‘RMTS: A robust clock synchronization scheme for wireless sensor networks’, J. Netw. Comput. Appl., 2019, 135, pp. 1–10.
    22. 22)
      • 70. Afsar, M.M., Tayarani, N.M.H.: ‘Clustering in sensor networks: a literature survey’, J. Netw. Comput. Appl., 2014, 46, pp. 198–226.
    23. 23)
      • 34. Li, Z., Lei, L.: ‘Sensor node deployment in wireless sensor networks based on improved particle swarm optimization’. Int. Conf. on Applied Superconductivity and Electromagnetic Devices, Chengdu, China, 2009, pp. 215–217.
    24. 24)
      • 40. Kong, H., Yu, B.: ‘An improved method of WSN coverage based on enhanced PSO algorithm’. 2019 IEEE 8th Joint Int. Information Technology and Artificial Intelligence Conf. (ITAIC), Chongqing, China, 2019, pp. 1294–1297.
    25. 25)
      • 12. Bellur, B., Ogier, R.G.: ‘A reliable, efficient topology broadcast protocol for dynamic networks’. IEEE INFOCOM'99, Conf. on Computer Communications. Proc., Eighteenth Annual Joint Conf. of the IEEE Computer and Communications Societies, New York, NY, USA., 1999, Vol. 1, pp. 178–186.
    26. 26)
      • 44. Sahoo, R.R., Singh, M., Sardar, A.R., et al: ‘TREE-CR: trust based secure and energy efficient clustering in WSN’. IEEE 2013 Int. Conf. on Emerging Trends in Computing, Communication and Nanotechnology (ICE-CCN), USA., 2013, pp. 532–538.
    27. 27)
      • 1. Akyildiz, I.F., Su, W., Sankarasubramani, Y., et al: ‘Wireless sensor networks: a survey’, Comput. Netw., 2002, 38, (4), pp. 393–422.
    28. 28)
      • 55. Kuila, P., Jana, P.K.: ‘A novel differential evolution based clustering algorithm for wireless sensor networks’, Appl. Soft Comput., 2014, 25, pp. 414–425.
    29. 29)
      • 76. Sharma, R., Vashisht, V., Singh, U.: ‘Node clustering in wireless sensor networks using fuzzy logic: survey’. 2018 Int. Conf. on System Modeling & Advancement in Research Trends (SMART), Moradabad, India, 2018, pp. 66–72.
    30. 30)
      • 74. 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. Tutorials, 2017, 19, (2), pp. 828–854.
    31. 31)
      • 83. Gupta, P., Sharma, A.K.: J. Ambient Intell. Humanized Comput., 2019, 10, (2), pp. 681–700.
    32. 32)
      • 88. Sharma, R., Vashisht, V., Singh, U.: ‘eeTMFO/GA: A secure and energy efficient cluster head selection in wireless sensor networks’, Telecommun. Syst., 2020, 74, (3), pp. 253–268.
    33. 33)
      • 50. Rajagopal, A., Somasundaram, S., Sowmya, B., et al: ‘Performance analysis for efficient cluster head selection in wireless sensor network using RBFO and hybrid BFO-BSO’, In. J. Wirel. Commun. Mobile Comput., 2018, 6, (1), pp. 1–9.
    34. 34)
      • 31. Sharma, R., Vashisht, V., Singh, U.: ‘Fuzzy modelling based energy aware clustering in wireless sensor networks using modified invasive weed optimization’, J. King Saud Univ. – Comput. Inf. Sci., 2019, https://doi.org/10.1016/j.jksuci.2019.11.014.
    35. 35)
      • 16. Grover, J., Sharma, M.: ‘Location based protocols in wireless sensor network – a review’. Fifth Int. Conf. on Computing, Communications and Networking Technologies (ICCCNT), Hefei, China, 2014, pp. 1–5.
    36. 36)
      • 38. Shanmukhi, M., Ramanaiah, O.B.V.: ‘Cluster-based comb-needle model for energy-efficient data aggregation in wireless sensor networks’. 2015 Applications and Innovations in Mobile Computing (AIMoC), Kolkata, 2015, pp. 42–47.
    37. 37)
      • 35. Liu, X., He, D.: ‘Ant colony optimization with greedy migration mechanism for node deployment in wireless sensor networks’, J. Netw. Comput. Appl., 2014, 39, pp. 310–318.
    38. 38)
      • 37. Fang, W., Wen, X., Xu, J., et al: ‘CSDA: a novel cluster-based secure data aggregation scheme for WSNs’, Cluster Comput.., 2019, 22, (3), pp. 5233–5244.
    39. 39)
      • 60. Kumarawadu, P., Dechene, D.J., Luccini, M., et al: ‘Algorithms for node clustering in wireless sensor networks: a survey’. 2008 4th Int. Conf. on Information and Automation for Sustainability, Sri Lanka, 2008, pp. 295–300.
    40. 40)
      • 59. Deosarkar, B.P., Yadav, N.S., Yadav, R.P.: ‘Cluster head selection in clustering algorithms for wireless sensor networks: a survey’. 2008 Int. Conf. on Computing, Communication and Networking, Karur, Tamil Nadu, India, 2008, pp. 1–8.
    41. 41)
      • 68. Mishra, S., Raj, A., Kayal, A., et al: ‘Study of cluster based routing protocols in wireless sensor networks’, Int. J. Scient. Eng. Res., 2012, 3, (7), pp. 1–7.
    42. 42)
      • 80. Fanian, F., Rafsanjani, M.K.: ‘Cluster-based routing protocols in wireless sensor networks: a survey based on methodology’, J. Netw. Comput. Appl., 2019, 142, pp. 111–142.
    43. 43)
      • 7. Braginsky, D., Estrin, D.: ‘Rumor routing algorthim for sensor networks’. Proc. of the 1st ACM Int. Workshop on Wireless Sensor Networks and Applications, Atlanta Georgia USA., 2002, pp. 22–31.
    44. 44)
      • 24. Younis, O., Fahmy, S.: ‘HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks’, IEEE Trans. Mob. Comput., 2004, 3, (4), pp. 366–379.
    45. 45)
      • 27. Xu, D., Gao, J.: ‘Comparison study to hierarchical routing protocols in wireless sensor networks’, Proc. Environ. Sci., 2005, 10, pp. 595–600.
    46. 46)
      • 22. Manjeshwar, A., Agrawal, D.P.: ‘TEEN: a routing protocol for enhanced efficiency in wireless sensor networks’. Proc. 15th Int. Parallel and Distributed Processing Symp. IPDPS, San Francisco, CA, 2001, Vol. 1, p. 189.
    47. 47)
      • 65. Singh, S.K., Singh, M.P., Singh, D.K.: ‘A survey of energy-efficient hierarchical cluster-based routing in wireless sensor networks’, Int. J. Adv. Netw. Appl. (IJANA), 2010, 2, (2), pp. 570–580.
    48. 48)
      • 19. Panwar, A., Kumar, S.A.: ‘Localization schemes in wireless sensor networks’. 2012 Second Int. Conf. on Advanced Computing & Communication Technologies, Rohtak, Haryana, India, 2012, pp. 443–449.
    49. 49)
      • 57. Nasser, N., Arboleda, C., Liliana, M.: ‘Comparison of clustering algorithms and protocols for wireless sensor networks’. 2006 Canadian Conf. on Electrical and Computer Engineering, Canada, 2006, pp. 1787–1792.
    50. 50)
      • 5. Intanagonwiwat, C., Govindan, R., Estrin, D.: ‘Directed diffusion: a scalable and robust communication paradigm for sensor networks’. Proc. of the 6th Annual Int. Conf. on Mobile Computing and Networking, Boston Massachusetts USA., 2000, pp. 56–67.
    51. 51)
      • 25. Muruganathan, S.D., Ma, D.C., Bhasin, R.I., et al: ‘A centralized energy-efficient routing protocol for wireless sensor networks’, IEEE Commun. Mag., 2005, 43, (3), pp. 8–13.
    52. 52)
      • 89. Sharma, R., Vashisht, V., Singh, U.: ‘Performance comparison of trust based clustering protocols for wireless sensor networks’. 2019 6th Int. Conf. on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2019, pp. 642–647.
    53. 53)
      • 84. Mann, P.S., Singh, S.: ‘Improved artificial bee colony metaheuristic for energy-efficient clustering in wireless sensor networks’, Artif. Intell. Rev., 2019, 51, (3), pp. 329–354.
    54. 54)
      • 11. Arce, P., Guerri, J.C., Pajares, A., et al: ‘Performance evaluation of video streaming over ad hoc networks using flat and hierarchical routing protocols’, Mobile Netw. Appl., 2008, 13, (3–4), pp. 324–336.
    55. 55)
      • 32. Nicolaou, A., Temene, N., Sergiou, C., et al: ‘Utilizing Mobile nodes for congestion control in wireless sensor networks’, arXiv preprint arXiv:1903.08989, 2019.
    56. 56)
      • 73. Zeb, A., Islam, A.M., Zareei, M., et al: ‘Clustering analysis in wireless sensor networks: the ambit of performance metrics and schemes taxonomy’, Int. J. Distrib. Sens. Netw., 2016, 12, (7), p. 4979142.
    57. 57)
      • 17. Karp, B., Kung, H.T.: ‘GPSR: greedy perimeter stateless routing for wireless networks’. Proc. of the 6th Annual Int. Conf. on Mobile Computing and Networking, Boston Massachusetts USA., August 2000, pp. 243–254.
    58. 58)
      • 29. Ruan, D., Huang, J.: ‘A PSO-based uneven dynamic clustering multi-hop routing protocol for wireless sensor networks’, Sensors, 2019, 19, (8), p. 1835.
    59. 59)
      • 10. Yao, Y., Gehrke, J.: ‘The cougar approach to in-network query processing in sensor networks’, ACM Sigmod Record, 2002, 31, (3), pp. 9–18.
    60. 60)
      • 8. Hedetniemi, S.M., Hedetniemi, S.T., Liestman, A.L.: ‘A survey of gossiping and broadcasting in communication networks’, Networks, 1988, 18, (4), pp. 319–349.
    61. 61)
      • 87. Sharma, R., Vashisht, V., Singh, U.: ‘Soft computing paradigms based clustering in wireless sensor networks: a survey’. Advances in Data Sciences, Security and Applications, Springer, Singapore, 2020, pp. 133–159.
    62. 62)
      • 77. Sharma, R., Vashisht, V., Singh, U.: ‘Nature inspired algorithms for energy efficient clustering in wireless sensor networks’. 2019 9th Int. Conf. on Cloud Computing, Data Science & Engineering (Confluence), Noida, India, 2019, pp. 365–370.
    63. 63)
      • 2. Kanavalli, A., Sserubiri, D., Shenoy, P.D., et al: ‘A flat routing protocol for sensor networks’. Proc. of Int. Conf. on Methods and Models in Computer Science (ICM2CS), New Delhi, India, 2009, pp. 1–5.
    64. 64)
      • 49. Raghuvanshi, A.S., Tiwari, S., Tripathi, R., et al: ‘Optimal number of clusters in wireless sensor networks: an FCM approach’. 2010 Int. Conf. on Computer and Communication Technology (ICCCT), Allahabad, India, 2010, pp. 817–823.
    65. 65)
      • 13. Ogier, R., Templin, F., Lewis, M.: ‘Topology dissemination based on reverse-path forwarding (TBRPF)’, IETF RFC 3684, 2004.
    66. 66)
      • 26. Rathi, N., Saraswat, J., Bhattacharya, P.P.: ‘A review on routing protocols for application in wireless sensor networks’, arXiv preprint arXiv:1210.2940, 2012.
    67. 67)
      • 6. Lim, H., Kim, C.: ‘Flooding in wireless ad hoc networks’, Comput. Commun., 2001, 24, (3–4), pp. 353–363.
    68. 68)
      • 42. Kim, S., Ko, J.G., Yoon, J., et al: ‘Multiple-objective metric for placing multiple base stations in wireless sensor networks’. 2007 2nd Int. Symp. on Wireless Pervasive Computing, San Juan, Puerto Rico, 2007.
    69. 69)
      • 58. Abbasi, A.A., Younis, M.: ‘A survey on clustering algorithms for wireless sensor networks’, Comput. Commun., 2007, 30, (14–15), pp. 2826–2841.
    70. 70)
      • 15. Soni, V., Mallick, D.K.: ‘Location-based routing protocols in wireless sensor networks: a survey’, Int. J. Internet Protocol Technol., 2014, 8, (4), pp. 200–213.
    71. 71)
      • 75. Rostami, A.S., Badkoobe, M., Mohanna, F., et al: ‘Survey on clustering in heterogeneous and homogeneous wireless sensor networks’, J. Supercomput., 2018, 74, (1), pp. 277–323.
    72. 72)
      • 33. Kazmi, H.S.Z., Javaid, N., Imran, M., et al: ‘Congestion control in wireless sensor networks based on support vector machine, grey wolf optimization and differential evolution’. 2019 Wireless Days (WD), Manchester, UK., 2019, pp. 1–8.
    73. 73)
      • 71. Singh, S.P., Sharma, S.C.: ‘A survey on cluster based routing protocols in wireless sensor networks’, Procedia Comput. Sci., 2014, 45, pp. 687–695.
    74. 74)
      • 41. Zafar, S., Bashir, A., Chaudhry, S.A.: ‘Mobility-aware hierarchical clustering in mobile wireless sensor networks’, IEEE Access, 2019, 7, pp. 20394–20403.
    75. 75)
      • 28. Sharma, R., Vashisht, V., Singh, U.: ‘EEFCM-DE: energy efficient clustering based on fuzzy C means and differential evolution algorithm in wireless sensor networks’, IET Commun.., 2019, 13, (8), pp. 996–1007.
    76. 76)
      • 43. Chandrawanshi, V.S., Tripathi, R.K., Pachauri, R.: ‘An intelligent energy efficient clustering technique for multiple base stations positioning in a wireless sensor network’, J. Intell. Fuzzy Syst., 2019, 36, (3), pp. 2409–2418.
    77. 77)
      • 82. Singh, S., Kumar, P.: ‘MH-CACA: multi-objective harmony search-based coverage aware clustering algorithm in WSNs’, Enterprise Inf. Syst., 2019, pp. 1–29.
    78. 78)
      • 18. Yu, Y., Govindan, R., Estrin, D.: ‘Geographical and energy aware routing: a recursive data dissemination protocol for wireless sensor networks’, 2001.
    79. 79)
      • 67. Liu, X.: ‘A survey on clustering routing protocols in wireless sensor networks’, Sensors, 2012, 12, (8), pp. 11113–11153.
    80. 80)
      • 52. Zhang, J., Lin, Y., Zhou, C., et al: ‘Optimal model for energy-efficient clustering in wireless sensor networks using global simulated annealing genetic algorithm’. Intelligent Information Technology Application Workshops, IITAW'08 Int. Symp., Shanghai, China, 2008, pp. 656–660.
    81. 81)
      • 14. Haas, Z.J.: ‘A new routing protocol for the reconfigurable wireless networks’. Proc. of ICUPC 97-6th Int. Conf. on Universal Personal Communications, Florence, Italy, 1997, Vol. 2, pp. 562–566.
    82. 82)
    83. 83)
      • 39. Aziz, N.A.A., Ibrahim, Z., Aziz, N.H.A., et al: ‘Simulated Kalman filter optimization algorithm for maximization of wireless sensor networks coverage’. 2019 Int. Conf. on Computer and Information Sciences (ICCIS), Pakistan, 2019, pp. 1–6.
    84. 84)
      • 72. Mahajan, S., Dhiman, P.K.: ‘Clustering in WSN: a review’, Int. J. Adv. Res. Comput. Sci., 2017, 7, (3), pp. 173–176.
    85. 85)
      • 46. Sharma, R., Vashisht, V., Singh, U.: ‘WOATCA: whale optimization algorithm based trusted scheme for cluster head selection in wireless sensor networks’, IET Commun.., 2020, 14, (8), pp. 1199–1208.
    86. 86)
      • 21. Lindsey, S., Raghavendra, C.S.: ‘PEGASIS: power-efficient gathering in sensor information systems’. Proc., IEEE Aerospace Conf., USA., 2002, Vol. 3, pp. 3–3.
    87. 87)
      • 4. Kulik, J., Heinzelman, W., Balakrishnan, H.: ‘Negotiation- based protocols for disseminating information in wireless sensor networks’, Wirel. Netw., 2002, 8, (2–3), pp. 169–185.
    88. 88)
      • 85. Gui, T., Wang, F., Ma, C., et al: ‘On cluster head selection in monkey-inspired optimization based routing protocol for WSNs’. 2019 Int. Conf. on Computing, Networking and Communications (ICNC), Honolulu, Hawaii, USA., 2019, pp. 126–130.
    89. 89)
      • 30. Sharma, R., Vashisht, V., Singh, U.: ‘Performance analysis of evolutionary technique based partitional clustering algorithms for wireless sensor networks’, in Pant, M., Sharma, T., Verma, O., Singla, R., Sikander, A. (Eds) Soft computing: theories and applications. Advances in intelligent systems and computing, Vol. 1053 (Springer, Singapore, 2020), pp. 171–180. https://doi.org/10.1007/978-981-15-0751-9_16.
    90. 90)
      • 54. Potthuri, S., Shankar, T., Rajesh, A.: ‘Lifetime improvement in wireless sensor net-works using hybrid differential evolution and simulated annealing (DESA)’, Ain Shams Eng. J., 2018, 9, (4), pp. 655–663.
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