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Survey on clustering in heterogeneous and homogeneous wireless sensor networks

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Abstract

In wireless sensor networks (WSNs), nodes have limited energy and cannot be recharged. In order to tackle this problem, clustering methods are employed to optimize energy consumption, gather data and also enhance the effective lifetime of the network. In spite of the clustering methods advantages, there are still some important challenges such as choosing a sensor as a cluster head (CH), which has a significant effect in energy efficiency. In clustering phase, nodes are divided into some clusters and then some nodes, named CH, are selected to be the head of each cluster. In typical clustered WSNs, nodes sense the field and send the sensed data to the CH, then, after gathering and aggregating data, CH transmits them to the Base Station. Node clustering in WSNs has many advantages, such as scalability, energy efficiency, and reducing routing delay. In this paper, several clustering methods are studied to demonstrate advantages and disadvantages of them. Among them, some methods deal with homogenous network, whereas some deals with heterogeneous. In this paper, homogenous and heterogeneous methods of clustering are specifically investigated and compared to each other.

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References

  1. Abbasi AA, Younis M (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30:2826–2841

    Article  Google Scholar 

  2. Abdullah M, Eldin HN, Al-Moshadak T, Alshaik R, Al-Anesi I (2015) Density grid-based clustering for wireless sensors networks. In: International Conference on Communication, Management and Information Technology (ICCMIT2015), Procedia Computer Science, vol 65, pp 35–47

  3. Agrawal DP, Manjeshwar A (2001) TEEN: a protocol for enhanced efficiency in wireless sensor networks. In: Proceedings of the 1st international workshop on parallel and distributed computing issues in wireless networks and mobile computing, pp 2009–2015, Apr 2001

  4. Ahmed G, Zou J, Fareed MMS, Zeeshan M (2016) Sleep-awake energy efficient distributed clustering algorithm for wireless sensor networks. Comput Electr Eng 56:385–398

    Article  Google Scholar 

  5. Akyildiz WS, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. J Comput Netw 38:393–422

    Article  Google Scholar 

  6. Albath J, Thakur M, Madria S (2013) Energy constraint clustering algorithms for wireless sensor networks. Ad Hoc Netw 11:2512–2525

    Article  Google Scholar 

  7. Azizi N, Karimpour J, Seifi F (2012) HCTE: hierarchical clustering based routing algorithm with applying the two cluster heads in each cluster for energy balancing in WSN. Int J Comput Sci Issues 09:57–61

    Google Scholar 

  8. Bandyopadhyay S, Coyle E (2003) An energy efficient hierarchical clustering algorithm for wireless sensor networks. In: Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2003), San Francisco, California, Apr 2003

  9. Banerjee S, Khuller S (2001) A clustering scheme for hierarchical control in multi-hop wireless networks. In: Proceedings of 20th Joint Conference of the IEEE Computer and Communications Societies (INFOCOM’ 01), Anchorage, AK, Apr 2001

  10. Behzad M, Ge Y (2017) Performance optimization in wireless sensor networks: a novel collaborative compressed sensing approach. In: 31st International Conference on Advanced Information Networking and Applications (AINA), 2017 IEEE, pp 749–756

  11. Beth HW (2000) Application specific protocol architectures for wireless networks. Doctor of Philosophy at Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  12. Bore Gowda SB, Puttamadappa C, Mruthyunjaya HS, Babu NV (2012) Sector based multi-hop clustering protocol for wireless sensor networks. Int J Comput Appl 43(13):32–38

    Google Scholar 

  13. Boyinbode O, Le H, Mbogho A, Takizawa M, Poliah R (2010) A survey on clustering algorithms for wireless sensor networks. In: 13th International Conference on Network-Based Information Systems (NBiS), Cape Town, South Africa: [s.n.], pp 358–364

  14. Cenedese A, Luvisotto M, Michieletto G (2017) Distributed clustering strategies in industrial wireless sensor networks. IEEE Trans Ind Inform 13(1):228–237

    Article  Google Scholar 

  15. Chatterjee M, Das SK, Turgut D (2002) WCA: a weighted clustering algorithm for mobile Ad Hoc networks. Clust Comput 05:193–204

    Article  Google Scholar 

  16. Dahane A, Loukil A, Kechar B, Berrached N (2015) Energy efficient weighted clustering algorithm in wireless sensor networks. Mob Inf Syst 2015:1–18

    Google Scholar 

  17. Dai F, Wu J (2005) On constructing k-connected k-dominating set in wireless networks. In: Proceedings of the 19th IEEE international parallel and distributed processing symposium (IPDPS’05), Denver, Colorado, pp. 81a, Apr 2005

  18. Demirbas M, Arora A, Mittal V (2004) FLOC: a fast local clustering service for wireless sensor networks, In: Proceedings of workshop on dependability issues in wireless ad hoc networks and sensor networks (DIWANS’04), Palazzo dei Congressi, Florence, Italy, June 2004

  19. Deshpande VV, Patil ARB (2013) Energy efficient clustering in wireless sensor network using cluster of cluster heads. In: Proceedings of WOCN, pp 1–5

  20. Ding P, Holliday J, Celik A (2005) Distributed energy efficient hierarchical clustering for wireless sensor networks, In: Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS’05), Marina Del Rey, CA, June 2005

  21. Ding P, Holliday J, Celik A (2005) Distributed energy efficient hierarchical clustering for wireless sensor networks. In: Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS’05), pp 322–339, June 2005

  22. Elbhiri B, Saadane R, Aboutajdine D (2009) Stochastic distributed energy-efficient clustering (SDEEC) for heterogeneous wireless sensor networks. ICGST-CNIR J 09(02):11–17

    Google Scholar 

  23. Erdal C, Ramesh G, Taieb Z, Mani S (2003) Wireless sensor networks. Comput Netw 43(15):417–419

    Google Scholar 

  24. Fahmy S, Younis O (2004) HEED: a hybrid energy-efficient distributed clustering approach for Ad Hoc sensor networks. IEEE Trans Mob Comput 3:366–379

    Article  Google Scholar 

  25. Fan C, Duan H (2007) A distributed energy balance clustering protocol for heterogeneous wireless sensor networks. In: Wireless Communications, Networking and Mobile Computing, pp 2469–2473

  26. Garcia F, Solano J, Stojmenovic I (2003) Connectivity based k-hopclustering in wireless networks. Telecommun Syst 22:205–220

    Article  Google Scholar 

  27. Garg D, Kumar P (2017) Performance analysis on energy efficient protocols in wireless sensor networks. Int J Adv Res Comput Sci 8(5):1862–1869

    Google Scholar 

  28. Guizani S, Ci M, Sharif H (2007) Adaptive clustering in wireless sensor networks by mining sensor energy data. Comput Commun 30:2968–2975

  29. Guo L-Q, Xie Y, Yang C-H, Jing Z-W (2010) Improve by LEACH by combining adaptive cluster head election and two-hop transmission. Int Conf Mach Learn Cybern (ICMLC) 4:1678–1683

    Google Scholar 

  30. Gupta G, Younis M (2003) Fault-tolerant clustering of wireless sensor networks. : Proceedings of the IEEE Wireless Communication and Networks Conference (WCNC 2003), New Orleans, Louisiana, Mar 2003

  31. Gupta G, Younis M (2003) Fault-tolerant clustering of wireless sensor networks. In: Proceedings of the IEEE Wireless Communication and Networks Conference (WCNC 2003), New Orleans, Louisiana, vol 3, pp 1579–1584

  32. Gupta G, Younis M (2003) Load-balanced clustering in wireless sensor networks. In: Proceedings of the International Conference on Communication (ICC 2003), Anchorage, Alaska, May 2003

  33. Hai DT, Son LH, Le VT (2017) Novel fuzzy clustering scheme for 3D wireless sensor networks. Appl Soft Comput 54:141–149

    Article  Google Scholar 

  34. Haibo Z, Yuanming W, Yanqi H, Guangzhong X (2008) A novel stable selection and reliable transmission protocol for clustered heterogeneous wireless sensor networks. In: computer communications, pp 1843–1849 (in press, corrected proof)

  35. Han G, Zhang C, Jiang J, Yang X, Guizani M (2017) Mobile anchor nodes path planning algorithms using network-density-based clustering in wireless sensor networks. J Netw Comput Appl 85:64–75

    Article  Google Scholar 

  36. Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) Application specific protocol architecture for wireless microsensor networks. In: IEEE transactions on wireless networking

  37. Heinzelman WR, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 01:660–670

    Article  Google Scholar 

  38. Heo S, Yi J, Cho Y, Hong J (2007) PEACH: power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks. Comput Commun 30:2842–2852

    Article  Google Scholar 

  39. Hu Y, Niu Y, Lam J, Shu Z (2017) An energy-efficient adaptive overlapping clustering method for dynamic continuous monitoring in WSNs. IEEE Sens J 17(3):834–847

    Article  Google Scholar 

  40. Hu X, Li Y, Xu H (2017) Multi-mode clustering model for hierarchical wireless sensor network. Phys A Stat Mech Appl 469:665–675

    Article  Google Scholar 

  41. Ilker Oyman E, Ersoy C (2004) Multiple sink network design problem inlarge scale wireless sensor networks. In: Proceedings of the IEEE International Conference on Communications (ICC 2004), vol 6, pp 3663–3667

  42. Jabeur N (2016) A firefly-inspired micro and macro clustering approach for wireless sensor networks. In: The 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2016), Procedia Computer Science, vol 98, pp. 132–139

  43. Kang SH, Nguyen T (2012) Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Commun Lett 16(9):1396–1399

    Article  Google Scholar 

  44. Krishnamachari B, Estrin D, Wicker S (2002) Modeling data centric routing in wireless sensor networks, In: Proceedings of IEEE INFOCOM, New York, NY, June 2002

  45. Kuila P, Jana PK (2014) Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach. Eng Appl Artif Intell 30:127–140

    Article  Google Scholar 

  46. Kumar D, Aseri TC, Patel RB (2009) EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks. Comput Commun 32:662–667

    Article  Google Scholar 

  47. Kumar SS, MP S, DsssK S (2010) A survey of energy-efficient hierarchical cluster-based routing in wireless sensor networks. Int J Adv Netw Appl 02:570–580

    Google Scholar 

  48. Kumarawadu P, Dechene DJ, Luccini M, Sauer A (2008) Algorithms for node clustering in wireless sensor networks: a survey. In: Information and automation for sustainability, pp 295–300, Dec 2008

  49. Lan KC, Wei M (2017) A compressibility-based clustering algorithm for hierarchical compressive data gathering. IEEE Sens J 17(8):2550–2562

    Article  Google Scholar 

  50. Laurence YZ, Yang T, Chen J (2010) RFID and sensor networks. AUERBACH Pub, CRC Press, Lodon

    Google Scholar 

  51. Li B, Gong L, Wang S, Zhou X (2008) Multihop routing protocol with unequal clustering for wireless sensor networks. In: International colloquium on computing, communication, control, and management (ISECS2008), pp 552–556

  52. Lindsey S, Raghavendra CS (2002) PEGASIS: power efficient gathering in sensor information systems, In: Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, Mar 2002

  53. Lindsey S, Raghavendra CS, Sivalingam K (2001) Data gathering in sensor networks using the energy*delay metric. In: Proceedings of the IPDPS Workshop on Issues in Wireless Networks and Mobile Computing, San Francisco, CA, Apr 2001

  54. Li X, Tao X, Mao G (2017) Unbalanced expander based compressive data gathering in clustered wireless sensor networks. IEEE Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission, vol 5, pp 7553–7566

  55. Liu Z, Zheng Q, Xue L, Guan X (2012) A distributed energy-efficient clustering algorithm with improved coverage in wireless sensor networks. Future Gener Comput Syst 28(05):780–790

    Article  Google Scholar 

  56. Liu X, Li J, Dong Z, Xiong F (2017) Joint design of energy-efficient clustering and data recovery for wireless sensor networks. Exploiting the benefits of interference in wireless networks: energy harvesting and security, pp 3646–3656

  57. Li C, Ye M, Chen G, Wu J (2005) An energy efficient unequal clustering mechanism for wireless sensor networks. In: Proceedings of 2005 IEEE International Conference on Mobile Adhoc and Sensor Systems Conference (MASS05), Washington, D.C. : [s.n.], pp 604–611, Nov 2005

  58. Loscri V, Morabito G, Marano S (2005) A two-level hierarchy for low-energy adaptive clustering hierarchy. Proc Veh Technol Conf 03:1809–1813

    Google Scholar 

  59. Low CP, Fang C, Ng JM, Ang YH (2008) Efficient load-balanced clustering algorithms for wireless sensor networks. Comput Commun 31:750–759

    Article  Google Scholar 

  60. Marin-Perianu RS, Scholten J, Havinga PJM, Hartel PH (2008) Cluster-based service discovery for heterogeneous wireless sensor networks. Int J Parallel Emerg Distrib Syst 04:325–346

    Article  MathSciNet  MATH  Google Scholar 

  61. Min R, Bhardwaj M, Cho S, Shih E, Sinha A, Wang A, Chandrakasan A (2001) Low power wireless sensor networks. In: Proceedings of International Conference on VLSI Design, pp 205–210

  62. Mirza MA, Garimella RM (2009) PASCAL: power aware sectoring based clustering algorithm for wireless sensor networks. The International Conference on Information Networking (ICOIN), Chiang Mai, Thailand, January 2009

  63. Mohd O (2017) Dynamic relocation of mobile BSin wireless sensor networks using a cluster-based harmony search algorithm. Inf Sci 385–386:76–95

    Google Scholar 

  64. Narottam Chand VK, Soni S (2011) A survey on clustering algorithms for heterogeneous wireless sensor networks. Int. J. Adv Netw Appl 02:745–754

    Google Scholar 

  65. Nayak P, Vathasavai B (2017) Energy efficient clustering algorithm for multi hop wireless sensor network using type-2 fuzzy logic. IEEE Sens J 17(14):4492–4499

    Article  Google Scholar 

  66. Ouchitachen H, Hair A, Idrissi N (2017) Improved multi-objective weighted clustering algorithm in wireless sensor network. Egypt Inform J 18:45–54

    Article  Google Scholar 

  67. Pal V, Yogita, Singh G, Yadav RP (2015) Effect of Heterogeneous nodes location on the performance of clustering algorithms for wireless sensor networks. In: 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015), vol 57, pp 1042–1048

  68. Phanish D, Coyle EJ (2017) Application-based optimization of multi-level clustering in ad hoc and sensor networks. IEEE Trans Wirel Commun 16(7):4460–4475

    Article  Google Scholar 

  69. Prasad D, Metta VP (2017) An improvement of energy efficiency clustering protocol by using K-Means algorithm. Int Res J Eng Technol (IRJET) 4(6):2486–2489

    Google Scholar 

  70. QIAN KAI-GUO (2013) A clustering routing protocol for sensor network based on distance probability. IEEE, pp 113–116

  71. Rabeay JM, Ammer MJ, da Silva JL, Patel D, Roundry S (2000) PicoRadio supports ad hoc ultra-low power wireless networking. IEEE Comput Mag 33:42–48

    Article  Google Scholar 

  72. Ram B, Chand N, Gupta P, Chauhan S (2011) A new approach layered architecture based a new approach layered architecture based. Int J Comput Appl 15(01):53–55

    Google Scholar 

  73. RS Lindsey, CS (2002) PEGASIS: Power-efficient gathering in sensor information system. In: Proceedings IEEE Aerospace Conference, Big Sky, MT: [s.n.], 03, pp 1125–1130

  74. Sabor N, Abo-Zahhad M, Sasaki S, Ahmed SM (2016) An unequal multi-hop balanced immune clustering protocol for wireless sensor networks. Appl Soft Comput 43:372–389

    Article  Google Scholar 

  75. Sandeep DN, Kumar V (2017) Review on clustering, coverage and connectivity in underwater wireless sensor networks: a communication techniques perspective, IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission, pp 1–22

  76. Shokouhifar M, Jalili A (2017) Optimized sugeno fuzzy clustering algorithm for wireless sensor networks. Eng Appl Artif Intell 60:16–25

    Article  Google Scholar 

  77. Singh Mann P, Singh S (2017) Energy efficient clustering protocol based on improved metaheuristic in wireless sensor networks. J Netw Comput Appl 83:40–52

    Article  Google Scholar 

  78. Singh J, kumar R, Mishra AK (2015) Clustering algorithms for wireless sensor networks: a review. In: 2nd International Conference on Computing for Sustainable Global Development (INDIACom), pp 637–642

  79. Smaragdakis G, Matta I, Bestavros A (2004) SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. In: Proceedings of the international workshop on SANPA, pp 251–261

  80. Sohn I, Lee J, Lee SH (2016) Low-energy adaptive clustering hierarchy using affinity propagation for wireless sensor networks. IEEE Commun Lett 20(3):558–561

    Article  Google Scholar 

  81. Subramanian L, Katz RH (2000) An architecture for building self configurable systems, In: Proceedings of IEEE/ACM workshop on mobile ad hoc networking and computing, Boston, MA, Aug 2000

  82. Tandon R, Dey B, Nandi S (2013) Weight based clustering. In: Wireless sensor networks, IEEE, pp 1–5

  83. Tyagi S, Gupta SK (2013) EHE-LEACH: Enhanced heterogeneous LEACH protocol for lifetime enhancement of wireless SNs. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp 1485–1490

  84. Varma S, Nigam N, Tiwary US (2008) BSHeterogeneous wireless sensor network using clustering. In: Wireless communication and sensor networks, WCSN, pp 1–6

  85. Venkateswarlu MK, Kandasamy A, Chandrasekaran K (2016) An energy-efficient clustering algorithm for edge-based wireless sensor networks. In: Twelfth International Multi-Conference on Information Processing-2016 (IMCIP-2016), Procedia Computer Science, vol 89, pp 7–16

  86. Wang A, Yang D, Sun D (2012) A clustering algorithm based on energy information and cluster heads expectation for wireless sensor network. Des Anal Wirel Syst Emerg Comput Archit Syst 38:662–671

    Google Scholar 

  87. Wang K, Abu AS, Little TDC, Basu P (2005) Attribute-based clustering for information dissemination in wireless sensor networks, In: Proceeding of 2nd Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON 2005), Santa Clara, CA, Sept 2005

  88. Woungang SMI, Misra SC (2009) Guide to wireless sensor networks. Springer, London

    MATH  Google Scholar 

  89. Yadav S, Kumar V (2017) Optimal clustering in underwater wireless sensor networks: acoustic, EM and FSO Communication compliant technique, IEEE Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission, pp 1–16

  90. Ye M, Li C, Chen G, Wu J (2006) An energy efficient clustering scheme in wireless sensor networks. Ad Hoc Sensor Wirel Netw 1:1–21

    Google Scholar 

  91. Young H, Wan Y, Haosong G, Zeng H (2009) A partition based LEACH algorithm. In IEEE Ninth International Conference on Computer and Information Technology, pp 40–45

  92. Younis O, Fahmy S (2004) HEED: a hybrid, energy-efficient, distributed clustering approach for Ad Hoc sensor networks. IEEE Trans Mob Comput 3(4):366–379

    Article  Google Scholar 

  93. Yueyang L, Hong J, Guangxin Y (2006) An energy-efficient PEGASIS-based enhanced algorithm in wireless sensor networks. China Communications Technology Forum

  94. Zhu Q, Qing L, Wang M (2006) Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Comput Commun 29:2230–2237

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Communication Engineering, University of Sistan and Baluchestan, Zahedan, Iran

    Ali Shokouhi Rostami, Marzieh Badkoobe, Farahnaz Mohanna & Hengameh keshavarz

  2. Young Researchers and Elite Club, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran

    Ali Asghar Rahmani Hosseinabadi

  3. School of Computing Science and Engineering, VIT University, Vellore, 632014, India

    Arun Kumar Sangaiah

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  1. Ali Shokouhi Rostami
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  2. Marzieh Badkoobe
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Rostami, A.S., Badkoobe, M., Mohanna, F. et al. Survey on clustering in heterogeneous and homogeneous wireless sensor networks. J Supercomput 74, 277–323 (2018). https://doi.org/10.1007/s11227-017-2128-1

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