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Hierarchical routing protocols for wireless sensor network: a compressive survey

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Abstract

Wireless sensor networks (WSNs) are one of the key enabling technologies for the internet of things (IoT). WSNs play a major role in data communications in applications such as home, health care, environmental monitoring, smart grids, and transportation. WSNs are used in IoT applications and should be secured and energy efficient in order to provide highly reliable data communications. Because of the constraints of energy, memory and computational power of the WSN nodes, clustering algorithms are considered as energy efficient approaches for resource-constrained WSNs. In this paper, we present a survey of the state-of-the-art routing techniques in WSNs. We first present the most relevant previous work in routing protocols surveys then highlight our contribution. Next, we outline the background, robustness criteria, and constraints of WSNs. This is followed by a survey of different WSN routing techniques. Routing techniques are generally classified as flat, hierarchical, and location-based routing. This survey focuses on the deep analysis of WSN hierarchical routing protocols. We further classify hierarchical protocols based on their routing techniques. We carefully choose the most relevant state-of-the-art protocols in order to compare and highlight the advantages, disadvantage and performance issues of each routing technique. Finally, we conclude this survey by presenting a comprehensive survey of the recent improvements of low-energy adaptive clustering hierarchy routing protocols and a comparison of the different versions presented in the literature.

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References

  1. Kumar, A., Ovsthus, K., & Kristensen, L. (2014). An industrial perspective on wireless sensor networks: A survey of requirements, protocols, and challenges. IEEE Communications Surveys Tutorials, 16(3), 1391–1412.

    Article  Google Scholar 

  2. Aldeer, M. M. N. (2013). A summary survey on recent applications of wireless sensor networks. In IEEE Student Conference on Research and Development (pp. 485–490).

  3. Gungor, V. C., Lu, B., & Hancke, G. P. (2010). Opportunities and challenges of wireless sensor networks in smart grid. IEEE Transactions on Industrial Electronics, 57(10), 3557–3564.

    Article  Google Scholar 

  4. Erol-Kantarci, M., & Mouftah, H. T. (2011). Wireless sensor networks for cost-efficient residential energy management in the smart grid. IEEE Transactions on Smart Grid, 2(2), 314–325.

    Article  Google Scholar 

  5. Prathap, U., Shenoy, P., Venugopal, K., & Patnaik, L. (2012). Wireless sensor networks applications and routing protocols: Survey and research challenges. In IEEE Symposium on Cloud and Services Computing (pp. 49–56).

  6. Gkikopouli, A., Nikolakopoulos, G., & Manesis, S. (2012). A survey on underwater wireless sensor networks and applications. In IEEE Conference on Control Automation (MED) (pp. 1147–1154).

  7. Blanckenstein, J., Klaue, J., & Karl, H. (2015). A survey of low-power transceivers and their applications. IEEE Circuits and Systems Magazine, 15(3), 6–17. thirdquarter.

    Article  Google Scholar 

  8. Miorandi, D., Lowe, D., & Gomez, K. M. (2010). Activation-inhibition-based data highways for wireless sensor networks. In E. Altman, I. Carrera, R. El-Azouzi, E. Hart, & Y. Hayel (Eds.), Bioinspired models of network. Information, and computing systems (pp. 95–102). Berlin, Heidelberg: Springer.

    Chapter  Google Scholar 

  9. Chang, J.-H., & Tassiulas, L. (2004). Maximum lifetime routing in wireless sensor networks. IEEE/ACM Transactions on Networking, 12(4), 609–619.

    Article  Google Scholar 

  10. Liu, X. (2015). Atypical hierarchical routing protocols for wireless sensor networks: A review. IEEE Sensors Journal, 15(10), 5372–5383.

    Article  Google Scholar 

  11. Ali, A., & Parmanand. (2015). Energy efficieny in routing protocol and data collection approaches for WSN: A survey. In IEEE Conference on Computing, Communication Automation (pp. 540–545).

  12. Chatap, A., & Sirsikar, S. (2017). Review on various routing protocols for heterogeneous wireless sensor network. In Conference on IoT in Social, Mobile, Analytics and Cloud (pp. 440–444).

  13. Singh, S., Kumar, P., & Singh, J. (2017). A survey on successors of LEACH protocol. IEEE Access, 5, 4298–4328.

    Article  Google Scholar 

  14. Yassen, M. B., Aljawaerneh, S., & Abdulraziq, R. (2016). Secure low energy adaptive clustering hierarchal based on internet of things for wireless sensor network (WSN): Survey. In Conference on Engineering MIS (pp. 1–9).

  15. Agarwal, A., Gupta, K., & Yadav, K. P. (2016). A novel energy efficiency protocol for WSN based on optimal chain routing. In IEEE Conference on Computing for Sustainable Global Development (INDIACom) (pp. 368–373).

  16. Kumari, J., & Prachi. (2015). A comprehensive survey of routing protocols in wireless sensor networks. In IEEE Conference on Computing for Sustainable Global Development (pp. 325–330).

  17. Hao, J., Zhang, B., & Mouftah, H. T. (2012). Routing protocols for duty cycled wireless sensor networks: A survey. IEEE Communications Magazine, 50(12), 116–123.

    Article  Google Scholar 

  18. Yamunadevi, S. P., Vairam, T., Kalaiarasan, C., & Vidya, G. (2012). Efficient comparison of multipath routing protocols in WSN. In IEEE Conference on Computing, Electronics and Electrical Technologies (pp. 807–811).

  19. Goyal, D., & Tripathy, M. (2012). Routing protocols in wireless sensor networks: A survey. In IEEE Conference on Advanced Computing Communication Technologies (pp. 474–480).

  20. Baghyalakshmi, D., Ebenezer, J., & Satyamurty, S. (2010). Low latency and energy efficient routing protocols for wireless sensor networks. In IEEE Conference on Wireless Communication and Sensor Computing (pp. 1–6).

  21. Watteyne, T., Molinaro, A., Richichi, M. G., & Dohler, M. (2011). From MANET To IETF ROLL standardization: A paradigm shift in WSN routing protocols. IEEE Communications Surveys Tutorials, 13(4), 688–707. Fourth.

    Article  Google Scholar 

  22. Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 1(4), 660–670.

    Article  Google Scholar 

  23. Kocakulak, M., & Butun, I. (2017). An overview of wireless sensor networks towards internet of things. In IEEE Computing and Communication Workshop and Conference (CCWC) (pp. 1–6).

  24. Sinha, A., & Chandrakasan, A. (2001). Dynamic power management in wireless sensor networks. IEEE Design Test of Computers, 18(2), 62–74.

    Article  Google Scholar 

  25. Schurgers, C., Tsiatsis, V., Ganeriwal, S., & Srivastava, M. (2002). Optimizing sensor networks in the energy-latency-density design space. IEEE Transactions on Mobile Computing, 1(1), 70–80.

    Article  Google Scholar 

  26. Ye, W., Heidemann, J., & Estrin, D. (2004). Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Transactions on Networking, 12(3), 493–506.

    Article  Google Scholar 

  27. Saghar, K., Henderson, W., Kendall, D., & Bouridane, A. (2010). Formal modelling of a robust wireless sensor network routing protocol. In IEEE Conference on Adaptive Hardware and Systems (pp. 281–288).

  28. Alazzawi, L. K., Elkateeb, A. M., Ramesh, A., & Aljuhar, W. (2008). Scalability analysis for wireless sensor networks routing protocols. In IEEE Advanced Information Networking and Applications—Workshops (pp. 139–144).

  29. Horjaturapittaporn, T., & Suntiamorntut, W. (2011). Scalable routing protocol in wireless sensor networks. In IEEE Conference on Communication Software and Networks (pp. 623–627).

  30. Mahmood, M. A., Seah, W. K., & Welch, I. (2015). Reliability in wireless sensor networks: A survey and challenges ahead. Computer Networks, 79(Supplement C), 166–187.

    Article  Google Scholar 

  31. Sohrabi, K., Gao, J., Ailawadhi, V., & Pottie, G. (2000). Protocols for self-organization of a wireless sensor network. IEEE Personal Communications, 7(5), 16–27.

    Article  Google Scholar 

  32. Sirsikar, S., Chunawale, A., & Chandak, M. (2014). Self-organization architecture and model for wireless sensor networks. In IEEE International Conference on Electronic Systems, Signal Processing and Computing Technologies (pp. 204–208).

  33. Spadoni, I. M. B., Araujo, R. B., & Marconde, C. (2009). Improving QoS in wireless sensor networks through adaptable mobile agents. In IEEE INFOCOM Workshops 2009 (pp. 1–2).

  34. Patel, M., & Aggarwal, A. (2013) Security attacks in wireless sensor networks: A survey. In IEEE Conference on Intelligent Systems and Signal Processing (pp. 329–333).

  35. Gaware, A., & Dhonde, S. (2016). A survey on security attacks in wireless sensor networks. In IEEE Conference on Computing for Sustainable Global Development (pp. 536–539).

  36. Sarode, S., Bakal, J., & Malik, L. (2015). Performance analysis of QoS parameters for constraint based WSNs. In IEEE Advance Computing Conference (pp. 877–882).

  37. Rao, G. S., & Kumari, V. V. (2012). A study on various deployment schemes for wireless sensor networks (pp. 495–505). Berlin, Heidelberg: Springer.

  38. Zhang, R., & Gorce, J. M. (2007). Connectivity of wireless sensor networks with unreliable links. In IEEE Conference on Communications and Networking in China (pp. 866–870).

  39. Lindsey, S., Raghavendra, C., & Sivalingam, K. M. (2002). Data gathering algorithms in sensor networks using energy metrics. IEEE Transactions Parallel Distributed System., 13(9), 924–935.

    Article  Google Scholar 

  40. Jung, S. M., Han, Y. J., & Chung, T. M. (2007). The concentric clustering scheme for efficient energy consumption in the PEGASIS. IEEE Conference on Advanced Communication Technology, 1, 260–265.

    Article  Google Scholar 

  41. Xi-rong, B., Shi, Z., Ding-yu, X., & Zhi-tao, Q. (2010). An energy-balanced chain-cluster routing protocol for wireless sensor networks. IEEE Conference on Networks, Security Wireless Communications and Trusted Computing, 2, 79–84.

    Google Scholar 

  42. Chen, K.-H., Huang, J.-M., & Hsiao, C.-C. (2009). CHIRON: an energy-efficient chain-based hierarchical routing protocol in wireless sensor networks. In ACM-IEEE Conference on Wireless Telecommunications Symposium (pp. 183–187). Piscataway, NJ: IEEE Press.

  43. Ding, M., Cheng, X., & Xue, G. (2003). Aggregation tree construction in sensor networks. IEEE Vehicular Technology Conference, 4, 2168–2172. Vol.4.

    Google Scholar 

  44. Kim, H. S., & Han, K. J. (2005). A power efficient routing protocol based on balanced tree in wireless sensor networks. In IEEE Conference on Distributed Frameworks for Multimedia Applications (pp. 138–143).

  45. Tan, H. O., & Körpeoǧlu, I. (2003). Power efficient data gathering and aggregation in wireless sensor networks. ACM SIGMOD Record, 32(4), 66–71.

    Article  Google Scholar 

  46. Qiu, W., Skafidas, E., & Hao, P. (2009). Enhanced tree routing for wireless sensor networks. Ad Hoc Networks, 7(3), 638–650.

    Article  Google Scholar 

  47. Buttyan, L., & Schaffer, P. (2007). PANEL: Position-based aggregator node election in wireless sensor networks. In IEEE Conference on Mobile Adhoc and Sensor Systems (pp. 1–9).

  48. Luo, H., Ye, F., Cheng, J., Lu, S., & Zhang, L. (2005). TTDD: Two-tier data dissemination in large-scale wireless sensor networks. Wireless Networks, 11(1), 161–175.

    Article  Google Scholar 

  49. Koutsonikolas, D., Das, S., Hu, Y. C., Stojmenovic, I. (2007). Hierarchical geographic multicast routing for wireless sensor networks. In Conference on Sensor Technologies and Applications (pp. 347–354).

  50. Banimelhem, O., & Khasawneh, S. (2012). GMCAR: Grid-based multipath with congestion avoidance routing protocol in wireless sensor networks. Ad Hoc Networks, 10(7), 1346–1361.

    Article  Google Scholar 

  51. Hamida, E., & Chelius, G. (2008) A line-based data dissemination protocol for wireless sensor networks with mobile sink. In IEEE Conference on Communications (pp. 2201–2205).

  52. Tunca, C., Isik, S., Donmez, M. Y., & Ersoy, C. (2015). Ring routing: An energy-efficient routing protocol for wireless sensor networks with a mobile sink. IEEE Transactions on Mobile Computing, 14(9), 1947–1960.

    Article  Google Scholar 

  53. Shin, J.-H., Kim, J., Park, K., & Park, D. (2005). Railroad: Virtual infrastructure for data dissemination in wireless sensor networks. In ACM Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks, New York, NY (pp. 168–174).

  54. Mo, H., Lee, E., Park, S., & Kim, S. (2013). Virtual line-based data dissemination for mobile sink groups in wireless sensor networks. IEEE Communications Letters, 17(9), 1864–1867.

    Article  Google Scholar 

  55. Mishra, A. K., Rahman, R. U., Bharadwaj, R., & Sharma, R. (2015). An enhancement of PEGASIS protocol with improved network lifetime for wireless sensor networks. In IEEE Power, Communication and Information Technology Conference (pp. 142–147).

  56. Dutta, R., & Gupta, S. (2016). Energy aware modified PEGASIS through packet transmission in wireless sensor network. In IEEE Conference on Parallel, Distributed and Grid Computing (pp. 443–446).

  57. Tan, N. D., & Viet, N. D. (2015) SSTBC: Sleep scheduled and tree-based clustering routing protocol for energy-efficient in wireless sensor networks. In IEEE Conference on Computing Communication Technologies (pp. 180–185).

  58. Kareem, H., & Jameel, H. (2018). Maintain load balancing in wireless sensor networks using virtual grid based routing protocol. In IEEE Conference on Advanced Science and Engineering (ICOASE) (pp. 227–232).

  59. Bhatti, R., Kaur, G. (2017). Virtual grid based energy efficient mobile sink routing algorithm for WSN. In IEEE Conference on Intelligent Systems and Control (ISCO) (pp. 30–33).

  60. Singh, B., Singh, T., & Sachdeva, H. S. (2017). Evaluating the performance of density grid-based clustering using ABC technique for efficient routing in WSNs. In IEEE Conference on Information Sciences and Systems (CISS) (pp. 1–7).

  61. Ali, M., Dey, T., & Biswas, R. (2008). ALEACH: advanced LEACH routing protocol for wireless microsensor networks. In IEEE Conference on Electrical and Computer Engineering (pp. 909–914).

  62. Tong, M., & Tang, M. (2010). Leach-b: An improved leach protocol for wireless sensor network. In IEEE Conference on Wireless Communications Networking and Mobile Computing (pp. 1–4).

  63. Mehta, R., Pandey, A., & Kapadia, P. (2012). Reforming clusters using C-LEACH in wireless sensor networks. In International Conference on Computer Communication and Informatics (pp. 1–4).

  64. Tripathi, M., Battula, R. B., Gaur, M. S., & Laxmi, V. (2013). Energy efficient clustered routing for wireless sensor network. In IEEE Conference on Mobile Ad-hoc and Sensor Networks (pp. 330–335).

  65. Handy, M., Haase, M., & Timmermann, D. (2002). Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In IEEE Workshop on Mobile and Wireless Communications Network (pp. 368–372).

  66. Xu, J., Jin, N., Lou, X., Peng, T., Zhou, Q., & Chen, Y. (2012). Improvement of leach protocol for WSN. In IEEE Conference on Fuzzy Systems and Knowledge Discovery (pp. 2174–2177).

  67. Azim, A., & Islam, M. (2009). Hybrid LEACH: A relay node based low energy adaptive clustering hierarchy for wireless sensor networks. In IEEE Conference on Communications (pp. 911–916).

  68. Beiranvand, Z., Patooghy, A., & Fazeli, M. (2013). I-LEACH: An efficient routing algorithm to improve performance amp; to reduce energy consumption in wireless sensor networks. In IEEE Conference on Information and Knowledge Technology (pp. 13–18).

  69. Udompongsuk, K., So-In, C., Phaudphut, C., Rujirakul, K., Soomlek, C., & Waikham, B. (2014). MAP: An optimized energy-efficient cluster header selection technique for wireless sensor networks. In H. Jeong, M. S. Obaidat, N. Yen, & J. Park (Eds.), Springer advances in computer science and its applications (pp. 191–199). Berlin, Heidelberg: Springer.

    Chapter  Google Scholar 

  70. Li, Y., Ding, L., & Liu, F. (2011). The improvement of LEACH protocol in wsn. IEEE Conference on Computer Science and Network Technology, 2, 1345–1348.

    Google Scholar 

  71. Jin, K., Zhang, Y., & Tian, D. (2012). Based on the improvement of LEACH protocol for wireless sensor network routing algorithm. IEEE Conference on Intelligent System Design and Engineering Application (pp. 1525–1528).

  72. Manzoor, B., Javaid, N., Rehman, O., Akbar, M., Nadeem, Q., Iqbal, A., et al. (2013). Q-LEACH: A new routing protocol for WSNs. Procedia Computer Science, 19, 926–931.

    Article  Google Scholar 

  73. Wang, A., Yang, D., & Sun, D. (2012). A clustering algorithm based on energy information and cluster heads expectation for wireless sensor networks. Computers and Electrical Engineering, 38, 662–671.

    Article  Google Scholar 

  74. Thein, M., & Thein, T. (2010). An energy efficient cluster-head selection for wireless sensor networks. In IEEE Conference on Intelligent Systems, Modelling and Simulation (pp. 287–291).

  75. Hou, R., Ren, W., & Zhang, Y. (2009). A wireless sensor network clustering algorithm based on energy and distance. IEEE Workshop on Computer Science and Engineering, 1, 439–442.

    Google Scholar 

  76. Ren, P., Qian, J., Li, L., Zhao, Z., & Li, X. (2010). Unequal clustering scheme based leach for wireless sensor networks. In IEEE Conference on Genetic and Evolutionary Computing (pp. 90–93).

  77. So-In, C., Udompongsuk, K., Phudphut, C., Rujirakul, K., & Khunboa, C. (2013). Performance evaluation of LEACH on cluster head selection techniques in wireless sensor networks. In Springer Conference on Computing and Information Technology (pp. 51–61). Berlin, Heidelberg: Springer.

  78. Angurala, M., & Bharti. (2016). A comparative study between leach and pegasis—A review. In IEEE Conference on Computing for Sustainable Global Development (pp. 3271–3274).

  79. Misra, S., & Kumar, R. (2017). An analytical study of leach and pegasis protocol in wireless sensor network. In IEEE Conference on Innovations in Information, Embedded and Communication Systems (pp. 1–5).

  80. Sharma, I., Singh, R., & Khurana, M. (2015). Comparative study of leach, leach-c and pegasis routing protocols for wireless sensor network. In IEEE Conference on Advances in Computer Engineering and Applications (pp. 842–846).

  81. Miorandi, D., Sicari, S., Pellegrini, F. D., & Chlamtac, I. (2012). Internet of things: Vision, applications and research challenges. Elseiver Ad Hoc Networks, 10(7), 1497–1516.

    Article  Google Scholar 

  82. Patel, N., & Kumar, S. (2018) Wireless sensor networks—Challenges and future prospects. In IEEE Conference on System Modeling Advancement in Research Trends (SMART) (pp. 60–65).

  83. Ninikrishna, T., Sarkar, S., Tengshe, R., Jha, M., Sharma, L., Daliya, V., et al. (2017). Software defined iot: Issues and challenges. In IEEE Conference on Computing Methodologies and Communication (ICCMC) (pp. 723–726).

  84. Lu, Y., & Xu, L. (2019). Internet of things (iot) cybersecurity research: A review of current research topics. IEEE Internet of Things Journal, 6(2), 2103–2115.

    Article  Google Scholar 

  85. Alagar, V., Alsaig, A., Ormandjiva, O., & Wan, K. (2018). Context-based security and privacy for healthcare iot. In IEEE Conference on Smart Internet of Things (pp. 122–128).

  86. Afolabi, D., Man, K. L., Liang, H.-N., Lim, E. G., Shen, Z., Lei, C.-U., et al. (2013). A WSN approach to unmanned aerial surveillance of traffic anomalies: Some challenges and potential solutions. In IEEE East-West Design Test Symposium (pp. 1–4).

  87. Bera, S., Misra, S., Roy, S. K., & Obaidat, M. S. (2018). Soft-WSN: Software-defined WSN management system for IoT applications. IEEE Systems Journal, 12(3), 2074–2081.

    Article  Google Scholar 

  88. Zhang, Y., Sun, L., Song, H., & Cao, X. (2014). Ubiquitous wsn for healthcare: Recent advances and future prospects. IEEE Internet of Things Journal, 1(4), 311–318.

    Article  Google Scholar 

  89. Mir, A., & Khachane, A. (2018). Sensing harmful gases in industries using IoT and WSN. In IEEE Conference on Computing Communication Control and Automation (pp. 1–3).

  90. Seah, W. K. G., Eu, Z. A., & Tan, H. (2018). Wireless sensor networks powered by ambient energy harvesting (WSN-heap)—Survey and challenges. IEEE Conference on Wireless Communication, Information Theory and Aerospace Electronic Systems Technology: Vehicular Technology (pp. 1–5).

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  1. School of Engineering, RMIT University, Melbourne, 3000, Australia

    Louie Chan, Karina Gomez Chavez, Heiko Rudolph & Akram Hourani

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  1. Louie Chan
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Correspondence to Karina Gomez Chavez.

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This article is dedicated to the memory of Dr. Heiko Rudolph, our lovely friend and colleague full of positive energy.

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Chan, L., Gomez Chavez, K., Rudolph, H. et al. Hierarchical routing protocols for wireless sensor network: a compressive survey. Wireless Netw 26, 3291–3314 (2020). https://doi.org/10.1007/s11276-020-02260-z

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