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A Survey on Analytical Modeling and Mitigation Techniques for the Energy Hole Problem in Corona-Based Wireless Sensor Network

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Abstract

Wireless sensor networks (WSNs) have attracted much attention in recent years. In the many-to-one WSNs, the nodes located around the sink relay the data from other sensor nodes, which depletes their energy more quickly, resulting in energy holes and hot spot areas. When an energy hole appears, data cannot be sent from other sensors to the sink even though most of the sensors still have energy. In this paper, we generally classified the schemes proposed for solving the energy hole problem. In addition, we investigated the basic mathematical modeling of network connectivity and coverage, energy consideration, and optimum width of coronas in the corona-based WSNs.

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References

  1. Perillo, M., Cheng, Z., & Heinzelman, W. (2005). An analysis of strategies for mitigating the sensor network hot spot problem. In The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, 2005. MobiQuitous 2005.

  2. Xiaobing, W., Guihai, C., & Das, S. K. (2008). Avoiding energy holes in wireless sensor networks with nonuniform node distribution. IEEE Transactions on Parallel and Distributed Systems, 19(5), 710–720.

    Article  Google Scholar 

  3. Chen, Y., & Zhao, Q. (2005). On the lifetime of wireless sensor networks. IEEE Communications Letters, 9(11), 976–978.

    Article  Google Scholar 

  4. Heinzelman, W., Kulik, J., & Balakrishnan, H. (2002). Negotiation-based protocols for disseminating information in wireless sensor networks. Wireless Networks, 8(2), 169–185.

    MATH  Google Scholar 

  5. Anastasi, G., et al. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks, 7(3), 537–568.

    Article  Google Scholar 

  6. Santi, P. (2005). Topology control in wireless ad hoc and sensor networks. ACM Computing Surveys (CSUR), 37(2), 164–194.

    Article  Google Scholar 

  7. Koushanfar, F., Taft, N., & Potkonjak, M. (2006). Sleeping coordination for comprehensive sensing using isotonic regression and domatic partitions. In INFOCOM 2006, 25th IEEE.

  8. Schurgers, C., Tsiatsis, V., & Srivastava, M.B. (2002). STEM: Topology management for energy efficient sensor networks. In Aerospace Conference Proceedings, 2002. IEEE.

  9. Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE.

  10. Demirkol, I., Ersoy, C., & Alagoz, F. (2006). MAC protocols for wireless sensor networks: A survey. IEEE Communications Magazine, 44(4), 115–121.

    Article  Google Scholar 

  11. Kredo, K., & Mohapatra, P. (2007). Medium access control in wireless sensor networks. Computer Networks, 51(4), 961–994.

    Article  MATH  Google Scholar 

  12. Yadav, R., Varma, S., & Malaviya, N. (2009). A survey of MAC protocols for wireless sensor networks. UbiCC Journal, 4(3), 827–833.

    Google Scholar 

  13. Singh, S. K., Singh, M. P., & Singh, D. K. (2010). A survey of energy-efficient hierarchical cluster-based routing in wireless sensor networks. International Journal of Advanced Networking and Application, 02(02), 570–580.

    Google Scholar 

  14. Alzaid, H., Foo, E., & Nieto, J.G. (2008). Secure data aggregation in wireless sensor network: A survey. In Proceedings of the sixth Australasian conference on Information security-Volume 81. Australian Computer Society Inc., 2008.

  15. Tang, C., & Raghavendra, C. (2004). Compression techniques for wireless sensor networks. In Wireless sensor networks (pp. 207–231) Springer.

  16. Pradhan, S. S., & Ramchandran, K. (2003). Distributed source coding using syndromes (DISCUS): Design and construction. IEEE Transactions on Information Theory, 49(3), 626–643.

    Article  MATH  MathSciNet  Google Scholar 

  17. Ilyas, M., Mahgoub, I., & Kelly, L. (2005). Handbook of sensor networks: Compact wireless and wired sensing systems. 2005. Boca Raton, FL, USA: CRC Press Inc.

    Google Scholar 

  18. Jae-Joon, L., Krishnamachari, B., & Kuo, C.C.J. (2004). Impact of heterogeneous deployment on lifetime sensing coverage in sensor networks. In Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004. 2004 First Annual IEEE Communications Society Conference on.

  19. Bandyopadhyay, S., & Coyle, E. J. (2004). Minimizing communication costs in hierarchically-clustered networks of wireless sensors. Computer Networks, 44(1), 1–16.

    Article  Google Scholar 

  20. Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30(14–15), 2826–2841.

    Article  Google Scholar 

  21. 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 

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

    Article  Google Scholar 

  23. Gupta, G., & Younis, M. (2003). Fault-tolerant clustering of wireless sensor networks. In Wireless Communications and Networking, 2003. WCNC 2003. 2003 IEEE.

  24. Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3(4), 366–379.

    Article  Google Scholar 

  25. Bekara, C., Laurent-Maknavicius, M., & Bekara, K. (2007). SAPC: A secure aggregation protocol for cluster-based wireless sensor networks. In Mobile Ad-Hoc and Sensor Networks (pp. 784–798).

  26. Çam, H., et al. (2006). Energy-efficient secure pattern based data aggregation for wireless sensor networks. Computer Communications, 29(4), 446–455.

    Article  Google Scholar 

  27. Fragouli, C., Le Boudec, J. Y., & Widmer, J. (2006). Network coding: An instant primer. ACM SIGCOMM Computer Communication Review, 36(1), 63–68.

    Article  Google Scholar 

  28. Soro, S., & Heinzelman, W.B. (2005). Prolonging the lifetime of wireless sensor networks via unequal clustering. In Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International.

  29. Luo, J., & Hubaux, J.P. (2005). Joint mobility and routing for lifetime elongation in wireless sensor networks. In INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE.

  30. Bi, Y., et al. (2007). HUMS: An autonomous moving strategy for mobile sinks in data-gathering sensor networks. EURASIP Journal on Wireless Communications and Networking, 2007, 064574.

  31. Marta, M., & Cardei, M. (2008). Using sink mobility to increase wireless sensor networks lifetime. In World of Wireless, Mobile and Multimedia Networks, 2008. WoWMoM 2008. 2008 International Symposium on a. IEEE.

  32. Wu, X., & Chen, G. (2007). Dual-sink: Using mobile and static sinks for lifetime improvement in wireless sensor networks. In Computer Communications and Networks, 2007. ICCCN 2007. Proceedings of 16th International Conference on. IEEE.

  33. Gatzianas, M., & Georgiadis, L. (2008). A distributed algorithm for maximum lifetime routing in sensor networks with mobile sink. IEEE Transactions on Wireless Communications, 7(3), 984–994.

    Article  Google Scholar 

  34. Heo, J., Hong, J., & Cho, Y. (2009). EARQ: Energy aware routing for real-time and reliable communication in wireless industrial sensor networks. IEEE Transactions on Industrial Informatics, 5(1), 3–11.

    Article  Google Scholar 

  35. Perillo, M., & Heinzelman, W. (2009). An integrated approach to sensor role selection. IEEE Transactions on Mobile Computing, 8(5), 709–720.

    Article  Google Scholar 

  36. Luo, J., et al. (2006). Mobiroute: Routing towards a mobile sink for improving lifetime in sensor networks. In Distributed Computing in Sensor Systems (pp. 480–497).

  37. Li, J., & Mohapatra, P. (2005). An analytical model for the energy hole problem in many-to-one sensor networks. In IEEE; 1999.

  38. Yunhuai, L., Hoilun, N., & Ni, L.M. (2006). Power-aware node deployment in wireless sensor networks. In Sensor Networks, Ubiquitous, and Trustworthy Computing, 2006. IEEE International Conference on.

  39. Xiaobing, W., Guihai, C., & Sajal, K.D. (2006). On the energy hole problem of nonuniform node distribution in wireless sensor networks. In Mobile Adhoc and Sensor Systems (MASS), 2006 IEEE International Conference on.

  40. Jarry, A., et al. (2006). An optimal data propagation algorithm for maximizing the lifespan of sensor networks distributed computing in sensor systems. Berlin, Heidelberg: Springer.

    Google Scholar 

  41. Ferng, H., Hadiputro, M., & Kurniawan, A. (2011). Design of novel node distribution strategies in corona-based wireless sensor networks. IEEE Transactions on Mobile Computing, 99, 1–1.

    Google Scholar 

  42. Liu, X., & Mahapatra, P. (2005). On the deployment of wireless sensor nodes. In Proceedings of the 3rd International Workshop on Measurement, Modeling, and Performance Analysis of Wireless Sensor Networks, in Conjunction with the 2nd Annual International Conference on Mobile and Ubiquitous Systems.

  43. Atiq Ur, R., Hasbullah, H., & Najm Us, S. (2012). Impact of Gaussian deployment strategies on the performance of wireless sensor network. In Computer & Information Science (ICCIS), 2012 International Conference on.

  44. Liu, T. (2013). Avoiding energy holes to maximize network lifetime in gradient sinking sensor networks. Wireless Personal Communications, 70(2), 581–600.

  45. Hou, Y. T., et al. (2005). On energy provisioning and relay node placement for wireless sensor networks. IEEE Transactions on Wireless Communications, 4(5), 2579–2590.

    Article  Google Scholar 

  46. Sheldon, M., et al. (2005). A practical approach to deploy large scale wireless sensor networks. In: Mobile Adhoc and Sensor Systems Conference, 2005. IEEE International Conference on.

  47. Iranli, A., Maleki, M., & Pedram, M. (2005). Energy efficient strategies for deployment of a two-level wireless sensor network. In Proceedings of the 2005 international symposium on Low power electronics and design. ACM.

  48. Esseghir, M., Bouabdallah, N., & Pujolle, G. (2007). Energy provisioning model for maximizing wireless sensor network lifetime. In Global Information Infrastructure Symposium, 2007. GIIS 2007. First International. IEEE.

  49. Lian, J., et al. (2004). Modeling and enhancing the data capacity of wireless sensor networks. IEEE Monograph on Sensor Network Operations, 91–138.

  50. Cheng, P., Chuah, C.N., & Liu, X. (2004). Energy-aware node placement in wireless sensor networks. In Global Telecommunications Conference, 2004. GLOBECOM’04. IEEE. IEEE.

  51. Halder, S., Ghosal, A., & Bit, S. D. (2011). A pre-determined node deployment strategy to prolong network lifetime in wireless sensor network. Computer Communications, 34(11), 1294–1306.

    Article  Google Scholar 

  52. Quanhong, W., et al. (2006). On lifetime-oriented device provisioning in heterogeneous wireless sensor networks: Approaches and challenges. IEEE Network, 20(3), 26–33.

    Article  Google Scholar 

  53. Wang, Q., et al. (2006). On lifetime-oriented device provisioning in heterogeneous wireless sensor networks: Approaches and challenges. IEEE Network, 20(3), 26–33.

    Article  MATH  Google Scholar 

  54. Kenan, X., et al. (2010). Relay node deployment strategies in heterogeneous wireless sensor networks. IEEE Transactions on Mobile Computing, 9(2), 145–159.

    Article  Google Scholar 

  55. Jing, L., et al. (2009). Regenerative cooperative diversity with path selection and equal power consumption in wireless networks. IEEE Transactions on Wireless Communications, 8(8), 3926–3932.

    Article  Google Scholar 

  56. Jiucai, Z., et al. (2009). A battery-aware deployment scheme for cooperative wireless sensor networks. In Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE.

  57. Suganthi, K., & Sundaram, B.V. (2012). A constraint based relay node deployment in heterogeneous wireless sensor networks for lifetime maximization. In Advanced Computing (ICoAC), 2012 Fourth International Conference on.

  58. Brazil, M., Ras, C., & Thomas, D. (2013). Relay augmentation for lifetime extension of wireless sensor networks. arXiv preprint arXiv:1301.4728.

  59. Bhardwaj, M., Garnett, T., & Chandrakasan, A.P. (2001). Upper bounds on the lifetime of sensor networks. In Communications, 2001. ICC 2001. IEEE International Conference on.

  60. Mhatre, V., & Rosenberg, C. (2004). Design guidelines for wireless sensor networks: Communication, clustering and aggregation. Ad Hoc Networks, 2(1), 45–63.

    Article  Google Scholar 

  61. Ammari, H. M., & Das, S. K. (2008). Promoting heterogeneity, mobility, and energy-aware voronoi diagram in wireless sensor networks. Parallel and Distributed Systems, IEEE Transactions on, 19(7), 995–1008.

  62. Lin, F. T., Shiu, L. C., Lee, C. Y., & Yang, C. S. (2013). A method to analyze the effectiveness of the holes healing scheme in wireless sensor network. International Journal of Distributed Sensor Networks, 2013.

  63. Guo, W., Liu, Z., & Wu, G. (2003). An energy-balanced transmission scheme for sensor networks. In Proceedings of the 1st international conference on Embedded networked sensor systems. ACM.

  64. Leone, P., & Rolim, J. (2004). Towards a dynamical model for wireless sensor networks. In Algorithmic Aspects of Wireless Sensor Networks (pp. 98–108).

  65. Liu, Z., Xiu, D., & Guo, W. (2005). An energy-balanced model for data transmission in sensor networks. In Vehicular Technology Conference, 2005. VTC-2005-Fall. 2005 IEEE 62nd. IEEE.

  66. Bhardwaj, M., & Chandrakasan, A.P. (2002). Bounding the lifetime of sensor networks via optimal role assignments. In INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE.

  67. Olariu, S., & Stojmenovic, I. (2006). Design guidelines for maximizing lifetime and avoiding energy holes in sensor networks with uniform distribution and uniform reporting.

  68. Leone, P., Nikoletseas, S., & Rolim, J. (2010). Stochastic models and adaptive algorithms for energy balance in sensor networks. Theory of Computing Systems, 47(2), 433–453.

    Article  MATH  MathSciNet  Google Scholar 

  69. Charilaos, E., Sotiris, N., & Jose, R. (2006). Energy balanced data propagation in wireless sensor networks. Wireless Networks, 12(6), 691–707.

    Article  Google Scholar 

  70. Jarry, A., et al. (2006). An optimal data propagation algorithm for maximizing the lifespan of sensor networks. In Distributed Computing in Sensor Systems (pp. 405–421).

  71. Giridhar, A., & Kumar, P. (2005). Maximizing the functional lifetime of sensor networks. Piscataway: IEEE Press.

    Google Scholar 

  72. Ritesh, M., et al. (2007). Modeling and optimization of transmission schemes in energy-constrained wireless sensor networks. IEEE/ACM Transactions on Networking, 15(6), 1359–1372.

    Article  Google Scholar 

  73. Ferentinos, K. P., & Tsiligiridis, T. A. (2007). Adaptive design optimization of wireless sensor networks using genetic algorithms. Computer Networks, 51(4), 1031–1051.

    Article  MATH  Google Scholar 

  74. Zhang, H., Shen, H., & Tan, Y. (2007). Optimal energy balanced data gathering in wireless sensor networks. In Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International.

  75. Powell, O., Leone, P., & Rolim, J. (2007). Energy optimal data propagation in wireless sensor networks. Journal of Parallel and Distributed Computing, 67(3), 302–317.

    Article  MATH  Google Scholar 

  76. Song, C., et al. (2009). Maximizing network lifetime based on transmission range adjustment in wireless sensor networks. Computer Communications, 32(11), 1316–1325.

    Article  Google Scholar 

  77. Ammari, H. M., & Das, S. K. (2008). Promoting heterogeneity, mobility, and energy-aware voronoi diagram in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 19(7), 995–1008.

    Article  Google Scholar 

  78. Haibo, Z., & Hong, S. (2009). Balancing energy consumption to maximize network lifetime in data-gathering sensor networks. IEEE Transactions on Parallel and Distributed Systems, 20(10), 1526–1539.

    Article  Google Scholar 

  79. Azad, A. K. M., & Kamruzzaman, J. (2011). Energy-balanced transmission policies for wireless sensor networks. IEEE Transactions on Mobile Computing, 10(7), 927–940.

    Article  Google Scholar 

  80. Chen, Y., et al. (2012). Mitigating energy holes in wireless sensor networks using cooperative communication. In Personal Indoor and Mobile Radio Communications (PIMRC), 2012 IEEE 23rd International Symposium on..

  81. Thanigaivelu, K., & Murugan, K. (2012). K-level based transmission range scheme to alleviate energy hole problem in WSN. In Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology. ACM.

  82. Bhardwaj, M., Garnett, T., Chandrakasan, A.P. (2001) Upper bounds on the lifetime of sensor networks. In IEEE.

  83. Rappaport, T. (1996). Wireless communications: Principles and practice. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  84. Dietrich, I., & Dressler, F. (2009). On the lifetime of wireless sensor networks. ACM Transactions on Sensor Networks, 5(1), 1–39.

    Article  Google Scholar 

  85. Stojmenovi, I., & Olariu, S. (2005). Data centric protocols for wireless sensor networks. In Handbook of Sensor Networks (pp 417–456).

  86. Wang, Y., & Jing, Y. (2012). An optimal energy balance strategy to maximize network lifetime in wireless sensor networks\(\star \). Journal of Computational Information Systems, 8(1), 107–114.

    MathSciNet  Google Scholar 

  87. Mhatre, V. P., et al. (2005). A minimum cost heterogeneous sensor network with a lifetime constraint. IEEE Transactions on Mobile Computing, 4(1), 4–15.

    Article  Google Scholar 

  88. Li, H., et al. (2013). COCA: Constructing optimal clustering architecture to maximize sensor network lifetime. Computer Communications, 36(3), 256–268.

    Article  Google Scholar 

  89. Mhatre, V., Rosenberg, C. (2004). Homogeneous vs heterogeneous clustered sensor networks: A comparative study. In Communications, 2004 IEEE International Conference on.

  90. Shakkottai, S., Srikant, R., & Shroff, N. (2003). Unreliable sensor grids: Coverage, connectivity and diameter. In INFOCOM 2003.

  91. Gupta, P., & Kumar, P.R. (1998). Critical power for asymptotic connectivity. In Decision and Control, 1998. Proceedings of the 37th IEEE Conference on.

  92. Jennifer Yick, B. M., & Ghosal, D. (2008). Wireless sensor network survey. Amsterdam: Elsevier.

    Google Scholar 

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Acknowledgments

This research was sponsored by National Advanced IPv6 Centre, Universiti Sains Malaysia through Grant No. 304/PNAV/6312093.

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Correspondence to Hadi Asharioun.

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Asharioun, H., Asadollahi, H., Wan, TC. et al. A Survey on Analytical Modeling and Mitigation Techniques for the Energy Hole Problem in Corona-Based Wireless Sensor Network. Wireless Pers Commun 81, 161–187 (2015). https://doi.org/10.1007/s11277-014-2122-3

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