Skip to main content

Advertisement

Log in

Survey on Wireless Sensor Network Applications and Energy Efficient Routing Protocols

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Wireless sensor network (WSN) is a group of small power-constrained nodes that sense data and communicate it to the base station (BS). These nodes cover a vast region of interest (ROI) for several purposes according to the application need. The first challenge encountered in WSNs is how to cover the ROI perfectly and send the monitored data to the BS. Although the energy introduced during setup phase and the violation of energy fairness constraint of dynamic routing topologies, they achieve high network performance in terms of coverage and connectivity. In this paper, we categorize the applications of WSN based on different aspects to show the major protocol design issues. Thus, the energy efficiency of the recent proactive routing protocols is studied from different angles. The energy overhead and energy fairness of each protocol were carefully analyzed. The most energy efficient routing protocols for homogeneous proactive networks were studied and compared to highlight the research challenges and existing problems in this area. The results proved that energy overhead and route selection are the most effective aspects of network lifetime and network efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Willig, A., Matheus, K., & Wolisz, A. (2005). Wireless technology in industrial networks. Proceedings of the IEEE, 93(6), 1130–1151.

    Article  Google Scholar 

  2. Sazonov, E. (2016). Wireless intelligent sensor network for autonomous structural health monitoring. In Proceedings of the SPIE (Vol. 5384, pp. 305–314).

  3. Wang, J., Niu, Y., Cho, J., & Lee, S. (2007). Analysis of energy consumption in direct transmission and multi-hop transmission for wireless sensor networks. In 2007 3rd international IEEE conference on signal-image technology and internet-based systems (pp. 275–280).

  4. Mhatre, V., & Rosenberg, C., Mhatre, V., & Rosenberg, C. (2004). Homogeneous vs heterogeneous clustered sensor networks: A comparative study. In 2004 IEEE international conference on communications (IEEE Cat. No. 04CH37577) (Vol. 6, pp. 1–6) http://dx.doi.org/10.1109/ICC.2004.1313223. Homogeneo.

  5. Yuan, H.-Y., Dai, J.-G., & Li, X.-L. (2007). An energy-efficient clustering algorithm in wireless sensor networks. Chinese Journal of Sensors Actuators, 20(12), 131–142.

    Google Scholar 

  6. Yun, Y., Member, S., & Xia, Y. (2010). Maximizing the lifetime of wireless sensor networks with mobile sink in delay-tolerant applications. IEEE Transactions on Mobile Computing, 9(9), 1308–1318.

    Article  Google Scholar 

  7. Waheed Khan, A., Abdullah, A. H., Anisi, M. H., & Iqbal Bangash, J. (2014). A comprehensive study of data collection schemes using mobile sinks in wireless sensor networks. Sensors (Switzerland), 14(2), 2510–2548.

    Article  Google Scholar 

  8. Lenzini, L., Martorini, L., Mingozzi, E., & Stea, G. (2006). Tight end-to-end per-flow delay bounds in FIFO multiplexing sink-tree networks. Performance Evaluation, 63(9–10), 956–987.

    Article  Google Scholar 

  9. Liang, W., Luo, J., & Xu, X. (2010). Prolonging network lifetime via a controlled mobile sink in wireless sensor networks. In GLOBECOMIEEE global telecommunication conference.

  10. Mudumbai, R., Brown, D. R., Madhow, U., & Poor, H. V. (2009). Distributed transmit beamforming: Challenges and recent progress. IEEE Communications Magazine, 47(2), 102–110.

    Article  Google Scholar 

  11. Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. In 2nd international workshop on sensor and actor network protocols and application (SANPA 2004) (pp. 1–11).

  12. Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: A survey on recent developments and potential synergies. The Journal of Supercomputing, 68(1), 1–48.

    Article  Google Scholar 

  13. Naeimi, S., Ghafghazi, H., Chow, C. O., & Ishii, H. (2012). A survey on the taxonomy of cluster-based routing protocols for homogeneous wireless sensor networks. Sensors (Switzerland), 12(6), 7350–7409.

    Article  Google Scholar 

  14. Singh, S. P., & Sharma, S. C. (2015). A survey on cluster based routing protocols in wireless sensor networks. Procedia Computer Science, 45(C), 687–695.

    Article  Google Scholar 

  15. García-hernández, C. F., Ibargüengoytia-gonzález, P. H., García-hernández, J., & Pérez-díaz, J. A. (2007). Wireless sensor networks and applications: A survey. Journal of Computer Science, 7(3), 264–273.

    Google Scholar 

  16. Shi, E., & Perrig, A. (2004). Designing secure sensor networks. IEEE Wireless Communications, 11(6), 38–43.

    Article  Google Scholar 

  17. Rault, T., Bouabdallah, A., Challal, Y., Rault, T., Bouabdallah, A., Challal, Y., et al. (2014). Energy efficiency in wireless sensor networks: a top-down survey. Computer Network, 67, 104–122.

    Article  Google Scholar 

  18. Khan, J. A., Qureshi, H. K., & Iqbal, A. (2016). Energy management in wireless sensor networks: A survey. Computers & Electrical Engineering, 41, 159–176.

    Article  Google Scholar 

  19. Anisi, M. H., Abdul-Salaam, G., & Abdullah, A. H. (2015). A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Precision Agriculture, 16(2), 216–238.

    Article  Google Scholar 

  20. Asharioun, H., Asadollahi, H., Wan, T. C., & Gharaei, N. (2015). A survey on analytical modeling and mitigation techniques for the energy hole problem in corona-based wireless sensor network. Wireless Personal Communications, 81(1), 161–187.

    Article  Google Scholar 

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

    Article  Google Scholar 

  22. Maimour, M., Zeghilet, H., & Lepage, F. (2010). Cluster-based routing protocols for energy efficiency in wireless sensor networks. Sustainable Wireless Sensor Networks. https://doi.org/10.5772/13274.

    Article  Google Scholar 

  23. Balen, J., Zagar, D., & Martinovic, G. (2011). Quality of service in wireless sensor networks: A survey and related patents. Recent Patents on Computer Science, 4(3), 188–202.

    Google Scholar 

  24. Liu, X. (2012). A survey on clustering routing protocols in wireless sensor networks. Sensors, 12(8), 11113–11153.

    Article  Google Scholar 

  25. Pantazis, N. A., Nikolidakis, S. A., Vergados, D. D., & Member, S. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 15(2), 551–591.

    Article  Google Scholar 

  26. Curry, R. M., Smith, J. C., Curry, R. M., Hall, F., & Hall, F. (2016). A survey of optimization algorithms for wireless sensor network lifetime maximization. Computers & Industrial Engineering, 101, 145–166. https://doi.org/10.1016/j.cie.2016.08.028.

    Article  Google Scholar 

  27. Gungor, V. C., Hancke, G. P., & Member, S. (2009). Industrial wireless sensor networks: Challenges, design principles, and technical approaches. IEEE Transactions on Industrial Electronics, 56(10), 4258–4265.

    Article  Google Scholar 

  28. Lee, I., & Lee, K. (2015). The internet of things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431–440.

    Article  Google Scholar 

  29. Bhatti, S., & Xu, J. X. J. (2009). Survey of target tracking protocols using wireless sensor network. In 2009 5th international conference on wireless and mobile communications (pp. 110–115).

  30. Barrenetxea, G., Ingelrest, F., Schaefer, G., Vetterli, M., Couach, O., & Parlange, M. (2008). SensorScope: Out-of-the-box environmental monitoring. In Proceedings of the 2008 international conference on information processing in sensor networks, IPSN 2008 (pp. 332–343).

  31. Balister, P., & Kumar, S. (2009). Random vs. deterministic deployment of sensors in the presence of failures and placement errors. In Proceedings of the IEEE INFOCOM, Section III (pp. 2896–2900).

  32. Halder, S., & Ghosal, A. (2016). A location-wise predetermined deployment for optimizing lifetime in visual sensor networks. IEEE Transactions on Circuits and Systems for Video Technology, 26(6), 1131–1145.

    Article  Google Scholar 

  33. Zou, Y., & Chakrabarty, K. (2003). Sensor deployment and target localization based on virtual forces. In 22nd annual joint conference of the IEEE computer and communications (Vol. 2, no. C, pp. 1293–1303).

  34. Wang, X., Wang, S., & Ma, J. (2006). Dynamic deployment optimization in wireless sensor networks in wireless sensor networks. Optimization, 1, 182–187.

    MATH  Google Scholar 

  35. Jovanov, E., & Milenkovic, A. (2011). Body area networks for ubiquitous healthcare applications: Opportunities and challenges. Journal of Medical Systems, 35(5), 1245–1254.

    Article  Google Scholar 

  36. Akyildiz, I. F., & Stuntebeck, E. P. (2006). Wireless underground sensor networks: Research challenges. Ad Hoc Networks, 4(6), 669–686.

    Article  Google Scholar 

  37. Felemban, E., Shaikh, F. K., Qureshi, U. M., Sheikh, A. A., & Bin Qaisar, S. (2015). Underwater sensor network applications: A comprehensive survey. International Journal of Distributed Sensor Networks, 11, 896832.

    Article  Google Scholar 

  38. Akyildiz, I. F., Wang, P., & Lin, S. C. (2015). SoftWater: Software-defined networking for next-generation underwater communication systems. Ad Hoc Networks, 46, 1–11.

    Article  Google Scholar 

  39. Bokareva, T., Hu, W., Kanhere, S., Ristic, B., & Wales, N. S. (2006). Wireless sensor networks for battlefield surveillance. In Signal processing (pp. 1–5).

  40. Lazarescu, M. T. (2013). Design of a WSN platform for long-term environmental monitoring for IoT applications. The IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 3(1), 45–54.

    Article  Google Scholar 

  41. Yang, Z., Li, M., & Liu, Y. (2007). Sea depth measurement with restricted floating sensors. In Proceedings of the real-time systems symposium (Vol. 13, no. 1, pp. 469–478).

  42. Spachos, P., & Hatzinakos, D. (2013). Prototypes of opportunistic wireless sensor networks supporting indoor air quality monitoring. In 2013 IEEE 10th consumer, communications and networks conference (pp. 851–852).

  43. Magno, M., Polonelli, T., Benini, L., & Popovici, E. (2015). A low cost, highly scalable wireless sensor network solution to achieve smart LED light control for green buildings. IEEE Sensors Journal, 15(5), 2963–2973.

    Article  Google Scholar 

  44. Kumar, P., Kumar, P., & Priyadarshini, P. (2012). Underwater acoustic sensor network for early warning generation. In Ocean, 2012 (pp. 1–6).

  45. Al-Fares, M. S., & Sun, Z. (2009). Self-organizing routing protocol to achieve QoS in wireless sensor network for forest fire monitoring. In Proceedings of IEEE 9th Malaysia international conference on communications with a special workshop on digital TV contents, MICC 2009 (pp. 211–216).

  46. Zhang, Q., Li, J., Rong, J., Xu, W., & He, J. (2011). Application of WSN in precision forestry. In Proceedings of IEEE 2011 10th international conference on electronic measurement and instruments, ICEMI 2011 (Vol. 4, pp. 320–323).

  47. Werner-Allen, G., Lorincz, K., Welsh, M., Marcillo, O., Johnson, J., Ruiz, M., et al. (2006). Deploying a wireless sensor network on an active volcano. IEEE Internet Computing, 10(2), 18–25.

    Article  Google Scholar 

  48. Nachtigall, J., & Redlich, J. (2011). Wireless alarming and routing protocol for earthquake early warning systems. In 4th IFIP international conference on new technologies, mobility and security, 2011 (pp. 1–6).

  49. Khedo, K. K., Perseedoss, R., & Mungur, A. (2010). A wireless sensor network air pollution monitoring system. International Journal of Wireless & Mobile Networks, 2(2), 31–45. https://doi.org/10.5121/ijwmn.2010.2203.

    Article  Google Scholar 

  50. Polastre, J., Szewczyk, R., Mainwaring, A., Culler, D., & Anderson, J. (2004). Chapter 18 analysis of wireless sensor networks for habitat monitoring. In Wireless sensor networks (pp. 399–423).

  51. Wark, T., Swain, D., Crossman, C., Valencia, P., Bishop-Hurley, G., & Handcock, R. (2009). Sensor and actuator networks: Protecting environmentally sensitive areas. IEEE Pervasive Computing, 8(1), 30–36.

    Article  Google Scholar 

  52. Coates, R. W., Delwiche, M. J., Broad, A., & Holler, M. (2013). Wireless sensor network with irrigation valve control. Computers and Electronics in Agriculture, 96, 13–22.

    Article  Google Scholar 

  53. Dong, X., Vuran, M. C., & Irmak, S. (2013). Autonomous precision agriculture through integration of wireless underground sensor networks with center pivot irrigation systems. Ad Hoc Networks, 11(7), 1975–1987.

    Article  Google Scholar 

  54. Yu, X., Wu, P., Han, W., & Zhang, Z. (2013). A survey on wireless sensor network infrastructure for agriculture. Computer Standards & Interfaces, 35(1), 59–64.

    Article  Google Scholar 

  55. He, T., Vicaire, P., Yan, T., Cao, Q., Zhou, G., Gu, L., Luo, L., Stoleru, R., Stankovic, J. A., & Abdelzaher, T. F. (2006). Achieving long-term surveillance in VigilNet. In Proceedings of IEEE INFOCOM (Vol. V).

  56. Zhang, P., Sadler, C. M., Lyon, S. A., & Martonosi, M. (2004). Hardware design experiences in ZebraNet. In Proceedings of the 2nd international conference on embedded networked sensor systemsSenSys ’04 (Vol. 7, p. 227).

  57. Butler, Z., Corke, P., Peterson, R., & Rus, D. (2006). From robots to animals: Virtual fences for controlling cattle. The International Journal of Robotics Research, 25(5–6), 485–508.

    Article  Google Scholar 

  58. Naumowicz, T., Freeman, R., Heil, A., Calsyn, M., Hellmich, E., Brändle, A., Guilford, T., & Schiller, J. (2008). Autonomous monitoring of vulnerable habitats using a wireless sensor network. In Proceedings of the workshop on real-world wireless sensor networksREALWSN ’08 (p. 51).

  59. Vellidis, G., Tucker, M., Perry, C., Kvien, C., & Bednarz, C. (2008). A real-time wireless smart sensor array for scheduling irrigation. Computers and Electronics in Agriculture, 61(1), 44–50.

    Article  Google Scholar 

  60. Lamont, L., Toulgoat, M., Ezie, M. D., & Patterson, G. (2011). Tiered wireless sensor network architecture for military surveillance applications. In SENSORCOMM 2011, 5th international conference on bio-sensing technology (pp. 288–294).

  61. Ball, M. G., Qela, B., & Wesolkowski, S. (2016). A review of the use of computational intelligence in the design of military surveillance networks. Studies in Computational Intelligence, 621, 663–693.

    Google Scholar 

  62. Sun, B., & Osborne, L. (2007). Intrusion detection techniques in mobile adhoc and wireless sensor networks. Lamar University (pp. 56–63).

  63. Wang, Y. W. Y., Wang, X. W. X., Bin Xie, B. X., Wang, D. W. D., & Agrawal, D. P. (2008). Intrusion detection in homogeneous and heterogeneous wireless sensor networks. IEEE Transactions on Mobile Computing, 7(6), 698–711.

    Article  Google Scholar 

  64. He, T., Krishnamurthy, S., Stankovic, J. A., Abdelzaher, T. F., Luo, L., Stoleru, R., et al. (2004). Energy-efficient surveillance system using wireless sensor networks. In Proceedings of the 2nd international conference on mobile systems, applications, and services - MobiSYS '04.

  65. Díaz-Michelena, M. (2009). Small magnetic sensors for space applications. Sensors, 9(4), 2271–2288.

    Article  Google Scholar 

  66. Lee, S. H. L., Lee, S., Song, H., & Lee, H. S. (2009). Wireless sensor network design for tactical military applications: Remote large-scale environments. In MILCOM 20092009 IEEE military communications conference (Vol. 19, pp. 1–7).

  67. DeBardelaben, J. A. (2003). Multimedia sensor networks for ISR applications. In Conference record of the thirty-seventh Asilomar conference on signals, systems, and computers, 2004 (Vol. 2, pp. 2009–2012).

  68. Caiti, A., Calabrò, V., Munafò, A., Dini, G., & Duca, A. L. (2013). Mobile underwater sensor networks for protection and security: Field experience at the UAN11 experiment. Journal of Field Robotics, 30(2), 237–253. https://doi.org/10.1002/rob.21447.

    Article  Google Scholar 

  69. Manvi, S. S. (2013). Coverage optimization based sensor deployment by using PSO for anti-submarine detection in UWASNs (pp. 15–22).

  70. Pantelopoulos, A. & Bourbakis, N. G. (2010). A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 40(1), 1–12.

    Article  Google Scholar 

  71. Al Ameen, M., Liu, J., & Kwak, K. (2012). Security and privacy issues in wireless sensor networks for healthcare applications. Journal of Medical Systems, 36(1), 93–101.

    Article  Google Scholar 

  72. Yoo, J., Yan, L., Lee, S., Kim, Y., & Yoo, H.-J. (2010). A 5.2 mW self-configured wearable body sensor network controller and a 12 uW wirelessly powered sensor for a continuous health monitoring system. IEEE Journal of Solid-State Circuits, 45(1), 178–188. https://doi.org/10.1109/jssc.2009.2034440.

    Article  Google Scholar 

  73. Lorincz, K., Malan, D. J., Jones, T. R., Nawoj, A., Clavel, A., Shnayder, V., et al. (2004). Sensor networks for emergency response: Challenges and opportunities. IEEE Pervasive Computing, 3, 16–23.

    Article  Google Scholar 

  74. Ko, J., Gao, T., Rothman, R., & Terzis, A. (2010). Wireless sensing systems in clinical environments: Improving the efficiency of the patient monitoring process. IEEE Engineering in Medicine and Biology Magazine, 29(2), 103–109.

    Article  Google Scholar 

  75. Tennina, S., Santos, M. F., Mesodiakaki, A., Mekikis, P., Kartsakli, E., Antonopoulos, A., et al. (2016). WSN4QoL: WSNs for remote patient monitoring in e-Health applications. 2016 IEEE International Conference on Communications (ICC), 1–6.

  76. Mikhaylov, K., Tervonen, J., Heikkila, J., & Kansakoski, J. (2012). Wireless sensor networks in industrial environment: Real-life evaluation results. In 2nd Baltic congress on future internet communications (BCFIC), 2012 (pp. 1–7).

  77. Hodge, V. J., Keefe, S. O., Weeks, M., & Moulds, A. (2015). Wireless sensor networks for condition monitoring in the railway industry: A survey. IEEE Transactions on Intelligent Transportation Systems, 16(3), 1088–1106.

    Article  Google Scholar 

  78. Erol-Kantarci, M., & Mouftah, H. T. (2015). Energy-efficient information and communication infrastructures in the smart grid: A survey on interactions and open issues. IEEE Communications Surveys & Tutorials, 17(1), 179–197.

    Article  Google Scholar 

  79. Fadel, E., Gungor, V. C., Nassef, L., Akkari, N., Malik, M. G. A., Almasri, S., et al. (2015). A survey on wireless sensor networks for smart grid. Computer Communications, 71, 22–33. https://doi.org/10.1016/j.comcom.2015.09.006.

    Article  Google Scholar 

  80. Lynch, J. P. (2006). A summary review of wireless sensors and sensor networks for structural health monitoring. Shock and Vibration Digest, 38(2), 91–128.

    Article  MathSciNet  Google Scholar 

  81. Stoianov, I., Nachman, L., Madden, S., Tokmouline, T., & Csail, M. (2007). PIPENET: A wireless sensor network for pipeline monitoring. In 6th international symposium on information processing in sensor networks, 2007. IPSN 2007 (pp. 264–273).

  82. Wang, R., Zhang, L., Sun, R., Gong, J., & Cui, L. (2011). EasiTia: A pervasive traffic information acquisition system based on wireless sensor networks. IEEE Transactions on Intelligent Transportation Systems, 12(2), 615–621.

    Article  Google Scholar 

  83. Alrajeh, N. A., Alabed, M. S., & Elwahiby, M. S. (2013). Secure ant-based routing protocol for wireless sensor network. In International journal of distributed sensor networks (Vol. 2013).

  84. Khan, A., & Jenkins, L. (2008). Undersea wireless sensor network for ocean pollution prevention. In 3rd international conference on communication systems software and middleware and workshops (COMSWARE ’08) (No. i, pp. 2–8).

  85. Yu, H., & Guo, M. (2012). An efficient oil and gas pipeline monitoring systems based on wireless sensor networks. In 2012 international conference on information security and intelligence control (ISIC) (pp. 178–181).

  86. Antil, P., & Malik, A. (2014). Hole detection for quantifying connectivity in wireless sensor networks: A survey (Vol. 2014).

  87. Yang, S.-H. (2014). Wireless sensor networks principles, design and applications. London: Springer. https://doi.org/10.1007/978-1-4471-5505-8.

    Book  Google Scholar 

  88. Gravogl, K., Haase, J., & Grimm, C. (2011). Choosing the best wireless protocol for typical applications. In 24th international conference on architecture of computing systems (ARCS) (p. 6).

  89. Schuegraf, K., Abraham, M. C., Brand, A., Naik, M., & Thakur, R. (2013). Semiconductor logic technology innovation to achieve sub-10 nm manufacturing. IEEE Journal of Electron Devices Society, 1(3), 66–75.

    Article  Google Scholar 

  90. Park, P. (2011). Modeling, analysis, and design of wireless sensor network protocols. Doctoral Thesis, KTH, School of Electrical Engineering, Automatic Control, Lab SE-100 44, Stockholm, Sweden.

  91. Heidemann, J., Stojanovic, M., & Zorzi, M. (2012). Underwater sensor networks: applications, advances and challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 370(1958), 158–175.

    Article  Google Scholar 

  92. Zin, S. M., Anuar, N. B., Kiah, M. L. M., & Pathan, A. S. K. (2014). Routing protocol design for secure WSN: Review and open research issues. Journal of Network and Computer Applications, 41(1), 517–530. https://doi.org/10.1016/j.jnca.2014.02.008.

    Article  Google Scholar 

  93. 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 

  94. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual Hawaii international conference on system science (Vol. 0, no. c, pp. 3005–3014).

  95. Lindsey, S., & Raghavendra, C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. IEEE Aerospace Conference Proceedings, 3, 1125–1130.

    Google Scholar 

  96. Mohemed, R. E., Saleh, A. I., Abdelrazzak, M., & Samra, A. S. (2017). Energy-efficient routing protocols for solving energy hole problem in wireless sensor networks. Computer Networks, 114, 51–66. https://doi.org/10.1016/j.comnet.2016.12.011.

    Article  Google Scholar 

  97. Upadhyayula, S., & Gupta, S. K. S. (2007). Spanning tree based algorithms for low latency and energy efficient data aggregation enhanced convergecast (DAC) in wireless sensor networks. Ad Hoc Networks, 5(5), 626–648.

    Article  Google Scholar 

  98. Younis, O. (2004). Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach. In 3rd annual conference on IEEE (pp. 1–12).

  99. Hong, J., Kook, J., & Lee, S. (2009). T-LEACH: The method of threshold-based cluster head replacement for wireless sensor networks. Information Systems Frontiers, 11(5), 513–521.

    Article  Google Scholar 

  100. Salim, A., Osamy, W., & Khedr, A. M. (2014). IBLEACH: Intra-balanced LEACH protocol for wireless sensor networks. Wireless Networks, 20, 1515–1525.

    Article  Google Scholar 

  101. Singh, S., Chand, S., Kumar, R., Malik, A., & Kumar, B. (2016). NEECP: Novel energy-efficient clustering protocol for prolonging lifetime of WSNs. IET Wireless Sensor Systems, 6(5), 151–157.

    Article  Google Scholar 

  102. Sicari, S., Grieco, L. A., Rizzardi, A., Boggia, G., & Coen-porisini, A. (2014). SETA: A SEcure sharing of TAsks in clustered wireless sensor networks. In 9th IEEE international conference on wireless and mobile computing, networking and communications 2013, WiMob 2013 (No. i, pp. 239–246).

  103. Xia, H., Jia, R. Z., & Pan, Y. Z. (2016). Energy-efficient routing algorithm based on unequal clustering and connected graph in wireless sensor networks. International Journal of Wireless Information Networks, 23(2), 141–150.

    Article  Google Scholar 

  104. Abdelhakim, M., & Member, I. (2016). Mobile coordinated wireless sensor network: An energy efficient scheme for real-time transmissions. IEEE Journal on Selected Areas in Communications, 8716, 1–15.

    Google Scholar 

  105. Farouk, F., Rizk, R., & Zaki, F. W. (2014). Multi-level stable and energy-efficient clustering protocol in heterogeneous wireless sensor networks. IET Wireless Sensor Systems, 4(October), 159–169.

    Article  Google Scholar 

  106. Ishmanov, F., Malik, A. S., & Kim, S. W. (2011). Energy consumption balancing (ECB) issues and mechanisms in wireless sensor networks (WSNs): A comprehensive overview. European Transactions on Telecommunications, 22(4), 151–167.

    Article  Google Scholar 

  107. Vincent, P. J., & Mceachen, J. (2006). An energy-efficient approach for information transfer from distributed wireless sensor systems. In IEEE/SMC International Conference on System of Systems Engineering, 2006 (pp. 100–105).

  108. Pottie, G. J., & Kaiser, W. J. (2000). Wireless integrated network sensors. Communications of the ACM, 43(5), 51–58.

    Article  Google Scholar 

  109. Qing, L., Zhu, Q., & Wang, M. (2006). Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer Communications, 29(12), 2230–2237.

    Article  Google Scholar 

  110. Lindsey, S., & Raghavendra, C. (2002) PEGASIS: Power-efficient gathering in sensor information systems. In Proceedings of IEEE aerospace conference USA (Vol. 3, pp. 1125–1130).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Reem E. Mohamed.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mohamed, R.E., Saleh, A.I., Abdelrazzak, M. et al. Survey on Wireless Sensor Network Applications and Energy Efficient Routing Protocols. Wireless Pers Commun 101, 1019–1055 (2018). https://doi.org/10.1007/s11277-018-5747-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5747-9

Keywords

Navigation