The importance of energy efficient in wireless sensor networks
Keywords:
lifetime, energy, mobile, node, packet, ratioAbstract
Mobile Node-based routing is an efficient routing technique compared to traditional approaches. Due to this FERP majorly data isolation is provided for sensor nodes, and the network is more energy efficient. The Mobile data collector collects data from only Family heads and forwards to the cluster head. The Node level energy saving scheme is proposed in this work. The performance of this routing protocol is assessed based on Energy consumption, Throughput, Lifetime, Packet Delivery Ratio, Energy efficiency. Most of the Energy is saved due to the introducing of mobile nodes for data collection. Apart from this, we are reducing the load for mobile data collectors also. In general, mobile data collectors have high energy resources. But it is not possible in all terrains. This FERP gives better results in military and plateaus, and irregular terrains where multihop communication is complex. This work is further enhanced by Trust node based routing to improve the lifetime of the network.
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Cardei, M., & Wu, J. (2006). Energy-efficient coverage problems in wireless ad-hoc sensor networks. Computer communications, 29(4), 413-420. https://doi.org/10.1016/j.comcom.2004.12.025
Mhemed, R., Aslam, N., Phillips, W., & Comeau, F. (2012). An energy efficient fuzzy logic cluster formation protocol in wireless sensor networks. Procedia Computer Science, 10, 255-262. https://doi.org/10.1016/j.procs.2012.06.035
Çam, H., Özdemir, S., Nair, P., Muthuavinashiappan, D., & Sanli, H. O. (2006). Energy-efficient secure pattern based data aggregation for wireless sensor networks. Computer Communications, 29(4), 446-455. https://doi.org/10.1016/j.comcom.2004.12.029
Singh, S. P., & Sharma, S. C. (2015). A survey on cluster based routing protocols in wireless sensor networks. Procedia computer science, 45, 687-695. https://doi.org/10.1016/j.procs.2015.03.133
Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 67, 104-122. https://doi.org/10.1016/j.comnet.2014.03.027
Chen, H., Mineno, H., & Mizuno, T. (2008). Adaptive data aggregation scheme in clustered wireless sensor networks. Computer Communications, 31(15), 3579-3585. https://doi.org/10.1016/j.comcom.2008.06.011
Aslam, N., Phillips, W., Robertson, W., & Sivakumar, S. (2011). A multi-criterion optimization technique for energy efficient cluster formation in wireless sensor networks. Information Fusion, 12(3), 202-212. https://doi.org/10.1016/j.inffus.2009.12.005
Javaid, N., Qureshi, T. N., Khan, A. H., Iqbal, A., Akhtar, E., & Ishfaq, M. (2013). EDDEEC: Enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks. arXiv preprint arXiv:1303.5274.
Chen, M., Kwon, T., & Choi, Y. (2006). Energy-efficient differentiated directed diffusion (EDDD) in wireless sensor networks. Computer Communications, 29(2), 231-245. https://doi.org/10.1016/j.comcom.2005.05.019
Khediri, S. E., Nasri, N., Wei, A., & Kachouri, A. (2014). A new approach for clustering in wireless sensors networks based on LEACH. Procedia Computer Science, 32, 1180-1185. https://doi.org/10.1016/j.procs.2014.05.551
Zhu, H., Luo, H., Peng, H., Li, L., & Luo, Q. (2009). Complex networks-based energy-efficient evolution model for wireless sensor networks. Chaos, Solitons & Fractals, 41(4), 1828-1835. https://doi.org/10.1016/j.chaos.2008.07.032
Gherbi, C., Aliouat, Z., & Benmohammed, M. (2016). An adaptive clustering approach to dynamic load balancing and energy efficiency in wireless sensor networks. Energy, 114, 647-662. https://doi.org/10.1016/j.energy.2016.08.012
Milenković, A., Otto, C., & Jovanov, E. (2006). Wireless sensor networks for personal health monitoring: Issues and an implementation. Computer communications, 29(13-14), 2521-2533. https://doi.org/10.1016/j.comcom.2006.02.011
Akyildiz, I. F., & Kasimoglu, I. H. (2004). Wireless sensor and actor networks: research challenges. Ad hoc networks, 2(4), 351-367. https://doi.org/10.1016/j.adhoc.2004.04.003
Lee, S. H., Lee, S., Song, H., & Lee, H. S. (2009, October). Wireless sensor network design for tactical military applications: Remote large-scale environments. In MILCOM 2009-2009 IEEE Military communications conference (pp. 1-7). IEEE. https://doi.org/10.1109/MILCOM.2009.5379900
Li, H., Lin, K., & Li, K. (2011). Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks. Computer Communications, 34(4), 591-597. https://doi.org/10.1016/j.comcom.2010.02.026
Kim, W. H., Lee, S., & Hwang, J. (2011). Real-time energy monitoring and controlling system based on Zigbee sensor networks. Procedia Computer Science, 5, 794-797. https://doi.org/10.1016/j.procs.2011.07.108
Kumar, D., Aseri, T. C., & Patel, R. B. (2009). EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks. Computer Communications, 32(4), 662-667. https://doi.org/10.1016/j.comcom.2008.11.025
Saleem, M., Ullah, I., & Farooq, M. (2012). BeeSensor: An energy-efficient and scalable routing protocol for wireless sensor networks. Information Sciences, 200, 38-56. https://doi.org/10.1016/j.ins.2012.02.024
Sudha, M. N., Valarmathi, M. L., & Babu, A. S. (2011). Energy efficient data transmission in automatic irrigation system using wireless sensor networks. Computers and Electronics in Agriculture, 78(2), 215-221. https://doi.org/10.1016/j.compag.2011.07.009
Qureshi, T. N., Javaid, N., Khan, A. H., Iqbal, A., Akhtar, E., & Ishfaq, M. (2013). BEENISH: Balanced energy efficient network integrated super heterogeneous protocol for wireless sensor networks. Procedia Computer Science, 19, 920-925. https://doi.org/10.1016/j.procs.2013.06.126
Lee, J. H., & Moon, I. (2014). Modeling and optimization of energy efficient routing in wireless sensor networks. Applied Mathematical Modelling, 38(7-8), 2280-2289. https://doi.org/10.1016/j.apm.2013.10.044
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