Abstract
Former developments and advances in micro-electro-mechanical systems have made it possible to produce and use tiny battery-powered nodes in wireless communications. Networks consisting of such nodes which are capable of measurement are called Wireless sensor networks (WSNs). The initial objective of using nodes was related to internal applications. The initial nodes are able to sense scalar information such as temperature, moisture, pressure and the location of surrounding objects. However, sensor nodes’ power is provided by battery with limited capacity. Hence, due to limited resources, a balance should be made between precision and power optimization in these networks. In this paper, a new method is proposed which addresses the issue of optimal power consumption in WSNs. Accordingly, using fish swarm optimization algorithm, we proposed an energy-aware routing protocol in WSNs which optimizes power consumption. The proposed protocol was simulated in OPNET 11.5 simulator and compared with ERA protocol. Simulation results indicated that the proposed protocol had better performance than ERA protocol regarding power consumption, end-to-end delay, media access delay, throughput rate, the probability of successful transmission to sink and signal to noise ratio.











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26 March 2021
A Correction to this paper has been published: https://doi.org/10.1007/s11277-021-08412-4
References
Welsh, M., Malan, D., Duncan, B., Fulford-Jones, T., & Moulton, S. (2004). Wireless sensor networks for emergency medical care. In GE global research conference, Boston.
Kurose, J., Lesser, V., de Silva, E., Jayasumana, A., & Liu, B. (2003). Sensor networks seminar. In CMPSCI 791L, University of Massachusetts, Amherst, MA, Fall.
Deshpande, A., Guestrin, C., Madden, S. R., Hellerstein, J. M., Hong, W. (2004). Model-driven data acquisition in sensor networks. In Proceedings of the thirtieth international conference on very large data bases (Vol. 30, pp. 588–599).
Minoli, D. (2002). Hotspot networks: Wi-Fi for public access locations. McGraw-Hill Professional.
Kumar, R., Tsiatsis, V., & Srivastava, M. B. (2003). Computation hierarchy for in-network processing. In Proceedings of the 2nd ACM international conference on wireless sensor networks and applications (pp. 68–77).
Sohraby, K., Minoli, D., & Znati, T. (2007). Wireless sensor networks: Technology, protocols, and applications. New York: Wiley.
Amgoth, T., & Jana, P. K. (2015). Energy-aware routing algorithm for wireless sensor networks. Computers & Electrical Engineering, 41, 357–367.
Chen, A., Li, X., Ni, X., & Luo, G. (2018). RTGOR: Reliability and timeliness guaranteed opportunistic routing in wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 2018, 1–8.
Ma, J., Wang, S., Meng, C., Ge, Y., & Du, J. (2018). Hybrid energy-efficient APTEEN protocol based on ant colony algorithm in wireless sensor network. EURASIP Journal on Wireless Communications and Networking, 2018, 102.
Mishra, M. B., Kumar, A. R., Kumar, V., & Singh, J. (2017). A grid-based approach to prolong lifetime of WSNs using fuzzy logic. In Advances in computational intelligence, Springer, pp. 11–22.
Zahedi, Z. M., Akbari, R., Shokouhifar, M., Safaei, F., & Jalali, A. (2016). Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks. Expert Systems with Applications, 55, 313–328.
Abasıkeleş-Turgut, İ, & Hafif, O. G. (2016). NODIC: a novel distributed clustering routing protocol in WSNs by using a time-sharing approach for CH election. Wireless Networks, 22, 1023–1034.
Sahoo, B. M., Amgoth, T., & Pandey, H. M. (2020). Particle swarm optimization based energy efficient clustering and sink mobility in heterogeneous wireless sensor network. Ad Hoc Networks, 106, 102237.
Parvin, J. R., & Vasanthanayaki, C. (2019). Particle swarm optimization-based energy efficient target tracking in wireless sensor network. Measurement, 147, 106882.
Shyjith, M., Maheswaran, C., & Reshma, V. (2020). Optimized and dynamic selection of cluster head using energy efficient routing protocol in WSN. Wireless Personal Communications, 116, 1–23.
Zhou, Z., & Niu, Y. (2020). An energy efficient clustering algorithm based on annulus division applied in wireless sensor networks. Wireless Personal Communications, 115(3), 2229–2241.
Li, X.-L. (2002). An optimizing method based on autonomous animals: Fish-swarm algorithm. Systems Engineering Theory & Practice, 22(32–38), 2002.
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Gorgich, S., Tabatabaei, S. Proposing an Energy-Aware Routing Protocol by Using Fish Swarm Optimization Algorithm in WSN (Wireless Sensor Networks). Wireless Pers Commun 119, 1935–1955 (2021). https://doi.org/10.1007/s11277-021-08312-7
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DOI: https://doi.org/10.1007/s11277-021-08312-7