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Efficient Algorithms for Hotspot Problem in Wireless Sensor Networks: Gravitational Search Algorithm

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Intelligent Systems Technologies and Applications (ISTA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 683))

Abstract

Energy conservation of sensor nodes (SNs) is the major concern of wireless sensor networks (WSNs) as those are operated by small batteries with a limited power. In a clustered WSN, cluster heads (CHs) collects local information such as temperature, humidity, pressure etc. from the member SNs aggregate it and send to the sink through few intermediate CHs. Here, the CHs that are closer to the sink are over burdened as they are responsible for forwarding more number of packets than the farther CHs that tends to exhaust their energy quickly. This results in network partitioning and this problem well known hot spot or energy hole problem. In this paper, a Gravitational Search Algorithm (GSA) approach based clustering and routing algorithms are proposed to address the hot spot problem. In clustering, we select few efficient SNs as CHs from the normal SNs with respect to certain cost function. We design an algorithm for CH selection based on GSA and assign the remaining SNs to the CHs based on another derived cost function. Then, a GSA based routing algorithm is presented with respect to the routing cost function. These algorithms are intended to develop to enhance the lifetime of network with efficient encoding schemes of GSA. The proposed algorithms are simulated on various scenarios of WSNs by varying number of SNs. The results of the proposed algorithms are compared with few well known algorithms to show the supremacy in terms network lifetime, residual energy and number of alive SNs.

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References

  1. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Comput. Netw. 38(4), 393–422 (2002)

    Article  Google Scholar 

  2. Bagci, H., Yazici, A.: An energy aware fuzzy approach to unequal clustering in wireless sensor networks. Appl. Soft Comput. 13(4), 1741–1749 (2013)

    Article  Google Scholar 

  3. Banka, H., Jana, P.K., et al.: PSO-based multiple-sink placement algorithm for protracting the lifetime of wireless sensor networks. In: Proceedings of the Second International Conference on Computer and Communication Technologies, pp. 605–616. Springer (2016)

    Google Scholar 

  4. Guo, W., Li, J., Chen, G., Niu, Y., Chen, C.: A PSO-optimized real-time fault-tolerant task allocation algorithm in wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 26(12), 3236–3249 (2015)

    Article  Google Scholar 

  5. Heinzelman, W.B.: Application-specific protocol architectures for wireless networks. Ph.D. thesis, Massachusetts Institute of Technology (2000)

    Google Scholar 

  6. Jiang, C.J., Shi, W.R., Tang, X.I., et al.: Energy-balanced unequal clustering protocol for wireless sensor networks. J. China Univ. Posts Telecommun. 17(4), 94–99 (2010)

    Article  Google Scholar 

  7. Kuila, P., Jana, P.K.: Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach. Eng. Appl. Artif. Intell. 33, 127–140 (2014)

    Article  Google Scholar 

  8. Latiff, N.A., Tsimenidis, C.C., Sharif, B.S.: Energy-aware clustering for wireless sensor networks using particle swarm optimization. In: IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2007, pp. 1–5. IEEE (2007)

    Google Scholar 

  9. Logambigai, R., Kannan, A.: Fuzzy logic based unequal clustering for wireless sensor networks. Wirel. Netw. 22(3), 945–957 (2016)

    Article  Google Scholar 

  10. Ok, C.S., Lee, S., Mitra, P., Kumara, S.: Distributed energy balanced routing for wireless sensor networks. Comput. Ind. Eng. 57(1), 125–135 (2009)

    Article  Google Scholar 

  11. Rao, P.S., Banka, H.: Novel chemical reaction optimization based unequal clustering and routing algorithms for wireless sensor networks. Wirel. Netw. 1–20 (2016)

    Google Scholar 

  12. Rashedi, E., Nezamabadi-Pour, H., Saryazdi, S.: GSA: A Gravitational Search Algorithm. Inf. Sci. 179(13), 2232–2248 (2009)

    Article  MATH  Google Scholar 

  13. Singh, B., Lobiyal, D.K.: A novel energy-aware cluster head selection based on particle swarm optimization for wireless sensor networks. Hum. Centric Comput. Inf. Sci. 2(1), 13 (2012)

    Article  Google Scholar 

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Correspondence to Srikanth Jannu .

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Jannu, S., Dara, S., Kumar, K.K., Bandari, S. (2018). Efficient Algorithms for Hotspot Problem in Wireless Sensor Networks: Gravitational Search Algorithm. In: Thampi, S., Mitra, S., Mukhopadhyay, J., Li, KC., James, A., Berretti, S. (eds) Intelligent Systems Technologies and Applications. ISTA 2017. Advances in Intelligent Systems and Computing, vol 683. Springer, Cham. https://doi.org/10.1007/978-3-319-68385-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-68385-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68384-3

  • Online ISBN: 978-3-319-68385-0

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