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GA-Based Fault Diagnosis Technique for Enhancing Network Lifetime of Wireless Sensor Network

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Nature Inspired Computing for Wireless Sensor Networks

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

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Abstract

A wireless sensor network (WSN) is a collection of more than one sensor nodes which is used both collecting as well as sensing data from its environment (Rongbo in Int J Distrib Sens Netw 2010(1155):1–7, [1], Herbert and Donald in Schilling principles of communication systems. McGraw-Hill, New York, [2]). The main aim of this process is to achieve several operations efficiently in terms of different applications such as intelligent building, precise agriculture, medicine and health care, preventive maintenance, machine surveillance, disaster relief operation and biodiversity mapping. The stated applications are optimized efficiently in terms of cost, scalability and readiness. Although, there are so many fruitful advantages of WSN, but it consists of limited capacity of batteries which is insufficient during any operation. The sensor nodes are directly or indirectly connected with base station as well as sink node. Sometimes, due to network variation or failure of hardware sensor nodes fail to transmit the data packet. Moreover, due to limited energy, sometimes sensor node exhausts before the delivery of the data packet and gets converted into faulty node (Heinzelman, Chandrakasan and Balakrishnan in Energy efficient communication protocol for wireless micro sensor networks, pp. 8020–8030, [3], Bhajantri, Nalini in Int J Comput Netw Inf Secur 6(12):37–46, [4]). This faulty node treated as dead node during operation. So, there is need to design an effective algorithm for detecting as well as calculating total dead nodes and provide optimum solution. In this paper, an efficient technique is proposed based on the direct diffusion technique that aims to find optimum path by recovering dead nodes. The proposed algorithm enhances the network lifetime by reducing data packet loss as well as energy consumption.

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Authors and Affiliations

  1. National Institute of Science and Technology (Autonomous), Institute Park, Pallur Hills, Berhampur, 761008, Odisha, India

    Ruchika Padhi & Bhabani Sankar Gouda

Authors
  1. Ruchika Padhi
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  2. Bhabani Sankar Gouda
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Correspondence to Ruchika Padhi .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University, Kolkata, West Bengal, India

    Debashis De

  2. Department of Computer Science and Engineering, Institute of Engineering and Management, Kolkata, West Bengal, India

    Amartya Mukherjee

  3. School of Computer Science and Engineering, National Institute of Science and Technology, Berhampur, Odisha, India

    Santosh Kumar Das

  4. Department of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

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Padhi, R., Gouda, B.S. (2020). GA-Based Fault Diagnosis Technique for Enhancing Network Lifetime of Wireless Sensor Network. In: De, D., Mukherjee, A., Kumar Das, S., Dey, N. (eds) Nature Inspired Computing for Wireless Sensor Networks. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-2125-6_3

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  • DOI: https://doi.org/10.1007/978-981-15-2125-6_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2124-9

  • Online ISBN: 978-981-15-2125-6

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