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Impacts of Computational Techniques for Wireless Sensor Networks

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Nature-Inspired Computing for Smart Application Design

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

Abstract

Ad-hoc and sensor network is a collection of two types of networks such as wireless sensor network (WSN) and wireless ad-hoc network (WANET). The combination of these two networks is known as ad-hoc and sensor network. The topology of the ad-hoc and sensor network is a combination of static and dynamic based on situation and problem. It is a collection of several sensor nodes along with some normal nodes. It consists a base station (BS) which acts as a router that provides the services to the customers by collecting sense information from the neighbor nodes. Although, there are several benefits of ad-hoc and sensor nodes, but it has also some limitations such as limited capacity of battery of the nodes, large number of deployable areas, resource constraints, variations of network parameters. The combination of these limitations causes several types of uncertainty and interference in the network that causes route breakage and data failure. In context of above-mentioned issues, optimization technique plays an important role in the context of single or multi-objectives. In multi-objective optimization, may be different objectives are conflicting one to another. In this paper, several swam intelligence techniques are compared with context of objective for giving better assessment. The name of these techniques are quasi-opposition dragonfly algorithm, quasi-opposition atom search optimization, salp swarm algorithm and quasi-opposition pathfinder algorithm. The results showed that the studied optimization techniques may be used for the WSN study and show good results.

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, SR Engineering College, Ananthsagar, Hasanparthy, Warangal, Telangana, India

    Chandan Kumar Shiva, Basetti Vedik & Ritesh Kumar

  2. Department of Electrical and Electronics Engineering, Alliance University, Bangalore, India

    Sheila Mahapatra

  3. Department of Electrical Engineering, Institute of Chemical Technology Mumbai, Marathwada Campus, Jalna, India

    Saurav Raj

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  1. Chandan Kumar Shiva
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  2. Basetti Vedik
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  3. Ritesh Kumar
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  4. Sheila Mahapatra
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  5. Saurav Raj
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Correspondence to Chandan Kumar Shiva .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Science and Technology (Autonomous), Berhampur, Odisha, India

    Santosh Kumar Das

  2. Division of Computational Mechatronics, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Thanh-Phong Dao

  3. Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Seri Kembangan, Malaysia

    Thinagaran Perumal

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Shiva, C.K., Vedik, B., Kumar, R., Mahapatra, S., Raj, S. (2021). Impacts of Computational Techniques for Wireless Sensor Networks. In: Das, S.K., Dao, TP., Perumal, T. (eds) Nature-Inspired Computing for Smart Application Design. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-33-6195-9_6

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  • DOI: https://doi.org/10.1007/978-981-33-6195-9_6

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