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Congestion Management Techniques in WSNs: A Comparative Study

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Cryptology and Network Security with Machine Learning (ICCNSML 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 918))

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Abstract

Wireless sensor network (WSN) is an interconnection of numerous sensor nodes with autonomous processing and communication capability. Sensor nodes collect data from the surroundings and transmit it to an endpoint receiver which is known as a sink, so that appropriate decisions can take place. WSN has resource constraints in terms of bandwidth, energy, storage, and processing. Due to limited resources, congestion may occur in WSN. Congestion is one of the serious issues in the network which is degrading the performance of the network and quality of service (QoS). Some factors like packet collision, channel contention, and data transmission in many-to-one fashions become the catalyst for congestion and result in packet drop. Many researchers provided different solutions to solve the issue, but congestion is still a serious problem. Therefore, more specialized strategies are required to manage congestion. In this paper, we have investigated various congestion detection and management methods and compared them based on queue, priority, source management, traffic management, packet service time, channel load, and buffer occupancy.

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Authors and Affiliations

  1. School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India

    Ajai Kumar & D. K. Lobiyal

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  1. Ajai Kumar
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  2. D. K. Lobiyal
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Correspondence to Ajai Kumar .

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Editors and Affiliations

  1. Department of Mathematics, Pranveer Singh Institute of Technology, Kanpur, India

    Atul Chaturvedi

  2. Department of Mathematics, Indian Institute of Technology Jammu, Jammu, India

    Sartaj Ul Hasan

  3. Applied Statistics Unit, Indian Statistical Institute, Kolkata, India

    Bimal Kumar Roy

  4. Department of Mathematics, Bar-Ilan University, Ramat-Gan, Israel

    Boaz Tsaban

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Kumar, A., Lobiyal, D.K. (2024). Congestion Management Techniques in WSNs: A Comparative Study. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_18

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  • DOI: https://doi.org/10.1007/978-981-97-0641-9_18

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  • Publisher Name: Springer, Singapore

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  • Online ISBN: 978-981-97-0641-9

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