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ACRA: Adaptive meta-heuristic based Clustering and Routing Algorithm for IoT-assisted wireless sensor network

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Abstract

Opportunistic routing  is crucial for the development and management of an efficient and flexible network in Internet of Things (IoT) assisted wireless sensor network (WSN). Sensor nodes are dispersed over a large region and collect data from the surroundings. Data is analysed rather than sensed before being transferred via an established route to the base station (BS). Being a resource constrained network; overhead problems manifest. The energy consumption and subsequently, quick demise of nodes employed for data detection and transmission is major issue. Many other kind of network problems also arise in these constrained networks due to deadlock and livelock. Deadlock could occur if two nodes are trying to access the same data or resource simultaneously and neither can proceed until the other node releases it. This can lead to a complete halt in network operations, as nodes are unable to communicate or exchange data. The very purpose of deploying a network fails. Livelock could occur if two nodes are repeatedly sending messages to each other in response to previous messages, but none of the messages are leading to a resolution of the issue. This can lead to excessive use of network resources and can also cause a complete halt in network operations if the network becomes overloaded with traffic. This paper addresses the problem of deadlock and livelock in the context of IoT assisted WSN and proposed a novel approach based on the Adaptive meta-heuristic based Clustering and Routing Algorithm for IoT-assisted wireless sensor network (ACRA) to solve it. The primary contributions for the proposed method in such a context are: (1) Reduce Wastage of resources so that energy consumption is minimized (2) No single node stuck in the loop and thus removes hotspot problem (3) Use of alternate optimal path without getting stuck into a single path and finally, (4) the event must cover a large region. Two algorithms are proposed in ACRA including (1) the inter-deadlock avoidance clustering algorithm (INDCA) and (2) the intra-deadlock avoidance routing algorithm (INDRA). Both algorithms construct an optimal route and cover a large region. The proposed algorithm performance is compared with other similar algorithms on essential parameters such as the Packet Delivery Ratio (PDR), number of active nodes, and Average residual energy (ARE). The simulation results show that the proposed algorithm considerably outperforms its competitive techniques in terms of energy efficiency while at the same time addresses deadlock and livelock problems in a robust manner.

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  1. Kamal Kumar contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Uttarakhand, Srinagar, Uttarakhand, India

    Soni Chaurasia & Kamal kumar

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  1. Soni Chaurasia
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  2. Kamal kumar
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Correspondence to Soni Chaurasia.

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Chaurasia, S., kumar, K. ACRA: Adaptive meta-heuristic based Clustering and Routing Algorithm for IoT-assisted wireless sensor network. Peer-to-Peer Netw. Appl. 16, 2186–2201 (2023). https://doi.org/10.1007/s12083-023-01505-w

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