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Mitigating Hotspot Issues in Heterogeneous Wireless Sensor Networks

Osamah Ibrahim Khalaf, Carlos Andrés Tavera Romero, Shahzad Hassan, Muhammad Taimoor Iqbal

2022Journal of Sensors73 citationsDOIOpen Access PDF

Abstract

Wireless Sensor Networks (WSNs) consist of a spatially distributed set of autonomous connected sensor nodes. The deployed sensor nodes are extensively used for sensing and monitoring for environmental surveillance, military operations, transportation monitoring, and healthcare monitoring. The sensor nodes in these networks have limited resources in terms of battery, storage, and processing. In some scenarios, the sensor nodes are deployed closer to the base station and responsible to forward their own and neighbor nodes’ data towards the base station and depleted energy. This issue is called a hotspot in the network. Hotspot issues mainly appear in those locations where traffic load is more on the sensor nodes. The dynamic and unequal clustering techniques have been used and mitigate the hotspot issues. However, with few benefits, these solutions have suffered from coverage overhead, network connection issues, unbalanced energy utilization among the sink nodes, and network stability issues. In this paper, a comprehensive review of various equal clustering, unequal clustering, and hybrid clustering approaches with their clustering attributes is presented to mitigate hotspot issues in heterogeneous WSNs by using various parameters such as cluster head selection, number of clusters, zone formation, transmission, and routing parameters. This review provides a detailed platform for new researchers to explore the new and novel solutions to solve the hotspot issues in these networks.

Topics & Concepts

Wireless sensor networkHotspot (geology)Cluster analysisComputer scienceComputer networkBase stationKey distribution in wireless sensor networksMobile wireless sensor networkEnergy consumptionDistributed computingWirelessWireless networkEngineeringTelecommunicationsElectrical engineeringGeologyGeophysicsMachine learningEnergy Efficient Wireless Sensor NetworksEnergy Harvesting in Wireless NetworksSecurity in Wireless Sensor Networks