This approach improves resource utilisation and reduces latency in fog environments, indicating enhanced scalability.
Fog computing, characterised by its dynamic and heterogeneous nature, necessitates efficient resource provisioning to maximise resource utilisation. Existing methods often suffer from computational overhead and scalability limitations. This research proposes a novel resource provisioning approach for fog environments to address these challenges. The user request is first transformed into a four queue model, in which very urgent and urgent requests are placed in the first and second priority queues to offload to the closest available fog resource while considering deadliness and latency. Here, the selection of a suitable fog node selection for flawless workload execution, an improved coati optimisation algorithm (ICOA) is developed. The proposed method is evaluated in terms of packet delivery ratio (PDR), processing time, end to end delay, throughput, energy consumption, and cost and acquired the value of 97.5 (%), 105.061 (ms), 44.807 (ms), 95.1826 (%), 21.2539 (Kwh), and 0.42402 ($) respectively.
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Usha et al. (2026) studied this question.
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