Title: WECOA: coati-walrus optimisation-based resource allocation in fog-cloud environment

Authors: Sonti Harika; B. Chaitanya Krishna

Addresses: Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh – 522502, India ' Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh – 522502, India

Abstract: Managing resource allocation in a fog-cloud environment is complex due to the dynamic nature of user requirements and the limited resources available in fog nodes. This work proposes a novel approach to optimisation-based resource allocation in fog-cloud (ORAFC) environments, utilising advanced optimisation techniques to improve system performance and efficiency. A core element of the model is a load prediction mechanism powered by a dual spatial pyramid pooling assisted SqueezeNet (DSPPAS) architecture, which determines whether tasks should be processed locally or offloaded to the cloud, considering factors like distance, delay, and performance metrics. To optimise resource allocation, this work employs the walrus enhanced with coati optimisation algorithm (WECOA), balancing key factors such as makespan, migration cost, energy consumption, and execution time. The proposed approach is validated through extensive simulations and comparisons with existing methods.

Keywords: resource allocation; fog computing; cloud computing; dual spatial pyramid pooling assisted SqueezeNet; DSPPAS; walrus enhanced with coati optimisation algorithm; WECOA.

DOI: 10.1504/IJCC.2026.152337

International Journal of Cloud Computing, 2026 Vol.15 No.1, pp.90 - 117

Received: 19 Nov 2024
Accepted: 11 Jun 2025
Published online: 16 Mar 2026 *

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