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Abstract

Mobile Edge Computing (MEC) is an inventive paradigm for computing that has the potential to notably diminish latency and energy consumption by transferring computationally demanding jobs to edge clouds near intelligent mobile users. This investigation aims to reduce offloading and latency between multiple users and edge computing in the context of Internet of Things (IoT) applications in the fifth generation (5G) by utilizing an optimization algorithm called the Bald Eagle Search Optimization Algorithm. Although employing deep learning methods might increase time consumption and computational complexity, an edge computing system enables devices to transfer their demanding jobs to edge servers, decreasing latency and conserving energy. The Bald Eagle Algorithm (BES) is an advanced optimization algorithm inspired by eagle hunting strategies and consists of select, search, and swoop stages. A resource estimation stage is introduced to select the most suitable resources to enhance the BES algorithm further. By transferring the most appropriate Internet of Things subtasks to edge servers, the edge system minimizes the anticipated execution time. To attain rapid and nearly optimal IoT device performance, a Bald Eagle Search Optimization Algorithm is suggested based on multiuser offloading. Edge computing effectively diminishes latency, surmounting the limitations of cloud-based processing. The BES algorithm outperforms existing methods, such as Deep-Q-Network (DQN) and Deep Deterministic Policy Gradient (DDPG), to lessen offloading latency. Finally, simulations are carried out to exhibit the attained power efficiency and stability by mitigating offloading latency.

Reason for Retraction

This article has been retracted at the request of the Editorial Office, following an internal investigation conducted in accordance with the Committee on Publication Ethics (COPE) Retraction Guidelines.

Please see the Retraction Notice available at: https://ijcsm.researchcommons.org/ijcsm/vol7/iss1/18/

DOI: https://doi.org/10.52866/2788-7421.1363

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