Year: 2025
Type: article
Abstract: Many problems and limitations appeared with the spread of mobile cloud computing (MCC) technology, due to the battery life of the mobile, limited resources, storage space and processors. In addition, the biggest challenge is to make decisions about executing tasks between local devices and cloud servers (edge) to save energy and reduce delay time by reducing the energy consumption (or cost) of the system concerned. In this paper, an optimization method based on the Lion Optimization Algorithm (LOA) is proposed for task- offloading of mobile cloud computing. Task- offloading is the transfer of tasks from mobile devices to servers that handle high-level computational operations, such as cloud servers or Mobile-Edge Computing (MEC) servers, to reduce task execution time and energy consumption. The proposed algorithm has a high performance in reducing the cost for offloading tasks. This method can be used to improve the performance of 5G, 6G and later mobile technologies to implement applications that require a large amount of computing, also, multi-objectives could be applied for more cost reduction. The results showed that the proposed algorithm LOA is better than other traditional algorithms such as the genetic algorithm in terms of calculating the costs to find the best solutions.
Institution: Mustansiriyah University
Language: English
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
Funder: Mustansiriyah University
OpenAlex ID: W4416903269
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