Abstract
The mobile edge computing (MEC) technology sinks the computing and storage resources to the network edge and reaches the goal of improving user service quality by formulating reasonable task offloading strategies. As the number of edge users increases, the energy consumption and energy cost of the MEC are also increasing. Therefore, we investigated the task offloading problem in MEC, and proposed a computational task offloading scheme based on immune clone. Taking the minimization of energy cost as the objective and in consideration of the relationship between number of users unloaded in the computing and energy price. It can be solved by the immune clone algorithm and determined the optimal offloading scheme. Simulation results demonstrate the superiority of the proposed scheme over other the traditional task computing scheme. That this scheme can effectively reduce the system energy cost and improve the solving efficiency as compared to the traditional task computing scheme, in terms of the solving efficiency.
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Ben, W., Tingrui, L., Xun, H., Huahui, L. (2021). A Computing Task Offloading Scheme for Mobile Edge Computing. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12737. Springer, Cham. https://doi.org/10.1007/978-3-030-78612-0_9
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DOI: https://doi.org/10.1007/978-3-030-78612-0_9
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