Abstract
The deployment of edge computing forms a two-tier mobile computing network where each computation task can be processed locally or at the edge node. In this paper, we consider a single mobile device equipped with a list of heavy off-loadable tasks. Our goal is to jointly optimize the offloading decision and the computing resource allocation to minimize the overall tasks processing time. The formulated optimization problem considers both the dedicated energy capacity and the processing deadlines. Therefore, as the obtained problem is NP-hard and we proposed a simulated annealing-based heuristic solution scheme. In order to evaluate and compare our solution, we carried a set of simulation experiments. Finally, the obtained results in terms of total processing time are very encouraging. In addition, the proposed scheme generates the solution within acceptable and feasible timeframes.
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El Ghmary, M., Chanyour, T., Hmimz, Y., Cherkaoui Malki, M.O. (2020). Processing Time and Computing Resources Optimization in a Mobile Edge Computing Node. In: Bhateja, V., Satapathy, S., Satori, H. (eds) Embedded Systems and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1076. Springer, Singapore. https://doi.org/10.1007/978-981-15-0947-6_10
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DOI: https://doi.org/10.1007/978-981-15-0947-6_10
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