Abstract
The edge user allocation (EUA) problem has attracted a lot of attention recently. EUA aims at allocating edge users to nearby edge servers strategically to ensure low-latency network connection. Existing approaches assume that a users’ request can only be served by an individual edge server or cannot be served at all. They neglect the fact that a user’s request may be decomposable and partitioned into multiple tasks to be performed by different edge servers. To tackle this new task-decomposable edge user allocation (TD-EUA) problem, we model it as an optimization problem. Two novel approaches named TD-EUA-O and TD-EUA-H are proposed, one for finding the optimal solution based on Integer Linear Programming that maximizes users’ overall Quality of Experience (QoE), and the other for efficiently finding a sub-optimal solution in large-scale EUA scenarios. Extensive experiments based on a widely-used real-world dataset are conducted to evaluate the effectiveness and efficiency of our approaches. The results demonstrate that our approaches significantly outperform the baseline and the state-of-the-art approach.
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Acknowledgments
This work was partially supported by Shanghai Natural Science Foundation (No. 18ZR1414400), National Key Research and Development Program of China (No. 2017YFC0907505), National Natural Science Foundation of China (No. 61772128) and Australian Research Council Discovery Projects (DP18010021 and DP200102491).
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Zou, G. et al. (2020). TD-EUA: Task-Decomposable Edge User Allocation with QoE Optimization. In: Kafeza, E., Benatallah, B., Martinelli, F., Hacid, H., Bouguettaya, A., Motahari, H. (eds) Service-Oriented Computing. ICSOC 2020. Lecture Notes in Computer Science(), vol 12571. Springer, Cham. https://doi.org/10.1007/978-3-030-65310-1_17
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DOI: https://doi.org/10.1007/978-3-030-65310-1_17
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