Abstract
The mobile edge computing (MEC) system is a new way to offer cloud computing capabilities at the edge of the radio access network (RAN). In an edge computing system, multiple servers are placed on the edge of the network near the mobile device to process offloading tasks. A key issue in the edge computing system is how to reduce the system cost while completing the offloaded tasks. In this paper, we study the task scheduling problem to reduce the cost of the edge computing system. We model the task scheduling problem as an optimization problem, where the goal is to reduce the system cost while satisfying the delay requirements of all the tasks. To solve this optimization problem effectively, we propose a task scheduling algorithm, called MATSCO. We validate the effectiveness of our algorithm by comparing with optimal solutions. Performance evaluation shows that our algorithm can effectively reduce the cost of the edge computing system.
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Acknowledgements
This work is supported by the Fundamental Research Funds for the Central Universities under Grant 2019RC09.
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Tan, J., Li, W., Liu, H., Feng, L. (2021). MATSCO: A Novel Minimum Cost Offloading Algorithm for Task Execution in Multiuser Mobile Edge Computing Systems. In: Liu, Q., Liu, X., Li, L., Zhou, H., Zhao, HH. (eds) Proceedings of the 9th International Conference on Computer Engineering and Networks . Advances in Intelligent Systems and Computing, vol 1143. Springer, Singapore. https://doi.org/10.1007/978-981-15-3753-0_23
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DOI: https://doi.org/10.1007/978-981-15-3753-0_23
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