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GPU-specific Task Offloading in the Mobile Edge Computing Network
- Authors
- Kim, N.; Lee, Y.; Lee, C.; Nguyen, T.V.; Tuong, V.D.; Cho, Sungrae
- Issue Date
- Oct-2020
- Publisher
- IEEE Computer Society
- Keywords
- GPU-specific task; mobile edge computing; task offloading
- Citation
- International Conference on ICT Convergence, v.2020-October, pp 1874 - 1876
- Pages
- 3
- Journal Title
- International Conference on ICT Convergence
- Volume
- 2020-October
- Start Page
- 1874
- End Page
- 1876
- ISSN
- 2162-1233
- Abstract
- Graphics processing unit (GPU)-specific tasks can be done by mobile edge computing in 5G networks because user equipments (UEs) offload the tasks near to Edge Server such as smart phones, access points, and so on. The data produced by Internet of Things devices can not be managed by traditional cloud computing system because of limited resource. Edge Computing is promising solution to this problem. The edge computing server is placed at the edge of network near the UEs. As a result, edge computing system guarantees low latency and energy-efficient task processing of the UEs. This paper introduces the system model for GPU-specific Task Offloading in the Mobile Edge Computing Networks and discusses the solutions for this problem. © 2020 IEEE.
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