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Offloading Time Optimization via Markov Decision Process in Mobile-Edge Computing
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DOI：10.1109/JIOT.2020.3033285.png)
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Abstract
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Computation offloading from a mobile device to the edge server is an emerging paradigm to reduce completion latency of intensive computations in mobile-edge computing (MEC). In order to satisfy the delay-sensitive computing tasks, offloading time, including task uploading time, task execution time, and results downloading time is adopted as the computational performance metrics for offloading nodes that perform offloaded computing tasks for mobile devices. Therefore, how to minimize the offloading time by selecting an optimal offloading node in MEC is of research importance. This work first investigates a MEC system consisting of mobile devices and heterogeneous edge severs that support various radio access technologies. Then, based on the available bandwidth of heterogeneous edge severs and the location of mobile devices, an optimal offloading node selection strategy is formulated as a Markov decision process (MDP), and solved by employing the value iteration algorithm (VIA). Finally, extensive numerical results demonstrate the effectiveness of the proposed strategy over classic strategies in terms of offloading time.
Keywords:
Task analysis
Mobile handsets
Servers
Bandwidth
Cloud computing
Edge computing
Wireless fidelity
Computation offloading
Markov decision process (MDP)
mobile-edge computing (MEC)
offloading time
value iteration algorithm (VIA)
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