A Novel Resource Allocation Algorithm in Edge Computing with Deep Reinforcement Learning, M.Sc. Thesis Sharif University of Technology ; Movaghar, Ali (Supervisor)
Abstract
With the explosion of mobile smart devices, many computation intensive applications have emerged, such as interactive gaming and augmented reality. Mobile edge computing (EC) is put forward, as an extension of cloud computing, to meet the low-latency require- ments of the applications. In mobile edge computing systems, an edge node may have a high load when a large number of mobile devices offload their tasks to it. those offloaded tasks may experience large processing delay or even be dropped when their deadlines expire. Due to the uncertain load dynamics at the edge nodes, it is challenging for each device to determine its offloading decision (i.e., whether to offload or not, and which...
Cataloging briefA Novel Resource Allocation Algorithm in Edge Computing with Deep Reinforcement Learning, M.Sc. Thesis Sharif University of Technology ; Movaghar, Ali (Supervisor)
Abstract
With the explosion of mobile smart devices, many computation intensive applications have emerged, such as interactive gaming and augmented reality. Mobile edge computing (EC) is put forward, as an extension of cloud computing, to meet the low-latency require- ments of the applications. In mobile edge computing systems, an edge node may have a high load when a large number of mobile devices offload their tasks to it. those offloaded tasks may experience large processing delay or even be dropped when their deadlines expire. Due to the uncertain load dynamics at the edge nodes, it is challenging for each device to determine its offloading decision (i.e., whether to offload or not, and which...
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