Dynamic Computation Offloading Based on Deep Reinforcement Learning

BaiChuan Cheng; Zhilong Zhang; DanPu Liu

doi:10.4108/eai.29-6-2019.2282108

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Dynamic Computation Offloading Based on Deep Reinforcement Learning

BaiChuan Cheng Zhilong Zhang DanPu Liu

Year: 2019

DOI: 10.4108/eai.29-6-2019.2282108

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Abstract

Mobile edge computing (MEC) provides computation capability at the edge of wireless network. To reduce the execution delay, computation-intensive multimedia tasks can be offloaded from user equipments (UEs) to the MEC server. How to allocate the computational and wireless resources is one of the key

Keywords:

Computer science Computation offloading Computation Mobile edge computing Reinforcement learning Wireless Edge computing Enhanced Data Rates for GSM Evolution Wireless network Computer network Distributed computing Server Edge device Key (lock) Mobile device Operating system Artificial intelligence Cloud computing

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Brain Tumor Detection and Classification

Life Sciences → Neuroscience → Neurology

IoT and Edge/Fog Computing

Physical Sciences → Computer Science → Computer Networks and Communications

Dynamic Computation Offloading Based on Deep Reinforcement Learning

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