1,337 research outputs found
Computation Offloading in Beyond 5G Networks: A Distributed Learning Framework and Applications
Facing the trend of merging wireless communications and multi-access edge
computing (MEC), this article studies computation offloading in the beyond
fifth-generation networks. To address the technical challenges originating from
the uncertainties and the sharing of limited resource in an MEC system, we
formulate the computation offloading problem as a multi-agent Markov decision
process, for which a distributed learning framework is proposed. We present a
case study on resource orchestration in computation offloading to showcase the
potentials of an online distributed reinforcement learning algorithm developed
under the proposed framework. Experimental results demonstrate that our
learning algorithm outperforms the benchmark resource orchestration algorithms.
Furthermore, we outline the research directions worth in-depth investigation to
minimize the time cost, which is one of the main practical issues that prevent
the implementation of the proposed distributed learning framework
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