An Online Mean Field Approach for Hybrid Edge Server Provision
Author:
Affiliation:
1. The Chinese University of Hong Kong
2. Network Technology Lab, Huawei Technologies Co., Ltd.
Funder
The Chinese University of Hong Kong
University Grants Committee
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3466772.3467042
Reference28 articles.
1. Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing
2. Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing
3. Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices
4. Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks
5. Asymptotically optimal algorithm for online reconfiguration of edge-clouds
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1. Online Approximation Scheme for Scheduling Heterogeneous Utility Jobs in Edge Computing;IEEE/ACM Transactions on Networking;2023-02
2. Toward Large-Scale Hybrid Edge Server Provision: An Online Mean Field Learning Approach;IEEE Journal on Selected Areas in Communications;2022-08
3. Decentralized Scheduling and Dynamic Pricing for Edge Computing: A Mean Field Game Approach;IEEE/ACM Transactions on Networking;2022
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