Optimal Proactive Resource Allocation at the Extreme Edge

Author:

El Khatib Rawan F.1,Elsayed Sara A.2,Zorba Nizar3,Hassanein Hossam S.2

Affiliation:

1. Queen’s University,Department of Electrical and Computer Engineering,Canada

2. Queen’s University,School of Computing,Canada

3. Qatar University,Department of Electrical Engineering,Qatar

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

IEEE

Reference15 articles.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. DRUDGE: Dynamic Resource Usage Data Generation for Extreme Edge Devices;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

2. Dynamic Worker Availability Prediction at the Extreme Edge;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

3. Uncertainty-Aware Multitask Allocation for Parallelized Mobile Edge Learning;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

4. RUMP: Resource Usage Multi-Step Prediction in Extreme Edge Computing;Computer Communications;2023-10

5. QoE-Aware Edge-Assisted Machine Learning-Based Fall Detection and Prediction with FBGs;ICC 2023 - IEEE International Conference on Communications;2023-05-28

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