An efficient computational offloading framework using HAA optimization-based deep reinforcement learning in edge-based cloud computing architecture-Reference-Cited by-同舟云学术

An efficient computational offloading framework using HAA optimization-based deep reinforcement learning in edge-based cloud computing architecture

Published:2022-10-26 Issue:1 Volume:65 Page:409-433
ISSN:0219-1377
Container-title:Knowledge and Information Systems
language:en
Short-container-title:Knowl Inf Syst

Author:

Saranya G.,Sasikala E.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s10115-022-01746-w.pdf

Reference38 articles.

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2. uz Zaman SK, Jehangiri AI, Maqsood T, Ahmad Z, Umar AI, Shuja J, Alanazi E, Alasmary W (2021) Mobility-aware computational offloading in mobile edge networks: a survey. Cluster Comput 1:1–22

3. Ali Z, Abbas ZH, Abbas G, Numani A, Bilal M (2021) Smart computational offloading for mobile edge computing in next-generation Internet of Things networks. Comput Netw 198:108356

4. Yu S, Wang X, Langar R (2017) Computation offloading for mobile edge computing: a deep learning approach. In: IEEE 28th annual international symposium on personal, indoor, and mobile radio communications (PIMRC). IEEE, pp 1–6

5. Zhang H, Yang Y, Huang X, Fang C, Zhang P (2021) Ultra-low latency multi-task offloading in mobile edge computing. IEEE Access 9:32569–32581

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