Deep reinforcement learning based task offloading and resource allocation strategy across multiple edge servers

In the mobile edge computing environment, multiple edge servers are often deployed in task-dense areas, however, the service coverage of these edge servers may overlap with each other. In such scenarios, users within the overlapping areas need to determine which server is chosen to offload the task....

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Veröffentlicht in:	Service oriented computing and applications Jg. 19; H. 3; S. 263 - 276
Hauptverfasser:	Shi, Bing, Pan, Yuting, Huang, Lianzhen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.09.2025 Springer Nature B.V
Schlagworte:	Algorithms Computation offloading Computer Appl. in Administrative Data Processing Computer Science Computer Systems Organization and Communication Networks Deep learning e-Commerce/e-business Edge computing Energy consumption Game theory Heuristic Internet of Things IT in Business Machine learning Management of Computing and Information Systems Markov processes Mobile computing Original Research Paper Parameterization Resource allocation Servers Software Engineering/Programming and Operating Systems Multiple edge servers Deep reinforcement learning Task offloading Resource allocation
ISSN:	1863-2386, 1863-2394
Online-Zugang:	Volltext
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