Computation offloading based on incomplete information in edge computing networks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10258634" target="_blank" >RIV/61989100:27240/25:10258634 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s10586-025-05560-1" target="_blank" >https://link.springer.com/article/10.1007/s10586-025-05560-1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10586-025-05560-1" target="_blank" >10.1007/s10586-025-05560-1</a>
Alternative languages
Result language
angličtina
Original language name
Computation offloading based on incomplete information in edge computing networks
Original language description
Mobile edge computing meets stringent latency requirements by offloading computational tasks to edge servers. However, in dynamic and uncertain environments, assigning tasks to multiple users becomes complex. To address this challenge, we design a multi-user task offloading framework that allows users to initiate service requests in a distributed manner. Specifically, we propose an online learning offloading algorithm based on a distributed auction multi-armed bandit, which can adapt to stochastically changing environments and gradually reduce computational latency. We then transform the dynamic task allocation problem into an online multi-user multi-armed bandit problem and develop an offloading algorithm based on heterogeneous distributed multi-armed bandit (HD-MAB) to optimize user rewards subject to network latency. We demonstrate that the HD-MAB algorithm can achieve optimal task allocation, thereby providing near-optimal service performance with linear regret. Simulation results show that our offloading method performs well in optimizing latency-sensitive tasks, and that user participation in the decision-making process of the HD-MAB algorithm does not affect the asymptotic optimality of the algorithm.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Cluster Computing-The Journal of Networks Software Tools and Applications
ISSN
1386-7857
e-ISSN
1573-7543
Volume of the periodical
28
Issue of the periodical within the volume
14
Country of publishing house
US - UNITED STATES
Number of pages
18
Pages from-to
nestránkováno
UT code for WoS article
001586153500048
EID of the result in the Scopus database
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