An Energy-Efficient Sleeping Strategy for Multi-access Edge Computing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00385237" target="_blank" >RIV/68407700:21230/25:00385237 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/WCNC61545.2025.10978367" target="_blank" >https://doi.org/10.1109/WCNC61545.2025.10978367</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WCNC61545.2025.10978367" target="_blank" >10.1109/WCNC61545.2025.10978367</a>
Alternative languages
Result language
angličtina
Original language name
An Energy-Efficient Sleeping Strategy for Multi-access Edge Computing
Original language description
In this paper, we focus on the scenario with offloading of computationally intensive tasks with delay constraints from users equipment (UEs) to multi-access edge computing (MEC) servers. To avoid user's dissatisfaction with offered quality of service, the computing resources should be able to handle even peak hours. As a result, a dense deployment of MEC servers should be considered in order to bring sufficient computing resources close to the UEs, thus enabling a low delay services. However, at the same time, the dense deployment of powerful MEC servers results, among others, in a high energy consumption. In this paper, we address the high energy consumption problem via a smart sleeping of the MEC servers while preserving quality of service for the UEs. To this end, we determine a set of MEC servers that should stay active and provide computation resources for the offloaded tasks while still meeting UEs requirements on delay. We formulate the problem of selecting the MEC server that can be set into sleep mode to save energy as a minimum set cover problem. Then, we propose a solution to minimize the energy consumption based on branch-and-bound algorithm to activate the MEC servers for computation ensuring the UEs requirement on delay. The effectiveness of the proposed solution is demonstrated through simulations showing that the proposal allows to save up to 34.9% of energy compared to state-of-the-art works while even slightly improving the ratio of offloaded tasks processed within required delay.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/LUASK22064" target="_blank" >LUASK22064: Predictive allocation of edge computing resources for autonomous driving</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>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
Article name in the collection
2025 IEEE Wireless Communications and Networking Conference (WCNC)
ISBN
979-8-3503-6836-9
ISSN
1558-2612
e-ISSN
1558-2612
Number of pages
6
Pages from-to
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Publisher name
IEEE
Place of publication
Milano
Event location
Milan
Event date
Mar 24, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001514465200249