| Autor: |
Hossain, M. Shamim, Hao, Yixue, Hu, Long, Liu, Jia, Wei, Gang, Min, Chen |
| Předmět: |
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| Zdroj: |
ACM Transactions on Multimedia Computing, Communications & Applications; Jun2024, Vol. 20 Issue 6, p1-23, 23p |
| Abstrakt: |
Immersive service caching, based on the intelligent edge cloud, can meet delay-sensitive service requirements. Although numerous service caching solutions for edge clouds have been designed, they have not been well explored. Moreover, to the best of our knowledge, there is no work to consider the immersive service caching scheme under the supply of renewable energy. In this article, we investigate the service caching problem under the renewable energy supply to minimize service latency while making full use of renewable energy. Specifically, we formulate the service caching and renewable energy harvesting problem, which considers the dynamic renewable energy, unknown service requests, and limited capacity of the edge cloud. To solve this problem, we propose an effective algorithm, called OSCRE. Our algorithm first uses Lyapunov optimization to convert the time-average problem into time-independence optimization and thus realizes optimal renewable energy harvesting. Then, it realizes the service caching scheme using data-driven combinatorial multi-armed bandit learning. The simulation results show that the OSCRE scheme can save service latency while making sufficient use of renewable energy. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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