Opportunistic CPU Sharing in Mobile Edge Computing Deploying the Cloud-RAN

Ocampo, Andres F ORCID: 0000-0001-6926-0992, Mah Rukh, Fida ORCID: 0000-0001-7660-1150, F. Botero, Juan, Elmokashfi, Ahmed and Bryhni, Haakon (2023) Opportunistic CPU Sharing in Mobile Edge Computing Deploying the Cloud-RAN. IEEE Transactions on Network and Service Management, 20 (3). pp. 2201-2217. doi:10.1109/TNSM.2023.3304067

13912 Ocampo, Andres F et al (2023) Opportunistic CPU Sharing in Mobile Edge Computing Deploying the Cloud RAN - Accepted version.pdf - Accepted Version
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Leveraging virtualization technology, Cloud-RAN deploys multiple virtual Base Band Units (vBBUs) along with collocated applications on the same Mobile Edge Computing (MEC) server. However, the performance of real-time (RT) applications such as the vBBU could potentially be impacted by sharing computing resources with collocated workloads. To address this challenge, this paper presents a dynamic CPU sharing mechanism, specifically designed for containerized virtualization in MEC servers, that hosts both RT and non-RT general-purpose applications. Initially, the CPU sharing problem in MEC servers is formulated as a Mixed-Integer Programming (MIP). Then, we present an algorithmic solution that breaks down the MIP into simpler subproblems that are then solved using efficient, constant factor heuristics. We assessed the performance of this mechanism against instances of a commercial solver. Further, via a small-scale testbed, we assessed various CPU sharing mechanisms and their effectiveness in reducing the impact of CPU sharing indicate that our CPU sharing mechanism reduces the worstcase execution time by more than 150% compared to the default host RT-Kernel approach. This evidence is strengthened when evaluating this mechanism within Cloud-RAN, in which vBBUs share resources with collocated applications on a MEC server. Using our CPU sharing approach, the vBBU’s scheduling latency decreases by up to 21% in comparison with the host RT-Kernel.

Item Type: Article
Article Type: Article
Additional Information: Full published version is available to current University of Gloucestershire students and staff via the IEEE database, see publisher link below.
Uncontrolled Keywords: Containers; Servers; Cloud computing; Virtualization; Resource management; Kernel; Linux; Cloud-RAN; Mobile edge computing; Containers; Resource management
Related URLs:
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas: Applied Business & Technology
Depositing User: Mah Rukh
Date Deposited: 17 Apr 2024 11:01
Last Modified: 30 Apr 2024 12:33
URI: https://eprints.glos.ac.uk/id/eprint/13912

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