PRINCIPIA: Opportunistic CPU and CPU-shares Allocation for Containerized Virtualization in Mobile Edge Computing

Ocampo, Andres F, Mah Rukh, Fida ORCID: 0000-0001-7660-1150, F. Botero, Juan, Elmokashfi, Ahmed and Bryhni, Haakon (2023) PRINCIPIA: Opportunistic CPU and CPU-shares Allocation for Containerized Virtualization in Mobile Edge Computing. In: NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, pp. 1-7. ISBN 9781665477161

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Text 13909 Ocampo Andres F et al (2023) PRINCIPIA Opportunistic CPU and CPU-shares Allocation for Containerized Virtualization in Mobile Edge Computing -Accepted version.pdf - Accepted Version Available under License All Rights Reserved. Download (458kB) | Preview

Abstract

Leveraging virtualization technology, Mobile Edge Computing (MEC) deploys multiple services with different execution time requirements running as isolated processes. For instance, both real-time (RT) and non-RT applications may be (are) running on the same infrastructure using containerized virtualization. Nevertheless, sharing resources (e.g., CPU) with collocated workloads could impact the RT performance of RT applications. This paper presents PRINCIPIA, a dynamic CPU and CPU-shares allocation mechanism that opportunistically enables non-RT applications to run on underutilized CPUs while providing RT guarantees to RT applications. By monitoring MEC’s system metrics like processor’s CPU utilization and container’s CPU usage, PRINCIPIA dynamically allocates both CPU and CPU-shares to containers running non-RT applications aiming at opportunistically exploiting underutilized CPUs by containers running RT applications. We evaluate PRINCIPIA on a small-scale MEC server which uses containerized virtualization along with Linux RT Kernel to deploy both RT and non-RT applications. Our findings show that PRINCIPIA mitigates the impact on the RT performance of RT applications providing bounded processing latency in comparison with the default host Kernel scheduler.

Item Type:	Book Section
Uncontrolled Keywords:	Mobile Edge Computing; Virtualization; Containers; Real-time containers; CPU sharing; CPU allocation
Related URLs:	Publisher
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 10:37
Last Modified:	26 Apr 2024 13:53
URI:	https://eprints.glos.ac.uk/id/eprint/13909

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