3D analytical modelling and iterative solution for high performance computing clusters

Kirsal, Yonal, Kirsal Ever, Yoney, Mapp, Glenford E. ORCID: https://orcid.org/0000-0002-0539-5852 and Raza, Mohsin ORCID: https://orcid.org/0000-0002-7351-9749 (2021) 3D analytical modelling and iterative solution for high performance computing clusters. IEEE Transactions on Cloud Computing . ISSN 2168-7161 [Article] (Published online first) (doi:10.1109/TCC.2021.3055119)

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Abstract

Mobile Cloud Computing enables the migration of services to the edge of the Internet. Therefore, high-performance computing clusters are widely deployed to improve computational capabilities of such environments. However, they are prone to failures and need analytical models to predict their behaviour in order to deliver desired quality-of-service and quality-of-experience to mobile users. This paper proposes a 3D analytical model and a problem-solving approach for sustainability evaluation of high-performance computing clusters. The proposed solution uses an iterative approach to obtain performance measurements to overcome the state space explosion problem. The availability modelling and evaluation of master and computing nodes are performed using a multi-repairman approach. The optimum number of repairmen is also obtained to get realistic results and reduce the overall cost. The proposed model is validated using discrete event simulation. The analytical approach is much faster and in good agreement with the simulations. The analysis focuses on mean queue length, throughput, and mean response time outputs. The maximum differences between analytical and simulation results in the considered scenarios of up to a billion states are less than1.149%,3.82%, and3.76%respectively. These differences are well within the5%of confidence interval of the simulation and the proposed model.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 32181
Notes on copyright: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Depositing User: Glenford Mapp
Date Deposited: 08 Mar 2021 11:37
Last Modified: 30 Sep 2021 15:59
URI: https://eprints.mdx.ac.uk/id/eprint/32181

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