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Modeling and Evaluation of Software Rejuvenation in Cloud Computing
, M.Sc. Thesis Sharif University of Technology ; Movaghar, Ali (Supervisor)
Abstract
Long and continuous running of software is likely to cause software aging-induced errors and failures. Cloud service centers suffer from such errors because of degradation of virtual machine monitors (VMMs) that oversee the execution of virtual machines (VMs). The proposed solution to prevent such VMM failures is to use a rejuvenation scheme for planned termination and restarting of monitor software. The best measure to determine the optimum time of rejuvenation is the VMM’s age, that is, the cumulative workload carried out since the last reboot, repair, or rejuvenation. This paper provides an analytical model based on stochastic activity network (SAN) tool for performance evaluation of...
Modeling and evaluation of power-aware software Rejuvenation in Cloud Systems
, Article Algorithms ; Volume 11, Issue 10 , 2018 ; 19994893 (ISSN) ; Ataie, E ; Movaghar, A ; Sharif University of Technology
MDPI AG
2018
Abstract
Long and continuous running of software can cause software aging-induced errors and failures. Cloud data centers suffer from these kinds of failures when Virtual Machine Monitors (VMMs), which control the execution of Virtual Machines (VMs), age. Software rejuvenation is a proactive fault management technique that can prevent the occurrence of future failures by terminating VMMs, cleaning up their internal states, and restarting them. However, the appropriate time and type of VMM rejuvenation can affect performance, availability, and power consumption of a system. In this paper, an analytical model is proposed based on Stochastic Activity Networks for performance evaluation of...