Next Article in Journal
Total Coloring Conjecture for Certain Classes of Graphs
Next Article in Special Issue
Special Issue on Algorithms for the Resource Management of Large Scale Infrastructures
Previous Article in Journal
A Faster Algorithm for Reducing the Computational Complexity of Convolutional Neural Networks
Previous Article in Special Issue
SLoPCloud: An Efficient Solution for Locality Problem in Peer-to-Peer Cloud Systems
Article Menu

Export Article

Open AccessArticle
Algorithms 2018, 11(10), 160; https://doi.org/10.3390/a11100160

Modeling and Evaluation of Power-Aware Software Rejuvenation in Cloud Systems

1
Department of Computer Engineering, Sharif University of Technology, Tehran 1458889694, Iran
2
Department of Engineering and Technology, University of Mazandaran, Babolsar 4741613534, Iran
*
Author to whom correspondence should be addressed.
Received: 30 August 2018 / Revised: 13 October 2018 / Accepted: 15 October 2018 / Published: 18 October 2018
(This article belongs to the Special Issue Algorithms for the Resource Management of Large Scale Infrastructures)
Full-Text   |   PDF [1954 KB, uploaded 18 October 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 Infrastructure-as-a-Service cloud systems. Using the proposed model, a two-threshold power-aware software rejuvenation scheme is presented. Many details of real cloud systems, such as VM multiplexing, migration of VMs between VMMs, VM heterogeneity, failure of VMMs, failure of VM migration, and different probabilities for arrival of different VM request types are investigated using the proposed model. The performance of the proposed rejuvenation scheme is compared with two baselines based on diverse performance, availability, and power consumption measures defined on the system. View Full-Text
Keywords: cloud computing; software rejuvenation; aged software; performance evaluation cloud computing; software rejuvenation; aged software; performance evaluation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Fakhrolmobasheri, S.; Ataie, E.; Movaghar, A. Modeling and Evaluation of Power-Aware Software Rejuvenation in Cloud Systems. Algorithms 2018, 11, 160.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top