Abstract
Quality features are important to be taken into account while allocating resource in Cloud Computing, since it allows to provide to the users or customers, high Quality of Service (QoS) with best response time as example and respects the Service Level Agreement (SLA) established.
Indeed, it is not easy to handle efficiently resource allocation processes in Cloud, since, the applications deployed on Cloud present non-uniform usage patterns, and the cloud allocation architecture needs to provide different scenarios of resource allocation to satisfy the demands and provide quality. In order to provide the measurement of quality indexes, the Cloud resource allocation architecture needs to be proactive and reactive.
The goal of this paper is to propose a resource allocation’ architecture for Cloud Computing that provides the measurement of quality indicators identified between the Key Performance Indicators (KPI) defined by the Cloud Services Measurement Initiative Consortium (CSMIC). Our architecture proposes different resource allocation policies: predictive and reactive. The allocation decisions are taken in this architecture, according to the SLA. Finally, the preliminary experimental results show that our proposed architecture can improve quality in Cloud.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
National Institute of Standards and Technology (NIST), http://www.nist.gov/itl/cloud/index.cfm
Cloud Service Measurement Initiative Consortium (CSMIC), Service Measurement Index, http://www.cloudcommons.com/
Velte, A.T., Velte, T.J., Elsenpeter, R.: Cloud Computing: A Practical Approach. McGraw-Hill (October 2009)
Garg, S.K., Versteeg, S., Buyya, R.: SMICloud: A Framework for Comparing and Ranking Cloud Services. In: 4th IEEE International Conference on Utility and Cloud Computing, pp. 210–218 (2011)
Chandra, A., Gong, W., Shenoy, P.: Dynamic resource allocation for shared data centers using online measurements. In: SIGMETRICS 2003: Proceedings of the 2003 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (2003)
Caron, E., Desprez, F., Muresan, A.: Pattern Matching Based Forecast of Non-periodic Repetitive Behavior for Cloud Clients. J. Grid Computing, 49–64 (2011)
Rightscale inc., http://support.rightscale.com/
Buyya, R., Garg, S.K., Calheiros, R.N.: SLA-Oriented Resource Provisioning for Cloud Computing: Challenges, Architecture, and Solutions. In: Proceedings of the 2011 IEEE International Conference on Cloud and Service Computing (CSC 2011). IEEE Press, USA (2011)
Tran, V., Tsuji, H., Masuda, R.: A new qos ontology and its qos-based ranking algorithm for web services. Simulation Modelling Practice and Theory 17(8), 1378–1398 (2009)
Calheiros, R.N., Ranjan, R., Beloglazov, A., De Rose, C.A.F., Buyya, R.: CloudSim: A Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms. Software: Practice and Experience 41(1), 23–50 (2011) ISSN: 0038-0644
Beloglazov, A., Buyya, R.: Optimal Online Deterministic Algorithms and Adaptive Heuristics for Energy and Performance Efficient Dynamic Consolidation of Virtual Machines in Cloud Data Centers. Concurrency and Computation: Practice and Experience (2011), doi:10.1002/cpe.1867, ISSN: 1532-0626
Amazon EC2 Instance, http://aws.amazon.com/ec2/instance-types
Park, K., Pai, V.S.: CoMon: A mostly-scalable monitoring system for PlanetLab. ACM SIGOPS Operating Systems Review 40(1), 65–74 (2006)
PlanetLab, An open platform for developing, deploying and accessing planetary-scale services, http://planet-lab.org
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sagbo, K.A.R., Houngue, P. (2012). Quality Architecture for Resource Allocation in Cloud Computing. In: De Paoli, F., Pimentel, E., Zavattaro, G. (eds) Service-Oriented and Cloud Computing. ESOCC 2012. Lecture Notes in Computer Science, vol 7592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33427-6_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-33427-6_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33426-9
Online ISBN: 978-3-642-33427-6
eBook Packages: Computer ScienceComputer Science (R0)