Journal
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
Volume 72, Issue -, Pages 180-192Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.future.2016.07.001
Keywords
Metal-as-a-service; Cloud Computing; Advance reservation; Provisioning; Bigstep Full Metal Cloud; Multi-variable regression
Categories
Funding
- DataWay: Real-time Data Processing Platform for Smart Cities: Making sense of Big Data [PN-II-RU-TE-2014-4-2731]
- MobiWay: Mobility Beyond Individualism: an Integrated Platform for Intelligent Transportation Systems of Tomorrow [PN-II-PT-PCCA-2013-4-0321]
- Romanian National Authority for Scientific Research, CNDI-UEFISCDI [47/2012]
- clueFarm: Information system based on cloud services accessible through mobile devices [PN-II-PT-PCCA-2013-4-0870]
- DataWay: Real-time Data Processing Platform for Smart Cities: Making sense of Big Data [PN-II-RU-TE-2014-4-2731]
- MobiWay: Mobility Beyond Individualism: an Integrated Platform for Intelligent Transportation Systems of Tomorrow [PN-II-PT-PCCA-2013-4-0321]
- Romanian National Authority for Scientific Research, CNDI-UEFISCDI [47/2012]
- clueFarm: Information system based on cloud services accessible through mobile devices [PN-II-PT-PCCA-2013-4-0870]
Ask authors/readers for more resources
Cloud management automation and management of SLA incidents become a research challenges for any Cloud service-based system. In the era of ongoing adoption of Cloud Computing at a fast rate the Metal-as-a-service (MaaS) platforms assure a higher level of performance, but at the cost of a more complex provisioning system, all of these being imposed by SLA assurance. More, disaster recovery and critical infrastructure protection become important aspects for any real-time applications that use Cloud Services. This paper deals with the problem of predicting provisioning and booting times in a MaaS system, and proposed a solution based on platform monitoring and a multi-variate regression algorithm. The configuration, provisioning flow, and capacity management capabilities were tested on Bigstep Full Metal Cloud platform an event-based tracking system, based on which provisioning times can be calculated for each individual element. We analyzed the performance of proposed solution by comparing the predicted booting and provisioning times with real times using different scenarios. (C) 2016 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available