S. Abar
Automated Dynamic Resource Provisioning and Monitoring in Virtualized Large-Scale Datacenter
Abar, S.; Lemarinier, P.; Theodoropoulos, G.; OHare, G.
Authors
P. Lemarinier
G. Theodoropoulos
G. OHare
Abstract
Infrastructure as a Service (IaaS) is a pay-as-you go based cloud provision model which on demand outsources the physical servers, guest virtual machine (VM) instances, storage resources, and networking connections. This article reports the design and development of our proposed innovative symbiotic simulation based system to support the automated management of IaaS-based distributed virtualized data enter. To make the ideas work in practice, we have implemented an Open Stack based open source cloud computing platform. A smart benchmarking application "Cloud Rapid Experimentation and Analysis Tool (aka CBTool)" is utilized to mark the resource allocation potential of our test cloud system. The real-time benchmarking metrics of cloud are fed to a distributed multi-agent based intelligence middleware layer. To optimally control the dynamic operation of prototype data enter, we predefine some custom policies for VM provisioning and application performance profiling within a versatile cloud modeling and simulation toolkit "CloudSim". Both tools for our prototypes' implementation can scale up to thousands of VMs, therefore, our devised mechanism is highly scalable and flexibly be interpolated at large-scale level. Autonomic characteristics of agents aid in streamlining symbiosis among the simulation system and IaaS cloud in a closed feedback control loop. The practical worth and applicability of the multiagent-based technology lies in the fact that this technique is inherently scalable hence can efficiently be implemented within the complex cloud computing environment. To demonstrate the efficacy of our approach, we have deployed an intelligible lightweight representative scenario in the context of monitoring and provisioning virtual machines within the test-bed. Experimental results indicate notable improvement in the resource provision profile of virtualized data enter on incorporating our proposed strategy.
Citation
Abar, S., Lemarinier, P., Theodoropoulos, G., & OHare, G. (2014). Automated Dynamic Resource Provisioning and Monitoring in Virtualized Large-Scale Datacenter. In 2014 IEEE 28th International Conference on Advanced Information Networking and Applications (AINA) : 13-16 May 2014, University of Victoria, Victoria, Canada (961-970). https://doi.org/10.1109/aina.2014.117
Conference Name | 2014 IEEE 28th International Conference on Advanced Information Networking and Applications |
---|---|
Conference Location | Victoria, Victoria, Canada |
Start Date | May 13, 2014 |
End Date | May 16, 2014 |
Publication Date | May 16, 2014 |
Deposit Date | Apr 21, 2016 |
Publicly Available Date | Apr 28, 2016 |
Pages | 961-970 |
Series ISSN | 1550-445X |
Book Title | 2014 IEEE 28th International Conference on Advanced Information Networking and Applications (AINA) : 13-16 May 2014, University of Victoria, Victoria, Canada. |
DOI | https://doi.org/10.1109/aina.2014.117 |
Additional Information | Date of Conference: 13-16 May 2014 |
Files
Accepted Conference Proceeding
(1.3 Mb)
PDF
Copyright Statement
© 2014 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.
You might also like
Efficient Comparison of Massive Graphs Through The Use Of 'Graph Fingerprints'
(2016)
Conference Proceeding
Towards large-scale what-if traffic simulation with exact-differential simulation
(2015)
Conference Proceeding
Data Quality Assessment and Anomaly Detection Via Map / Reduce and Linked Data: A Case Study in the Medical Domain
(2015)
Conference Proceeding
Fast Compression of Large Semantic Web Data using X10
(2015)
Journal Article
Towards an Info-Symbiotic Decision Support System for Disaster Risk Management
(2015)
Conference Proceeding
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search