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Comparison of SLA based Energy Efficient Dynamic Virtual Machine Consolidation Algorithms

by Heena Kaushar, Pankaj Ricchariya, Anand Motwani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 102 - Number 16
Year of Publication: 2014
Authors: Heena Kaushar, Pankaj Ricchariya, Anand Motwani
10.5120/17901-8461

Heena Kaushar, Pankaj Ricchariya, Anand Motwani . Comparison of SLA based Energy Efficient Dynamic Virtual Machine Consolidation Algorithms. International Journal of Computer Applications. 102, 16 ( September 2014), 31-36. DOI=10.5120/17901-8461

@article{ 10.5120/17901-8461,
author = { Heena Kaushar, Pankaj Ricchariya, Anand Motwani },
title = { Comparison of SLA based Energy Efficient Dynamic Virtual Machine Consolidation Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 102 },
number = { 16 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume102/number16/17901-8461/ },
doi = { 10.5120/17901-8461 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:18.125076+05:30
%A Heena Kaushar
%A Pankaj Ricchariya
%A Anand Motwani
%T Comparison of SLA based Energy Efficient Dynamic Virtual Machine Consolidation Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 102
%N 16
%P 31-36
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing emerged as need for rapidly increasing computational power thus results in greater power consumption, increased operational costs and high carbon footprints to environment. A key issue for Cloud Providers is to maximize their profits by minimizing power consumption along with SLA considerations of hosted applications. Dynamic Virtual Machine (VM) consolidation is promising approach for reducing energy consumption by dynamically adjusting the number of active machines to match resource demands but it is one of the most important challenges in the cloud based distributed systems. In this work, the researchers tried to investigate “SLA and Energy-Efficient Dynamic Virtual Machine (VM) Consolidation” that meets Quality of Service expectations and Service Level Agreements (SLA) requirements. The analysis of VM consolidation algorithms based on various heuristics on legitimate host is presented as key contribution of this work. We also present a comparative analysis and results by conducting a performance evaluation study of various existing energy efficient VM consolidation techniques using real world workload traces from more than a thousand VMs using CloudSim toolkit. This paper is aimed at helping cloud providers analyze several power characteristics of their own technologies as well as pre-existing IT resources to identify their favorability in the migration to the new energy efficient cloud architectures. The results also helps in analyzing the existing frameworks and offers substantial energy savings while effectively dealing with firm QoS requirements negotiated by SLA.

References
  1. Ranganathan P, Leech P, Irwin D, Chase J. Ensemble-level power management for dense blade servers. Proceedings of the 33rd International Symposium on Computer Architecture (ISCA 2006), Boston, MA, USA, 2006; 66–77.
  2. Hosman, Laura; Baikie, Bruce, "Solar-Powered Cloud Computing Datacenters," IT Professional , vol.15, no.2, pp.15-21, March-April 2013.
  3. Anton Beloglazov, Jemal Abawajy, Rajkumar Buyya, “Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing”, Future Generation Computer Systems Volume 28, Issue 5, May 2012, pp. 755–768, Elsevier.
  4. Anton Beloglazov and Rajkumar Buyya, “Adaptive Threshold-Based Approach for Energy-Efficient Consolidation of Virtual Machines in Cloud Data Centers”, MGC ’2010, 29 November - 3 December 2010, Bangalore, India. Copyright 2010 ACM 978-1-4503-0453-5/10/11.
  5. Anton Beloglazov and Rajkumar Buyya, “Managing Overloaded Hosts for Dynamic Consolidation of Virtual Machines in Cloud Data Centers under Quality of Service Constraints”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 7, JULY 2013.
  6. Rajkumar Buyyaa, Chee Shin Yeoa, Srikumar Venugopala, James Broberg , Ivona Brandic, “Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility”, Future Generation Computer Systems 25 (2009) 599-616 Elsevier.
  7. Yue Gao; Yanzhi Wang; Gupta, S.K.; Pedram, M., "An energy and deadline aware resource provisioning, scheduling and optimization framework for cloud systems," Hardware/Software Codesign and System Synthesis (CODES+ISSS), 2013 International Conference on , vol., no., pp.1,10, Sept. 29 2013-Oct. 4 2013.
  8. Meng Wang, Xiaoqiao Meng, and Li Zhang, “Consolidating Virtual Machines with Dynamic Bandwidth Demand in Data Centers”, Mini Conference IEEE INFOCOM 2011, 978-1-4244-9920-5/11/ 2011 IEEE.
  9. Anton Beloglazov, Rajkumar Buyya, “Optimal online deterministic algorithms and adaptive heuris-tics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers”, Wiley InterScience, Concurr. Comput. : Pract. Exper., 24(13):1397-1420, September 2012.
  10. Beloglazov, A.; Buyya, R., "Energy Efficient Allocation of Virtual Machines in Cloud Data Centers," Cluster, Cloud and Grid Computing (CCGrid), 2010 10th IEEE/ACM International Conference on , vol., no., pp.577,578, 17-20 May 2010.
  11. M. Yue, “A simple proof of the inequality FFD (L)< 11/9 OPT (L)+ 1,for all l for the FFD bin-packing algorithm,” Acta Mathematicae Applicatae Sinica (English Series), vol. 7, no. 4, pp. 321–331, 1991.
  12. Hesham Hassan, Ahmed Shawky Moussa, “Power Aware Computing Survey”, International Journal of Computer Applications (0975 – 8887) Volume 90 – No.3, March 2014.
  13. Buyya R, Beloglazov A, Abawajy J. Energy-efficient management of data center resources for cloud computing: a vision, architectural elements, and open challenges” in Proceedings of the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2010). Las Vegas, USA, July 2010.
  14. Buyya, R.; Ranjan, R.; Calheiros, R.N., "Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities," High Performance Computing & Simulation, 2009. HPCS '09. International Conference on , vol., no., pp.1,11, 21-24 June 2009.
  15. Rodrigo N. Calheiros, Rajiv Ranjan, Anton Beloglazov, Cesar A. F. De Rose, and Rajkumar Buyya, “CloudSim: A Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms,” Software: Practice and Experience (SPE), Volume 41, Number 1, Pages: 23-50, ISSN: 0038-0644, Wiley Press, New York, USA, January, 2011.
  16. B. Guenter, N. Jain, and C. Williams, “Managing Cost, Performance, and Reliability Tradeoffs for Energy-Aware Server Provisioning,” Proc. IEEE INFOCOM, pp. 1332-1340, 2011.
  17. N. Bobroff, A. Kochut, and K. Beaty, “Dynamic Placement of Virtual Machines for Managing SLA Violations,” Proc. IFIP/ IEEE 10th Int’l Symp. Integrated Network Management (IM), pp. 119-128, 2007.
  18. Yuxiang Shi; Xiaohong Jiang; Kejiang Ye, "An Energy-Efficient Scheme for Cloud Resource Provisioning Based on CloudSim," Cluster Computing (CLUSTER), 2011 IEEE International Conference on , vol., no., pp.595,599, 26-30 Sept. 2011.
  19. Verma A, Ahuja P, Neogi A. pMapper: Power and migration cost aware application placement in virtualized systems. Proceedings of the 9th ACM/IFIP/USENIX International Conference on Middleware (Middleware 2008), Springer, Leuven, Belgium, 2008; 243–264.
  20. Y. Song, “Multi-Tiered On-Demand resource scheduling for VM-Based data center” In Proc. of the 2009 9th IEEE/ACM Intl. Symp. On Cluster Computing, 155, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing (CC) Cloud Providers Energy Energy efficient Quality of Service (QoS) Service Level Agreements (SLA) Virtual Machine (VM) VM Consolidation

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