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Dynamic Consolidation of Virtual Machines with Multi-Agent System

by Esha Barlaskar, Y. Jayanta Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 94 - Number 9
Year of Publication: 2014
Authors: Esha Barlaskar, Y. Jayanta Singh
10.5120/16373-5831

Esha Barlaskar, Y. Jayanta Singh . Dynamic Consolidation of Virtual Machines with Multi-Agent System. International Journal of Computer Applications. 94, 9 ( May 2014), 30-38. DOI=10.5120/16373-5831

@article{ 10.5120/16373-5831,
author = { Esha Barlaskar, Y. Jayanta Singh },
title = { Dynamic Consolidation of Virtual Machines with Multi-Agent System },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 94 },
number = { 9 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 30-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume94/number9/16373-5831/ },
doi = { 10.5120/16373-5831 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:17:13.809187+05:30
%A Esha Barlaskar
%A Y. Jayanta Singh
%T Dynamic Consolidation of Virtual Machines with Multi-Agent System
%J International Journal of Computer Applications
%@ 0975-8887
%V 94
%N 9
%P 30-38
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing systems supply massive infrastructures for high-performance computing that are flexible as they are able to acclimate to user and application requirements. Cloud Computing offers on demand services which are used by virtue of a service-oriented interface that execute the anything-as-a-service archetype. The enlargement of Cloud computing has resulted in the establishment of large-scale data centers around the world containing thousands of compute nodes and these data centers consume excessive amounts of electrical energy resulting in high operating costs. Therefore, to cut down the cost of energy consumption the cloud providers must optimize resource usage by performing dynamic consolidation of virtual machines (VMs) in an effective way to improve energy efficiency in cloud data center. The problem of VM consolidation can be split into four sub-problems namely physical machine overload detection; physical machine under-load detection; VM selection and VM placement. Each of the afore-stated sub-problems must operate in an optimized manner to maintain the tradeoff between energy and performance. In this research paper a new multi-agent system (MAS) for dynamic consolidation of VMs is proposed with the aim of making the cloud system smarter by incorporating the five traits of multi-agent systems which are ubiquity, interconnection, intelligence, delegation and human orientation. The Cloud Computing systems require intelligent and perceptive based software with progressive, elastic, self-ruling style which can be provided by MASs. The proposed method has significantly reduced energy consumption and at the same time ensures a high level of constancy to the Service Level Agreements (SLA).

References
  1. Domenico Talia, "Clouds Meet Agents: Toward Intelligent Cloud Services", IEEE Internet Computing . Vol. 16, Issue 2, pp- 78-81. 0p , March 2012.
  2. K. P. Sycara, "Multiagent systems," AI Magazine, vol. 19, no. 2, pp. 79-92, 1998.
  3. NIST Cloud Computing Program. www. nist. gov/ itl/cloud/. [Online]. Accessed on June 2013.
  4. M. Armbrust, et al. , "A view of cloud computing," Communications of the ACM, vol. 53, no. 4, pp. 50-58, April 2010.
  5. Wuxue Jiang, Jing Zhang, Junhuai Li, Hui Hu, "A Resource Scheduling Strategy in Cloud Computing based on Multi-agent Genetic Algorithm", TELKOMNIKA, Vol. 11, No. 11, pp. 6563~6569, November 2013.
  6. Myougnjin Kim, Hanku Lee, Hyogun Yoon, Jee-In Kim and HyungSeok Kim, "IMAV: An Intelligent Multi-Agent Model Based on Cloud Computing for Resource Virtualization", In : 2011 International Conference on Information and Electronics Engineering, IPCSIT, vol. 6,pp- 199-203, IACSIT Press, Singapore 2011.
  7. T. Han, K. M. Sim, "An Ontology-enhanced Cloud Service Discovery System", Lecture Notes in Engineering and Computer Science 2180(1) 2010: 644-649, 2010.
  8. Yue-Shan Chang, Tong-Ying Juan, Che-Hsiang Chang and Jing-Shyang Yen, "Integrating Intelligent Agent and Ontology for Services Discovery on Cloud Environment", IEEE International Conference on Systems, Man, and Cybernetics, pp: 3215 – 3220, 2012.
  9. Jaeyong Kang and Kwang Mong Sim, "Towards Agents and Ontology for Cloud Service Discovery", 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, pp: 483 – 490, Beijing, 2011.
  10. Sheng-Yuan Yang and Dong-Liang Lee, "Developing a Cloud Intelligent and Energy-saving Information Interface Agent with Web Services", 2012 26th International Conference on Advanced Information Networking and Applications Workshops, pp: 1310 – 1315, Fukuoka , 2012.
  11. K. M. Sim, "Agent-based Cloud Computing", IEEE Transactions On Services Computing, Vol. 5, No. 4, pp. 564,577, Fourth Quarter 2012.
  12. L. Tasquier, S. Venticinque, R. Aversa, and B. Di, "Agent Based Application Tools for Cloud Provisioning and Management",3rd International Conference on Cloud Computing (CLOUDCOMP 2012), Wien, Austria, September 24–26, 2012.
  13. Taha Chaabouni, Hamdi Kchaou and Maher Khemakhem, "Agent technology based resources management in Cloud Computing", 2013 World Congress on Computer and Information Technology (WCCIT), pp:1-3, Sousse, 2013.
  14. Qi Liu, Georgios K. Theodoropoulos, Dilma Da Silva and Elvis S. Liu, "Towards An Agent-Based Symbiotic Architecture For Autonomic Management Of Virtualized Data Centers", Proceedings of the 2012 Winter Simulation Conference, Article no. 147, 2012.
  15. Aravindh Ramaswamy, Aswath Balasubramanian, Palaniappan Vijaykumar and Varalakshmi P, "A Mobile Agent based Approach of ensuring Trustworthiness in the Cloud", IEEE-International Conference on Recent Trends in Information Technology, MIT, Anna University, Chennai. June 3-5, 2011.
  16. K. Mukherjee and G. Sahoo, "Green Cloud: An Algorithmic Approach", International Journal of Computer Applications (0975 – 8887), Volume 9– No. 9, November 2010.
  17. Jinhua Hu, Jianhua Gu, Guofei Sun, Tianhai Zhao, "A Strategy on LoadBalancing of VirtualMachine Resources in Cloud Computing Environment", IEEE Third International Symposium on Parallel Architectures, Algorithms and Programming (PAAP), pp. 89 – 96, 2010.
  18. N Bobroff, A. Kochut, and K. Beaty, "Dynamic placement of virtual machines for managing SLA violations", In Proc. International Symposium on Integrated Network Management ',2007.
  19. D. Barbagallo, E. Di Nitto, D. J. Dubois, and R. Mirandola, "A bio-inspired algorithm for energy optimization in a self-organizing data center," In Proc. SOAR'09. Berlin, Heidelberg: Springer-Verlag, pp. 127–151, 2010.
  20. Anton Beloglazovy, Rajkumar Buyya,Young Choon Lee,Albert omaya, "A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems", Technical Report, CLOUDS-TR-2010-3, Cloud Computing and Distributed Systems Laboratory, The University of Melbourne, 2010.
  21. Nathuji R, Schwan K, "Virtual power: coordinated power management in virtualized enterprise systems", In: ACM, pp 265–278. 2007.
  22. Ajith Singh. N and M. Hemalatha, "Virtual Machine Placement by Using Honey Bee ForagerAlgorithm in Cloud Computing", Karpagam Journal of Computer Science, Vol7 Issue 4,Page No: 209-215, ISSN 0973-2926, May-June 2013.
  23. Bernardetta Addis, Danilo Ardagna, Barbara Panicucci, Mark Squillante, Li Zhang: "A Hierarchical Approach for the Resource Management of Very Large Cloud Platforms", IEEE Transactions On Dependable And Secure Computing, 2013.
  24. Mohsen Sharifi, Hadi Salimi, Mahsa Najafzadeh, "Power-ef?cient distributed scheduling of virtual machines using workload-aware consolidation techniques", The Journal of Supercomputing, Vol 61(1), pp. 46-66, 2011.
  25. Anton Beloglazovy, R. Buyya, "Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers". Concurr. Comput. Pract. Experience 24(13), 1–24 (2011). .
  26. R. Buyya, Rajiv Ranjan, Rodrigo N. Calheiros, Anton Beloglazov, C´esar A. F. De Rose, "CloudSim: a toolkit for modeling and simulation of cloudcomputing environments and evaluation of resource provisioning algorithms" , Advanced Information Networking and Applications (AINA), 2010 24th IEEE International Conference on, On page(s): 446 –452, April 2010.
  27. Ajith Singh. N and M. Hemalatha, "Cluster Based Bee Algorithm for Virtual Machine Placement in Cloud Data Centre", Journal of Theoretical and Applied Information Technology, Vol. 57, No. 3, pp. 01-10, November 2013.
  28. Anton Beloglazovy, J. Abawajy, R. Buyya. "Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing". Future Generation Computer Systems 2011; doi:10. 1016/j. future. 2011. 04. 017
  29. JACK INTELLIGENT AGENT. http://en. wikipedia. org/ wiki/JACK_Intelligent_Agents. [Online]2014.
  30. JADE. http://jade. tilab. com/. [Online]. Accessed on February 2014.
Index Terms

Computer Science
Information Sciences

Keywords

Dynamic consolidation energy efficiency multi-agent system virtual machine placement

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