Scheduling Reservations of Virtual Machines in Cloud Data Center for Energy Optimization

Sebagenzi Jason¹ , Suchithra. R.²

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.6 , pp.16-26, Dec-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i6.1626

Online published on Dec 31, 2018

Copyright © Sebagenzi Jason, Suchithra. R. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

View this paper at   Google Scholar | DPI Digital Library

XML View     PDF Download

How to Cite this Paper

448 Views    266 Downloads    157 Downloads

Abstract :
The present paper examine the scheduling reservations of energy-efficient of virtual machine (VM) in a Cloud Data center. Focusing on CPU-intensive applications, the target of this paper is to schedule all reservations non-preemptively, subjecting to constraints to capacities of physical machine (PM) and running time interval spans, in order to minimize the consumption of the total energy of all physical machines. This problem is an NP-complete. The best solution for this problem is a 5-approximation algorithm by using First-Fit-Decreasing algorithm and 3-approximation algorithm for in case of offline parallel machine scheduling with unit demand. Combining the characteristics of workload and optimality in interval spans, a method to find the optimal solution with the minimum number of job migrations is proposed, and a 2-approximation algorithm called Longest Loaded Interval First algorithm (LLIF) for general cases. At the end, how the algorithms are applied to minimize the total energy consumption in a Cloud Data center will be shown.

Key-Words / Index Term :
Virtual machine reservation, Energy efficiency, Cloud Data centers, Resource scheduling

References :
[1] Baker, Thar, Asim, Muhammad, Tawfik, Hissam (2017). An energy-aware service composition algorithm for multiple cloud-based to applications. J.Netw. Comp. App. 89 (1), 96-108.
[2] Beloglizov, A., Abawajy, J., Buyya, R., 2012. Energy-aware resource allocation Heuristics for efficient management of data centers for cloud computing. Future Generat.Comput. System. 28 (5), 755 - 768.
[3] Beloglizov, A., Buyya, R., Lee, Y.C, Zomaya, A.Y., 2011. In:Zelkonwitz, M. (ed), A Taxonomy and survey of Energy-efficiency Data Centers and Cloud Computing Systems, Advances in computers, vol.82. Elsevier, Amsterdam, The Netherlands, PP 47 - 111.
[4] Bohrer, P., Elnozahy, E., Keller, T., Kistler, M., Lefurgy, C., McDowell, C., & Rajamony, R. (2014). The case for power management in Web servers. Norwell, MA, USA: Kluwer Academic Publishers.
[5] Bollen, J., & Heylighen, F. (2015). Algorithms for the Self-organization of Distributed, Multiuser Networks. Austrian: Cybernetics and Systems.
[6] Bonabeau, E., Dorigo, M., & Theraulaz, G. (2015). swarm Intelligence. USA: Oxford University Press.
[7] Coffman Jr., E.G., Garey, M.R., Johnson, D.S., 1987. Bin-Packing with divisible item sizes. J. Complex 3 (1987), 406 - 428.
[8] Elnozahy, E., Kistler, M., & Rajamony, R. (2015). Energy- Efficient server clusters. Power-Aware Computer Systems.
[9] Flammini, M., Monaco, G., Moscardelli, L., Shachnai, H., Shalom, M., Tamir, T., Zaks, S. 2010. Minimizing total power-on time in parallel scheduling with application to optical networks. Theor. Comput. Sci. 411 (40 - 42), 3553-3562.
[10] Heylighen, F. (2015). The science of self-organization and Adaptivity. USA: Encyclopedia of life support. .
[11] Heylighen, F., & Gershenson, C. (2015). The meaning of self-organization in computing. IEE Intelligent Systems.
[12] Khargharia, B., Hariri, S., & Yousif, M. (2015). Autonomic power and performance management for computing systems. USA: Cluster Computing.
[13] Kim, K., Beloglazov, A., Buyya, R., 2011. Power- aware provisioning of virtual machines for real-time Cloud services. Concurrency Comput. Pract. Exp. 23 (13), 1491-1505.
[14] Lefurgy, C., Rajamani, K., Rawson, F., Felter, W., Kistler, M., & Keller, T. (2015). Energy Management for commercial servers. USA: Computer 36 (12).
[15]Mathew, V., Sitaraman, R.K., Shenoy, P., 2012. Energy-aware load balancing in content delivery networks. In: Proceedings of INFOCOM 2012, 25-30 March, PP. 954-962 Olrando, F1.
[16] Pinheiro, E., Bianchini, R., Carrera, E., & Heath, T. (2015). Load Balancing and unbalancing for power and performance in cluster-based systems. In proceedings of the Workshop on Compilers and Operating Systems for Low Power.
[17]White, R., & Abels, T. (2014). Energy Resorce management in the virtual data center. Washington, DC, USA: Proceedings of the International Symposium on Electronics and the Environment.
[18] Jun, C., Yunchuan , Q., Yu Ye, & Zhuo, T. (2015). A Live Migration Algorithm for Virtual Machine in a Cloud Computing Environment. Chine: UIC-ATC-ScalCom-CBDCom-IoP.
[19] Megha, Desai R.; Hiren, Patel B.;. (2015). Efficient Virtual Machine Migration in Cloud Computing. Fifth International Conference on Communication Systems and Networking Technologies.
[20] Mofijul, I. M. (2015). A Genetic Algorithm for Virtual Machine Migration in Heterogeneous Mobile Cloud Computing. Bangladesh.
[21] Pankajdeep , K., & Rani, A. (2015). Virtual Machine Migration in Cloud Computing. Internationale Journal of Grid Distribution Computing Vol.8.
[22] Rabiatul , A., Ruhani, R. A., Norliza, Z., & Mustaffa, S. (2015). Virtual Machine Migration Implementation in Load Balancing for cloud computing. Mara (UiTM).

Authors Profile
Mr. Sebagenzi Jason pursed Bachelor of Science from Adventist university of Central Africa (Rwanda), and Master of Science in Information Technology from Jain University (India) in year 2011. He is currently pursuing Ph.D. in the University of Jain in India since 2016. His main research work focuses on Cloud Management He has 9 years of teaching experience.

Dr.Suchithra R pursed Bachelor of Commerce, Master of Computer Application and Ph.D in Computer Science from Manonmaniam Sundaranar University , India in year 2009. She worked as Associate Professor and Head of MS (IT) Department in Jain university since 2010. She has published more than 20 research papers in reputed international journal.