G-SLAM: OPTIMIZING ENERGY EFFICIENCY IN CLOUDS
Main Article Content
Abstract
Cloud services are very highly demanding as it provides high performance in pay-as-you-go manner. For providing various services data center need servers, storage devices, cooling system and power delivery system. Services of cloud computing must satisfy SLAs. SLAs are related with performance, resource utilization, quality of service, etc. As the demand of cloud services are growing day-by-day, it is also increasing energy consumption. High energy consumption results in increased operational cost, reduced profit and increased carbon emission. Carbon footprints are unfriendly to the environment. There is a need to reduce energy consumption of data centers. To reach the goal of eco-efficient green issues, Green SLA came into existence. It includes green computing issues like energy consumption, carbon footprint, etc. The objective of this paper is to design an energy efficient framework for cloud data centers in order to minimize the energy consumption on different levels.
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.
References
NIST, 2011, The NIST Definition of Cloud Computing Recommendations of the National Institute of Standards and Technology. NIST Special Publication, 145, p.7. Available at: http://www.mendeley.com/research/the-nist-definition-about-cloud-computing/.K.Elissa, “Title of paper if known,†unpublished.
L. Wu, and R. Buyya, “Service Level Agreement (SLA) in Utility Computing Systems, †Performance and Dependability in Service Computing: Concepts, Techniques and Research Directions, V. Cardellini et. al. (eds), ISBN: 978-1-60-960794-4, IGI Global, Hershey, PA, USA, July 2011, pp.1-25.
G. S. Akula and A. Potluri, “Heuristics for migration with consolidation of ensembles of virtual machines,†Proc. Communication Systems and Networks (COMSNETS), 2014 6th Int. Conf., pp. 1, 4, 6–10.
S. K. Garg and R. Buyya, “Green Cloud Computing and Environmental Sustainability†.
A. Beloglazov, J. Abawajy, and R. Buyya, “Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing,†Futur. Gener. Comput. Syst., vol. 28, no. 5, pp. 755–768, 2012.
Z. Cao, “Energy-aware framework for virtual machine consolidation in Cloud computing,†Int. Conf. High Perform. Comput. Commun., p. 429, 2013.
A. Beloglazov and 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. Exp., vol. 24, no. 13, pp. 1397–1420, 2012.
C. Paper, “Energy-aware VM consolidation approach using combination of heuristics and migration control Energy-aware VM Consolidation Approach Using Combination of Heuristics and Migration Control,†Internatioal Conf. Digit. Inf. Manag., no. December 2015, pp. 74–79, 2014.
M. Alaul and H. Monil, “Implementation of Modified Overload Detection Technique with VM Selection Strategies Based on Heuristics and Migration Control,†Int. Conf. Comput. Inf. Sci., pp. 0–4, 2015.
M. Hasan and M. S. Goraya, “Resource Efficient Fault-Tolerant Computing Service Framework in Cloud,†Int. J. Comput. Sci. Eng., vol. 9, no. 3, pp. 51–60, 2017.
C. M. Wu, R. S. Chang, H. Y. Chan, “A green energy-efficient scheduling algorithm using the DVFS technique for cloud datacentersâ€, Future Generation Computer Systems, Volume 37, pp 141-147, 2014
N. Kord and H. Haghighi, “An energy-efficient approach for virtual machine placement in cloud based data centers,†in Proc. 5th Information and Knowledge Technology Conf., 2013, pp. 44–49.
A. Murtazaev and S. Oh, “Sercon: Server consolidation algorithm using live migration of virtual machines for green computing,†IETE Technical Review, vol. 28, no. 3, pp. 212–231, 2011.
H. Li, J. Wang, J. Peng, J. Wang and T. Liu, “Energy-aware scheduling scheme using workload-aware consolidation technique in cloud data centres,†Communications, China, vol. 10, no. 12, pp.114, 124, Dec. 2013. doi: 10.1109/CC.2013.6723884
Habibullah, Khan Mohammad, "Developing strategies to mitigate the energy consumed by network infrastructures." (2016).
M. S. Hasan, Y. Kouki, T. Ledoux, and J.-L.Pazat, “Cloud energy broker: Towards SLA-driven green energy planning for IaaS providers,†in Proc. IEEE Int. Conf. HPCC, Aug. 2014, pp. 1–8.