Energy Efficient Resource Allocation and Scheduling in Cloud Computing Platform

Authors: Shuen-Tai Wang, Ying-Chuan Chen, Yu-Ching Lin

Abstract:

There has been renewal of interest in the relation between Green IT and cloud computing in recent years. Cloud computing has to be a highly elastic environment which provides stable services to users. The growing use of cloud computing facilities has caused marked energy consumption, putting negative pressure on electricity cost of computing center or data center. Each year more and more network devices, storages and computers are purchased and put to use, but it is not just the number of computers that is driving energy consumption upward. We could foresee that the power consumption of cloud computing facilities will double, triple, or even more in the next decade. This paper aims at resource allocation and scheduling technologies that are short of or have not well developed yet to reduce energy utilization in cloud computing platform. In particular, our approach relies on recalling services dynamically onto appropriate amount of the machines according to user’s requirement and temporarily shutting down the machines after finish in order to conserve energy. We present initial work on integration of resource and power management system that focuses on reducing power consumption such that they suffice for meeting the minimizing quality of service required by the cloud computing platform.

Keywords: Cloud computing, energy utilization, power consumption, resource allocation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1127176

References:

[1] Foster, Ian, et al. "Cloud computing and grid computing 360-degree compared." 2008 Grid Computing Environments Workshop. IEEE, 2008.
[2] Armbrust, Michael, et al. "Above the clouds: A Berkeley view of cloud computing." (2009).
[3] Zhang, Qi, Lu Cheng, and Raouf Boutaba. "Cloud computing: state-of-the-art and research challenges." Journal of internet services and applications 1.1 (2010): 7-18.
[4] Goth, Greg. "Virtualization: Old technology offers huge new potential." IEEE Distributed Systems Online 8.2 (2007): 3.
[5] Meyer, Richard A., and Love H. Seawright. "A virtual machine time-sharing system." IBM Systems Journal 9.3 (1970): 199-218.
[6] Goldberg, Robert P. "Architecture of virtual machines." Proceedings of the workshop on virtual computer systems. ACM, 1973.
[7] W. Forrest, "How to cut data centre carbon emissions?" Available: http://www.computerweekly.com/Articles/2008/12/05/233748/how-to-cut-data-centre-carbon-emissions.htm, Sep. 2016.
[8] Stemm, Mark. "Measuring and reducing energy consumption of network interfaces in hand-held devices." IEICE transactions on Communications 80.8 (1997): 1125-1131.
[9] Younge, Andrew J., et al. "Efficient resource management for cloud computing environments." Green Computing Conference, 2010 International. IEEE, 2010.
[10] Tripathi, Tanvi, and Sunita Gond. "An Efficient Approach of Power Consumption in Cloud using Scheduling of Resources." International Journal of Modern Education and Computer Science 7.7 (2015): 60.
[11] DuBois, Paul. MySQL: the definitive guide to using, programming, and administering MySQL 4. Sams, 2003.
[12] Johnson, Bruce, and Joel Webber. Google web toolkit. Addison-Wesley, 2007.
[13] Hickson, Ian, and David Hyatt. "Html5." W3C Working Draft WD-html5-20110525, May (2011).
[14] Buyya, Rajkumar, Anton Beloglazov, and Jemal Abawajy. "Energy-efficient management of data center resources for cloud computing: A vision, architectural elements, and open challenges." arXiv preprint arXiv:1006.0308 (2010).
[15] Liu, Liang, et al. "GreenCloud: a new architecture for green data center." Proceedings of the 6th international conference industry session on Autonomic computing and communications industry session. ACM, 2009.
[16] VMware virtualization, Available at: http://www.vmware.com/, Sep. 2016.
[17] Xen hypervisor, Available at: http://www.xen.org/, Sep. 2016.
[18] Chen, Wei, et al. "A novel hardware assisted full virtualization technique." Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for. IEEE, 2008.
[19] Kivity, Avi, et al. "KVM: The Linux virtual machine monitor." Proceedings of the Linux symposium. Vol. 1. 2007.
[20] IPMI, Intelligent Platform Management Interface, Available at: http://www.intel.com/design/servers/ipmi/, Sep. 2016.
[21] NCHC Formosa 3 Cloud Cluster, Available at: http://formosa3.nchc.org.tw/, Sep. 2016.
[22] NCHC, National Center for High-performance Computing, Available at: http://www.nchc.org.tw, Sep. 2016.