Effect of the Architecture and Topology of Cloud Computing on Power Saving

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The use of cloud computing is increasing worldwide because users are now offered with IT utility services that consist of a pool of servers and switches that are fully interconnected. As such, cloud computing consumes huge amounts of power energy, leading to high operational costs and leaving carbon footprints in the environment. Thus, we are promoting the use of Green Cloud computing solutions. In this paper, we investigate how power management affects power saving in cloud computing by analyzing the architecture, topology, average load/server, and scheduling algorithms. We validated our result by using the GreenCloud simulator. Results reveal that changes in architecture, topology, average load/server, and scheduling algorithms have an impact on cloud computing, thus allowing for significant cost savings and indicating the high potential of improving energy efficiency under dynamic workload scenarios.

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661-670

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August 2015

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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[1] B. P. Rimal, E. Choi, and I. Lumb, A taxonomy and survey of cloud computing systems, " in INC, IMS and IDC, 2009. NCM, 09. Fifth International Joint Conference on, 2009, pp.44-51.

DOI: 10.1109/ncm.2009.218

Google Scholar

[2] T. Horvath, T. Abdelzaher, K. Skadron, and X. Liu, Dynamic voltage scaling in multitier web servers with end-to-end delay control, Computers, IEEE Transactions on, vol. 56, pp.444-458, (2007).

DOI: 10.1109/tc.2007.1003

Google Scholar

[3] (DEC 2013). greencloud simulator user manual.

Google Scholar

[4] M. Guzek, D. Kliazovich, and P. Bouvry, A holistic model for resource representation in virtualized cloud computing data centers, in Cloud Computing Technology and Science (CloudCom), 2013 IEEE 5th International Conference on, 2013, pp.590-598.

DOI: 10.1109/cloudcom.2013.84

Google Scholar

[5] A. Beckmann, U. Meyer, P. Sanders, and J. Singler, Energy-efficient sorting using solid state disks, Sustainable Computing: Informatics and Systems, vol. 1, pp.151-163, (2011).

DOI: 10.1016/j.suscom.2011.02.004

Google Scholar

[6] A. Beloglazov, J. Abawajy, and R. Buyya, Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing, Future Generation Computer Systems, vol. 28, pp.755-768, (2012).

DOI: 10.1016/j.future.2011.04.017

Google Scholar

[7] D. Kliazovich, P. Bouvry, and S. U. Khan, GreenCloud: a packet-level simulator of energy-aware cloud computing data centers, The Journal of Supercomputing, vol. 62, pp.1263-1283, (2012).

DOI: 10.1007/s11227-010-0504-1

Google Scholar

[8] P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan, Energy aware network operations, in INFOCOM Workshops 2009, IEEE, 2009, pp.1-6.

DOI: 10.1109/infcomw.2009.5072138

Google Scholar

[9] D. Kliazovich, P. Bouvry, and S. U. Khan, DENS: data center energy-efficient network-aware scheduling, Cluster computing, vol. 16, pp.65-75, (2013).

DOI: 10.1007/s10586-011-0177-4

Google Scholar

[10] G. Chen, W. He, J. Liu, S. Nath, L. Rigas, L. Xiao, et al., Energy-Aware Server Provisioning and Load Dispatching for Connection-Intensive Internet Services, in NSDI, 2008, pp.337-350.

Google Scholar

[11] X. Fan, W. -D. Weber, and L. A. Barroso, Power provisioning for a warehouse-sized computer, in ACM SIGARCH Computer Architecture News, 2007, pp.13-23.

DOI: 10.1145/1273440.1250665

Google Scholar