Data center architectures; Power comparison; Energy Efficiency
Abstract :
[en] Power consumption is a primary concern for cloud computing data centers. Being the network one of the non- negligible contributors to energy consumption in data centers, several architectures have been designed with the goal of improv- ing network performance and energy-efficiency. In this paper, we provide a comparison study of data center architectures, covering both classical two- and three-tier design and state-of-art ones as Jupiter, recently disclosed by Google. Specifically, we analyze the combined effect on the overall system performance of different power consumption profiles for the IT equipment and of different resource allocation policies. Our experiments, performed in small and large scale scenarios, unveil the ability of network-aware allocation policies in loading the the data center in a energy-proportional manner and the robustness of classical two- and three-tier design under network-oblivious allocation strategies.
Disciplines :
Computer science
Author, co-author :
Ruiu, Pietro; Istituto Superiore Mario Boella (ISMB) ; Politecnico di Torino
Bianco, Andrea; Politecnico di Torino
Fiandrino, Claudio ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Giaccone, Paolo; Politecnico di Torino
Kliazovich, Dzmitry ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
yes
Language :
English
Title :
Power Comparison of Cloud Data Center Architectures
Publication date :
May 2016
Event name :
IEEE International Conference on Communications (ICC)
Event date :
May 2016
Main work title :
IEEE International Conference on Communications (ICC), Kuala Lumpur, Malaysia, 2016
Q. Zhang, L. Cheng, and R. Boutaba, "Cloud computing: state-of-the-art and research challenges, " Journal of Internet Services and Applications, vol. 1, no. 1, pp. 7-18, 2010.
"Cisco Global Cloud Index: Forecast and Methodology, 2013-2018, " 2014, White Paper.
D. Kliazovich, J. Pecero, A. Tchernykh, P. Bouvry, S. Khan, and A. Zomaya, "CA-DAG: Modeling communication-aware applications for scheduling in cloud computing, " Journal of Grid Computing, pp. 1-17, 2015.
P. Corcoran and A. Andrae, "Emerging trends in electricity consumption for consumer ICT, " 2013, White Paper. [Online]. Available: http://hdl. handle. net/10379/3563
U. S. Department of Energy, "Improving data center efficiency with rack or row cooling devices, " 2012, White Paper.
L. Barroso and U. Holzle, "The case for energy-proportional computing, " IEEE Computer, vol. 40, no. 12, pp. 33-37, 2007.
Q. Zhang and R. Boutaba, "Dynamic workload management in heterogeneous cloud computing environments, " in IEEE Network Operations and Management Symposium (NOMS), May 2014, pp. 1-7.
C. Fiandrino, D. Kliazovich, P. Bouvry, and A. Zomaya, "Performance and energy efficiency metrics for communication systems of cloud computing data centers, " IEEE Transactions on Cloud Computing, 2015.
Y. Shang, D. Li, and M. Xu, "A comparison study of energy proportionality of data center network architectures, " in IEEE ICDCSW, 2012.
A. Hammadi and L. Mhamdi, "A survey on architectures and energy efficiency in data center networks, " Computer Communications, vol. 40, pp. 1-21, 2014.
M. Al-Fares, A. Loukissas, and A. Vahdat, "A scalable, commodity data center network architecture, " in ACM SIGCOMM, 2008.
N. Mysore et al., "PortLand: A scalable fault-tolerant layer 2 data center network fabric, " in ACM SIGCOMM Computer Communication Review, vol. 39, no. 4, 2009, pp. 39-50.
A. Greenberg et al., "VL2: A scalable and flexible data center network, " in ACM SIGCOMM Computer Communication Review, vol. 39, no. 4, 2009, pp. 51-62.
A. Singh et al., "Jupiter rising: A decade of Clos topologies and centralized control in Google datacenter network, " in ACM SIGCOMM, 2015.
C. Guo et al., "BCube: A high performance, server-centric network architecture for modular data centers, " ACM SIGCOMM Computer Communication Review, vol. 39, no. 4, pp. 63-74, 2009.
C. Guo et al., "DCell: A scalable and fault-tolerant network structure for data centers, " in ACM SIGCOMM Computer Communication Review, vol. 38, no. 4, 2008, pp. 75-86.
M. Guzek, P. Bouvry, and E.-G. Talbi, "A survey of evolutionary computation for resource management of processing in cloud computing, " IEEE Computational Intelligence Magazine, vol. 10, no. 2, pp. 53-67, May 2015.
L. Popa, S. Ratnasamy, G. Iannaccone, A. Krishnamurthy, and I. Stoica, "A cost comparison of datacenter network architectures, " in CoNEXT. ACM, 2010.
W. Fang, X. Liang, S. Li, L. Chiaraviglio, and N. Xiong, "VMPlanner: Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers, " Computer Networks, vol. 57, no. 1, pp. 179-196, 2013.
M. Guzek, D. Kliazovich, and P. Bouvry, "HEROS: Energy-efficient load balancing for heterogeneous data centers, " in IEEE CLOUD, 2015.
D. Belabed, S. Secci, G. Pujolle, and D. Medhi, "Striking a balance between traffic engineering and energy efficiency in virtual machine placement, " IEEE Transactions on Network and Service Management, vol. 12, no. 2, pp. 202-216, June 2015.
L. Wang, F. Zhang, J. Arjona Aroca, A. Vasilakos, K. Zheng, C. Hou, D. Li, and Z. Liu, "GreenDCN: A general framework for achieving energy efficiency in data center networks, " IEEE Journal on Selected Areas in Communications, vol. 32, no. 1, pp. 4-15, January 2014.