Yunfei Shang
ABSTRACT
The goal of data center network is to interconnect the massive number of data center servers, and provide efficient and fault-tolerant routing service to upper-layer applications. To overcome the problem of tree architecture in current practice, many new network architectures are proposed, represented by Fat-Tree, BCube, and etc. A consistent theme in these new architectures is that a large number of network devices are used to achieve 1:1 oversubscription ratio. However, at most time, data center traffic is far below the peak value. The idle network devices will waste significant amount of energy, which is now a headache for many data center owners.
In this paper, we discuss how to save energy consumption in high-density data center networks in a routing perspective. We call this kind of routing energy-aware routing. The key idea is to use as few network devices to provide the routing service as possible, with no/little sacrifice on the network performance. Meanwhile, the idle network devices can be shutdown or put into sleep mode for energy saving. We establish the model of energy-aware routing in data center network, and design a heuristic algorithm to achieve the idea. Our simulation in typical data center networks shows that energy-aware routing can effectively save power consumed by network devices.
- S. Ghemawat, H. Gobioff, and S. Leung. The Google File System. In SOSP, 2003. Google Scholar
Digital Library
- CloudStore. Higher Performance Scalable Storage. http://kosmosfs.sourceforge.net/.Google Scholar
- J. Dean and S. Ghemawat. MapReduce: Simplified Data Processing on Large Clusters. In OSDI, 2004. Google ScholarDigital Library
- M. Al-Fares, A. Loukissas, and A. Vahdat. A Scalable, Commodity Data Center Network Architecture. In SIGCOMM, 2008. Google ScholarDigital Library
- C. Guo, G. Lu, D. Li, H. Wu, X. Zhang, Y. Shi, C. Tian, Y. Zhang, and S. Lu. BCube: A High Performance, Server-centric Network Architecture for Modular Data Centers. In ACM SIGCOMM, August 2009. Google ScholarDigital Library
- C. Guo, H. Wu, K. Tan, L. Shi, Y. Zhang, and S. Lu. DCell: A Scalable and Fault-Tolerant Network Structure for Data Centers. In ACM SIGCOMM, pages 75--86, 2008. Google ScholarDigital Library
- B. Heller, S. Seetharaman, P. Mahadevan. ElasticTree: Saving Energy in Data Center Networks. In NSDI'10, Apr 2010. Google ScholarDigital Library
- U.S. Environmental Protection Agency. Data Center Report to Congress. http://www.energystar.gov.Google Scholar
- R.M.Karp. Reducibility Among Combinatorial Problems, in R.E.Miller and J.W. Thatcher (Eds.), Complexity of Computer Computations. Plenum Press, New York, 1972.Google Scholar
- A.Levitin. Introduction to the design & analysis of algorithms. Addison-Wesley, 2003. Google ScholarDigital Library
- D.Nace, N.L.Doan, E.Gourdin, B.Liau. Computing Optimal Max-Min Fair Resource Allocation for Elastic Flows. IEEE/ACM Transactions on Networking 16(6): 1272--1281, 2006. Google ScholarDigital Library
- D.Bertsekas, R.Gallager. Data networks. Englewood Cliffs, NJ: Prentice-Hall, 1992. Google ScholarDigital Library
- R. N. Mysore, et al. PortLand: A Scalable Fault-Tolerant Layer 2 Data Center Network Fabric. In ACM SIGCOMM, August 2009. Google ScholarDigital Library
- A. Greenberg, N. Jain, S. Kandula, C. Kim, P. Lahiri, D. Maltz, P. Patel, and S. Sengupta. VL2: A Scalable and Flexible Data Center Network. In ACM SIGCOMM, August 2009. Google ScholarDigital Library
- D. Li, C. X. Guo, H. T. Wu, K Tan, Y. G. Zhang, S. W. Lu. FiConn: Using Backup Port for Server Interconnection in Data Centers. In INFOCOM 2009.Google Scholar
- M. Gupta, S. Singh. Greening of the Internet. In ACM SIGCOMM, Karlsruhe, Germany. August 2003. Google ScholarDigital Library
- M. Gupta and S. Singh. Using Low-Power Modes for Energy Conservation in Ethernet LANs. INFOCOM'07, May 2007.Google Scholar
- S. Nedevschi et al. Reducing network energy consumption via sleeping and rate-adaptation. In Proceedings of the 5th USENIX NSDI, pages 323--336, 2008. Google ScholarDigital Library
- K. Christensen, B.Nordman, R.Brown. Power Management in Networked Devices. In IEEE COMPUTER SOCIETY, August 2004. Google ScholarDigital Library
- J. Chabarek, J. Sommers, P. Barford, et al. Power Awareness in Network Design and Routing. INFOCOM'08, Apr 2008.Google Scholar
- G. Magklis, M. Scott, G. Semeraro, and etc. Profile-based Dynamic Voltage and Frequency Scaling for a Multiple Clock Domain Microprocessor. In ISCA'03, Jun 2003. Google ScholarDigital Library
- D. Meisner, B. Gold, T. Wenisch. PowerNap: Eliminating Server Idle Power. In ASPLOS'09, May 2009. Google ScholarDigital Library
- G. Ananthanarayanan and R. H. Katz. Greening the Switch. HotPower'08, Dec 2008. Google ScholarDigital Library
- C. Patel, C. Bash, R. Sharma, M. Beitelmam, and R. Friedrich. Smart Cooling of data Centers. In Proceedings of InterPack, July 2003.Google ScholarCross Ref
- S. Nedevschi, J. Chandrashekar, and B. Nordman. Skilled in the Art of Being Idle: Reducing Energy Waste in Networked Systems. NSDI'09, Apr 2009. Google ScholarDigital Library
- S. Srikantaiah, A. Kansal and F. Zhao. Energy Aware Consolidation for Cloud Computing. HotPower'08, Dec 2008. Google ScholarDigital Library
- L. A. Barroso, U. Hlzle. The case for energy-proportional computing. Computer, 40(12):33--37,2007. Google ScholarDigital Library
Index Terms
- Energy-aware routing in data center network
Recommendations
A Comparison Study of Energy Proportionality of Data Center Network Architectures
ICDCSW '12: Proceedings of the 2012 32nd International Conference on Distributed Computing Systems WorkshopsToday's data center networks consume a great amount of energy, which significantly aggravates the operational cost of data centers and the carbon footprint. It is an ideal objective for operators to make the power consumption of data center networks ...
On energy consumption of switch-centric data center networks
Data center network (DCN) is the core of cloud computing and accounts for 40% energy spend when compared to cooling system, power distribution and conversion of the whole data center (DC) facility. It is essential to reduce the energy consumption of DCN ...
Greening data center networks with throughput-guaranteed power-aware routing
Cloud based applications and services require high performance and strong reliability provided by data center networks. To overcome the problem of traditional tree based data center network, recently many new network architectures are proposed, such as ...
Comments