László Gyarmati
Abstract
Data centers have a crucial role in current Internet architecture supporting content-centric networking. State-of-the-art data centers have different architectures like fat-tree, DCell, or BCube. However, their architectures share a common property: symmetry. Due to their symmetric nature, a tricky point with these architectures is that they are hard to be extended in small quantities. Contrary to state-of-the-art data center architectures, we propose an asymmetric data center topology generation method called Scafida inspired by scale-free networks; these data centers have not only small diameters and high fault tolerance, inherited by scale-free networks, but can also be scaled in smaller and less homogenous increments. We extend the original scale-free network generation algorithm of Barabasi and Albert to meet the physical constraints of switches and routers. Despite the fact that our method artificially limits the node degrees in the network, our data center architectures keep the preferable properties of scale-free networks. Based on extensive simulations we present preliminary results that are promising regarding the error tolerance, scalability, and flexibility of the architecture.
- W. Aiello, F. Chung, and L. Lu. A random graph model for massive graphs. In STOC '00: Proceedings of the thirty-second annual ACM symposium on Theory of computing, pages 171--180, New York, NY, USA, 2000. ACM. Google Scholar
Digital Library
- M. Al-Fares, A. Loukissas, and A. Vahdat. A scalable, commodity data center network architecture. In SIGCOMM '08, pages 63--74, 2008. Google ScholarDigital Library
- R. Albert, H. Jeong, and A.-L. Barabási. Internet: Diameter of the World-Wide Web. Nature, 401(6749):130--131, September 1999.Google ScholarCross Ref
- R. Albert, H. Jeong, and A.-L. Barabási. Error and attack tolerance of complex networks. Nature, 406(6794):378--82, August 2000.Google ScholarCross Ref
- A.-L. Barabási and R. Albert. Emergence of Scaling in Random Networks. Science, 286(5439):509--512, 1999.Google Scholar
- R. Cohen and S. Havlin. Scale-free networks are ultrasmall. Phys. Rev. Lett., 90(5):058701, Feb 2003.Google ScholarCross Ref
- P. Costa, T. Zahn, A. Rowstron, G. O'Shea, and S. Schubert. Why should we integrate services, servers, and networking in a data center? In WREN '09: Proceedings of the 1st ACM workshop on Research on enterprise networking, pages 111--118, New York, NY, USA, 2009. ACM. Google ScholarDigital Library
- J. Dean and S. Ghemawat. MapReduce: Simplified data processing on large clusters. In OSDI'04: Sixth Symposium on Operating System Design and Implementation, San Francisco, 2004. Google ScholarDigital Library
- A. Greenberg, J. Hamilton, D. A. Maltz, and P. Patel. The cost of a cloud: research problems in data center networks. SIGCOMM Comput. Commun. Rev., 39(1):68--73, 2009. Google ScholarDigital Library
- A. Greenberg, J. R. Hamilton, N. Jain, S. Kandula, C. Kim, P. Lahiri, D. A. Maltz, P. Patel, and S. Sengupta. Vl2: a scalable and flexible data center network. In SIGCOMM '09, pages 51--62, 2009. 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 SIGCOMM '09, pages 63--74, 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 SIGCOMM '08, pages 75--86, 2008. Google ScholarDigital Library
- L. Gyarmati and T. A. Trinh. How can architecture help to reduce energy consumption in data center networking? In e-Energy '10, pages 183--186, New York, NY, USA, 2010. ACM. Google ScholarDigital Library
- M. E. J. Newman, S. H. Strogatz, and D. J. Watts. Random graphs with arbitrary degree distributions and their applications. Phys. Rev. E, 64(2):026118, Jul 2001.Google ScholarCross Ref
- D. S. Nikolopoulos. Green building blocks - software stacks for energy-efficient clusters and data centers. ERCIM News 79, 2009. R. Niranjan Mysore, {16} A. Pamboris, N. Farrington, N. Huang, P. Miri, S. Radhakrishnan, V. Subramanya, and A. Vahdat. Portland: a scalable fault-tolerant layer 2 data center network fabric. In SIGCOMM '09, pages 39--50, 2009. Google ScholarDigital Library
- R. Pastor-Satorras and A. Vespignani. Epidemic spreading in scale-free networks. Phys. Rev. Lett., 86(14):3200--3203, Apr 2001. H. Wu, G. Lu, D. Li, {18} C. Guo, and Y. Zhang. Mdcube: a high performance network structure for modular data center interconnection. In CoNEXT '09, pages 25--36, New York, NY, USA, 2009. ACM. Google ScholarDigital Library
Index Terms
- Scafida: a scale-free network inspired data center architecture
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