BCDC: A High-Performance, Server-Centric Data Center Network
- 13 Downloads
Abstract
The capability of the data center network largely decides the performance of cloud computing. However, the number of servers in the data center network becomes increasingly huge, because of the continuous growth of the application requirements. The performance improvement of cloud computing faces great challenges of how to connect a large number of servers in building a data center network with promising performance. Traditional tree-based data center networks have issues of bandwidth bottleneck, failure of single switch, etc. Recently proposed data center networks such as DCell, FiConn, and BCube, have larger bandwidth and better fault-tolerance with respect to traditional tree-based data center networks. Nonetheless, for DCell and FiConn, the fault-tolerant length of path between servers increases in case of failure of switches; BCube requires higher performance in switches when its scale is enlarged. Based on the above considerations, we propose a new server-centric data center network, called BCDC, based on crossed cube with excellent performance. Then, we study the connectivity of BCDC networks. Furthermore, we propose communication algorithms and fault-tolerant routing algorithm of BCDC networks. Moreover, we analyze the performance and time complexities of the proposed algorithms in BCDC networks. Our research will provide the basis for design and implementation of a new family of data center networks.
Keywords
data center network interconnection network crossed cube server-centric fault-tolerantPreview
Unable to display preview. Download preview PDF.
Notes
Acknowledgment
We thank the anonymous reviewers and editors for their valuable suggestions that help to improve the presentation of the paper.
Supplementary material
References
- 1.Harris D. Ballmer’s millionserver claim doesn’t seem so crazy. https://gigaom.com/2013/07/17/ballmers-million-server-claim-doesnt-seem-so-crazy/#comments, July 2013.
- 2.Dignan L. AWS financials on deck: The road to 3 million servers in operation. http://www.zdnet.com/article/aws-financials-on-deck-the-road-to-3-million-servers-in-operation/, April 2015.
- 3.Al-Fares M, Loukissas A, Vahdat A. A scalable, commodity data center network architecture. In Proc. the ACM SIGCOMM Conf. Data Communication, August 2008, pp.63-74.Google Scholar
- 4.Guo C X, Wu H T, Tan K, Shi L, Zhang Y G, Lu S W. DCell: A scalable and fault-tolerant network structure for data centers. In Proc. the ACM SIGCOMM Conf. Data Communication, August 2008, pp.75-86.Google Scholar
- 5.Li D, Guo C X, Wu H T, Tan K, Zhang Y G, Lu S W. Fi-Conn: Using backup port for server interconnection in data centers. In Proc. IEEE INFOCOM, April 2009, pp.2276-2285.Google Scholar
- 6.Guo C X, Lu G H, Li D, Wu H T, Zhang X, Shi Y F, Tian C, Zhang Y G, Lu S W. BCube: A high performance, server-centric network architecture for modular data centers. In Proc. the ACM SIGCOMM Conf. Data Communication, August 2009, pp.63-74.Google Scholar
- 7.Greenberg A, Hamilton J R, Jain N, Kandula S, Kim C, Lahiri P, Maltz D A, Patel P, Sengupta S. VL2: A scalable and flexible data center network. In Proc. the ACM SIGCOMM Conf. Data Communication, August 2009, pp.51-62.Google Scholar
- 8.Abu-Libdeh H, Costa P, Rowstron A, O’Shea G, Donnelly A. Symbiotic routing in future data centers. In Proc. ACM SIGCOMM, Aug.30-Sept.3, 2010, pp.51-62.Google Scholar
- 9.Yu Y, Qian C. Space shuffle: A scalable, flexible, and high-performance data center network. IEEE Trans. Parallel and Distributed Systems, 2016, 27(11): 3351-3365.CrossRefGoogle Scholar
- 10.Zheng K, Wang L, Yang B H, Sun Y, Uhlig S. LazyCtrl: A scalable hybrid network control plane design for cloud data centers. IEEE Trans. Parallel and Distributed Systems, 2017, 28(1): 115-127.CrossRefGoogle Scholar
- 11.Bhuyan L N, Agrawal D P. Generalized hypercube and hyperbus structures for a computer network. IEEE Trans. Computers, 1984, C-33(4): 323-333.CrossRefMATHGoogle Scholar
- 12.Leiserson C E. Fat-trees: Universal networks for hardware-efficient supercomputing. IEEE Trans. Computers, 1985, 34(10): 892-901.CrossRefGoogle Scholar
- 13.Dally W J. Performance analysis of k-ary n-cube interconnection networks. IEEE Trans. Computers, 1990, 39(6): 775-785.MathSciNetCrossRefGoogle Scholar
- 14.Xiang D, Zhang Y L, Pan Y. Practical deadlock-free fault-tolerant routing in meshes based on the planar network fault model. IEEE Trans. Computers, 2009, 58(5): 620-633.MathSciNetCrossRefMATHGoogle Scholar
- 15.Xiang D. Deadlock-free adaptive routing in meshes with fault-tolerance ability based on channel overlapping. IEEE Trans. Dependable and Secure Computing, 2011, 8(1): 74-88.CrossRefGoogle Scholar
- 16.Lin D, Liu Y, Hamdi M, Muppala J. FlatNet: Towards a flatter data center network. In Proc. IEEE Global Communications Conf., December 2012, pp.2499-2504.Google Scholar
- 17.Wang T, Su Z Y, Xia Y, Qin B, Hamdi M. NovaCube: A low latency Torus-based network architecture for data centers. In Proc. IEEE Global Communications Conf., December 2014, pp.2252-2257.Google Scholar
- 18.Wang T, Su Z Y, Xia Y, Liu Y, Muppala J, Hamdi M. SprintNet: A high performance servercentric network architecture for data centers. In Proc. IEEE Int. Conf. Communications, June 2014, pp.4005-4010.Google Scholar
- 19.Wang T, Su Z Y, Xia Y, Muppala J, Hamdi M. Designing efficient high performance server-centric data center network architecture. Computer Networks, 2015, 79: 283-296.CrossRefGoogle Scholar
- 20.Wang T, Su Z Y, Xia Y, Hamdi M. CLOT: A cost-effective low-latency overlaid Torus-based network architecture for data centers. In Proc. IEEE Int. Conf. Communications, June 2015, pp.5479-5484.Google Scholar
- 21.Li D W, Wu J, Liu Z Y, Zhang F. Towards the tradeoffs in designing data center network architectures. IEEE Trans. Parallel and Distributed Systems, 2017, 28(1): 260-273.Google Scholar
- 22.Efe K. A variation on the hypercube with lower diameter. IEEE Trans. Computers, 1991, 40(11): 1312-1316.CrossRefGoogle Scholar
- 23.Cull P, Larson S M. The Möbius cubes. IEEE Trans. Computers, 1995, 44(5): 647-659.Google Scholar
- 24.Abraham S, Padmanabhan K. The twisted cube topology for multiprocessors: A study in network asymmetry. Journal of Parallel and Distributed Computing, 1991, 13(1): 104-110.CrossRefGoogle Scholar
- 25.Fan J X, He L Q. BC interconnection networks and their properties. Chinese Journal of Computers, 2003, 26(1): 84-90. (in Chinese)MathSciNetGoogle Scholar
- 26.Wang D J. Hamiltonian embedding in crossed cubes with failed links. IEEE Trans. Parallel and Distributed Systems, 2012, 23(11): 2117-2124.CrossRefGoogle Scholar
- 27.Kulasinghe P, Bettayeb S. Embedding binary trees into crossed cubes. IEEE Trans. Computers, 1995, 44(7): 923-929.CrossRefMATHGoogle Scholar
- 28.Fan J, Lin X, Jia X. Optimal path embedding in crossed cubes. IEEE Trans. Parallel and Distributed Systems, 2005, 16(12): 1190-1200.CrossRefGoogle Scholar
- 29.Efe K. The crossed cube architecture for parallel computation. IEEE Trans. Parallel and Distributed Systems, 1992, 3(5): 513-524.CrossRefGoogle Scholar
- 30.Chang C P, Sung T Y, Hsu L H. Edge congestion and topological properties of crossed cubes. IEEE Trans. Parallel and Distributed Systems, 2000, 11(1): 64-80.CrossRefGoogle Scholar
- 31.Efe K, Blackwell P K, Slough W, Shiau T. Topological properties of the crossed cube architecture. Parallel Computing, 1994, 20(12): 1763-1775.Google Scholar
- 32.Kulasinghe P D. Connectivity of the crossed cube. Information Processing Letters, 1997, 61(4): 221-226.MathSciNetCrossRefMATHGoogle Scholar
- 33.Fan J X, Jia X H. Edge-pancyclicity and path-embeddability of bijective connection graphs. Information Sciences, 2008, 178(2): 340-351.MathSciNetCrossRefMATHGoogle Scholar
- 34.Yang X F, Dong Q, Tang Y Y. Embedding meshes/tori in faulty crossed cubes. Information Processing Letters, 2010, 110(14/15): 559-564.MathSciNetCrossRefMATHGoogle Scholar
- 35.Zhou S M. The conditional diagnosability of crossed cubes under the comparison model. International Journal of Computer Mathematics, 2010, 87(15): 3387-3396.MathSciNetCrossRefMATHGoogle Scholar
- 36.Dong Q, Zhou J L, Fu Y, Yang X F. Embedding a mesh of trees in the crossed cube. Information Processing Letters, 2012, 112(14/15): 599-603.MathSciNetCrossRefMATHGoogle Scholar
- 37.Cheng B L, Fan J X, Jia X H, Zhang S K. Independent spanning trees in crossed cubes. Information Sciences, 2013, 233: 276-289.MathSciNetCrossRefMATHGoogle Scholar
- 38.Cheng B L, Fan J X, Jia X H, Wang J. Dimension-adjacent trees and parallel construction of independent spanning trees on crossed cubes. Journal of Parallel and Distributed Computing, 2013, 73(5): 641-652.CrossRefMATHGoogle Scholar
- 39.Chen H C, Kung T L, Hsu L Y. 2-disjoint-path-coverable panconnectedness of crossed cubes. The Journal of Supercomputing, 2015, 71(7): 2767-2782.CrossRefGoogle Scholar
- 40.Chen H C, Zou Y H, Wang Y L, Pai K J. A note on path embedding in crossed cubes with faulty vertices. Information Processing Letters, 2017, 121: 34-38.MathSciNetCrossRefMATHGoogle Scholar
- 41.Cheng B L, Wang D J, Fan J X. Constructing completely independent spanning trees in crossed cubes. Discrete Applied Mathematics, 2017, 219: 100-109.MathSciNetCrossRefMATHGoogle Scholar
- 42.Diestel R. Graph Theory (4th edition). Springer, 2010.Google Scholar
- 43.Ghemawat S, Gobioff H, Leung S T. The Google file system. In Proc. the 19th ACM Symp. Operating Systems Principles, October 2003, pp.29-43.Google Scholar
- 44.Dean J, Ghemawat S. MapReduce: Simplified data processing on large clusters. Communications of the ACM, 2008, 51(1): 107-113.CrossRefGoogle Scholar