Abstract
Recently, data center networks (DCN) have received significant attention from the academic and industry. However, researches of DCN are mainly concentrated on the improvement of network architectures and the design of routing protocols, or the performance evaluation from the perspective of node importance. In contrast to existing solutions, in this paper, we propose using maximum-flow theory to assess the network performance. Firstly, we abstract two kinds of typical DCN architectures and then formulate and convert the performance analysis of those architectures into a maximum-flow problem including a supersource and a supersink. Secondly, we get the value of maximum-flow by using Edmonds and Goldberg algorithm. Last but not the least, based on the theory of maximum-flow and Minimal cut sets, we get the critical edges for each architecture. Extended experiments and analysis show that our method is effective and indeed introduce low overhead on computation. In addition, the method and issues observed in this paper is generic and can be widely used in newly proposed DCN architectures.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Vaquero LM, Rodero-Merino L, Caceres J, Lindner M (2008) A break in the clouds: towards a cloud definition. ACM SIGCOMM Comput Commun Rev 39:50–55
Peng K, Zou H, Lin R, Yang F (2012) Small business-oriented index construction of cloud data. In: Proceedings in 12th international conference on algorithms and architectures for parallel processing, pp 156–165
Guo C, Wu H, Tan K, Shi L, Zhang Y, Lu S (2008) Dcell: a scalable and fault-tolerant network structure for data centers. ACM SIGCOMM Comput Commun Rev 75–86
Li D, Guo C, Wu H, Tan K, Zhang Y, Lu S (2009) FiConn: using backup port for server interconnection in data centers. In: Proceedings in 28th conference on computer communications, pp 2276–2285
Guo C, Lu G, Li D, Wu H, Zhang X, Shi Y, Tian C, Zhang Y, Lu S (2009) BCube: a high performance, server-centric network architecture for modular data centers. ACM SIGCOMM Comput Commun Rev 39:63–74
Leiserson CE (1985) Fat-trees: universal networks for hardware-efficient supercomputing. Comput IEEE Trans 100(10):892–901
Greenberg A, Hamilton JR, Jain N, Kandula S, Kim C, Lahiri P, Maltz DA, Patel P, Sengupta S (2009) VL2: a scalable and flexible data center network. In: Proceedings of ACM SIGCOMM computer communication review, pp 51–62
Liao Y, Yin D, Gao L (2010) Dpillar: scalable dual-port server interconnection for data center networks. In: Proceedings in 19th international conference on computer communications and networks, pp 1–6
Shangguang W, Zheng Z, Qibo S, Hua Z, Fangchun Y (2011) Cloud model for service selection. In: Proceedings in 30th IEEE conference on computer communications workshops on cloud computing computer communications workshops, pp 666–671
Zhang Y, Su AJ, Jiang G (2011) Understanding data center network architectures in virtualized environments: a view from multi-tier applications. Comput Netw 55:2196–2208
Meng X, Pappas V, Zhang L (2010) Improving the scalability of data center networks with traffic-aware virtual machine placement. In: Proceedings in 29th IEEE conference on computer communications, pp 1–9
Acknowledgments
This work is supported by the National Natural Science Fund China under Grant No. 2009CB320406, the National 863 High-tech Project of China under Grant No. 2011AA01A102, Funds for Creative Research Groups of China (60821001) and State Key Lab of Networking and Switching Technology. Ph.D. Programs Foundation of Ministry of Education (20110005130001).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Peng, K., Lin, R., Huang, B., Zou, H., Yang, F. (2014). Assessment of Performance in Data Center Network Based on Maximum Flow. In: Huang, YM., Chao, HC., Deng, DJ., Park, J. (eds) Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Lecture Notes in Electrical Engineering, vol 260. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7262-5_50
Download citation
DOI: https://doi.org/10.1007/978-94-007-7262-5_50
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-7261-8
Online ISBN: 978-94-007-7262-5
eBook Packages: EngineeringEngineering (R0)