Abstract
In large-scale data centers, many servers are interconnected via a dedicated networking structure, so as to satisfy specific design goals, such as the low equipment cost, the high network capacity, and the incremental expansion. The topological properties of a networking structure are critical factors that dominate the performance of the entire data center. The existing networking structures are either fully random or completely structured. Although such networking structures exhibit advantages on given aspects, they suffer obvious shortcomings in other essential fields. In this paper, we aim to design a hybrid topology, called R3, which is the compound graph of structured and random topology. It employs random regular graph as a unit cluster and connects many such clusters by means of a structured topology, i.e., the generalized hypercube. Consequently, the hybrid topology combines the advantages of structured as well as random topologies seamlessly. Meanwhile, a coloring-based algorithm is proposed for R3 to enable fast and accurate routing. R3 possesses many attractive characteristics, such as the modularity and expansibility at the cost of only increasing the degree of any node by one. Comprehensive evaluation results show that our hybrid topology possesses excellent topology properties and network performance.
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Lailong Luo received his BS in School of Information System and Management from National University of Defence Technology (NUDT), China in 2013. He is currently working for his MS in College of Information System and Management, NUDT. His research interests include data centers and software defined networks.
Deke Guo received his BS in industry engineering from Beihang University, China in 2001, and PhD in management science and engineering from National University of Defense Technology (NUDT), China in 2008. He is an associate professor with the College of Information System and Management, NUDT. His research interests include distributed systems, software-defined networking, data center networking.
Wenxin Li received his BE from the School of Computer Science and Technology, Dalian University of Technology (DUT), China in 2012. Currently, he is a PhD candidate in the School of Computer Science and Technology, DUT. His research interests include data center networks and cloud computing.
Tian Zhang is an undergraduate from School of Information Management of Wuhan University, China. His major is Information Management and Information System, and his research interest is mainly on wireless sensor networks and data center networking.
Junjie Xie received his BS in computer science and technology from Beijing Institute of Technology, China in 2013. He is currently working for his MS in College of Information System and Management, National University of Defense Technology, China. His research interests include distributed systems, data centers, software defined networks and interconnection networks.
Xiaolei Zhou received his BA from the Information Management Department, Nanjing University, China in 2009, and his MS in military science from the National University of Defense Technology (NUDT), China in 2011. He is currently working for his PhD in the School of Information System and Management, NUDT. His current research interests include indoor localization, wireless sensor networks and data center networking.
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Luo, L., Guo, D., Li, W. et al. Compound graph based hybrid data center topologies. Front. Comput. Sci. 9, 860–874 (2015). https://doi.org/10.1007/s11704-015-4483-5
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DOI: https://doi.org/10.1007/s11704-015-4483-5