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RRect: A Novel Server-Centric Data Center Network with High Power Efficiency and Availability

  • Stony Brook University

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

In this paper, we propose a novel server-centric network for data centers, called RRect. Compared to existing server-centric networks, RRect provides a more graceful degradation performance in the presence of component failure. Meanwhile, RRect enjoys a linear diameter to the network order and multiple parallel paths. We present algorithms to find paths and to construct all parallel paths between any pair of servers in RRect. We also show that without using any power-Aware routing algorithm, RRect behaves more power efficient in its interconnection network. To meet today's stringent high availability requirement, RRect can be configured into redundancy and failover scheme. In particular, RRect can be configured into both symmetric and asymmetric redundancy modes to cater different applications' needs, which cannot be implemented in existing server-centric networks. Moreover, RRect gives more flexibility to adjust the network size. Given the same switches, by fine tuning the parameters, RRect provides numerous structures with different sizes, while preserving the properties of short diameter and multiple parallel paths. Our comprehensive simulations show that RRect gives much better graceful degradation performance in the presence of component failure, and RRect saves much energy in the interconnection network. Meanwhile, RRect can maintain the same performance on many critical metrics as BCube, including short diameter and excellent aggregate throughput. All these features make RRect a very empirical structure for enterprise dater center network products.

Original languageEnglish
Article number8318604
Pages (from-to)914-927
Number of pages14
JournalIEEE Transactions on Cloud Computing
Volume8
Issue number3
DOIs
StatePublished - Jul 1 2020

Keywords

  • Data center networks
  • diameter
  • graceful degradation
  • high availability
  • parallel paths
  • power efficiency
  • server-centric

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