When TCP Meets Reconfigurations: A Comprehensive Measurement Study

Kaan Aykurt, Johannes Zerwas, Andreas Blenk, Wolfgang Kellerer

Research output: Contribution to journalArticlepeer-review


The diversity of deployed applications in data centers leads to a complex traffic mix in the network. Reconfigurable Data Center Networks (RDCNs) have been designed to fulfill the demanding requirements of ever-changing data center traffic. However, they pose new challenges for network traffic engineering, e.g., interference between reconfigurations, transport layer protocols, and congestion control (CC) algorithms. This raises a fundamental research problem: can the current transport layer protocols handle frequent network updates? This paper focuses on TCP and presents a measurement study of TCP performance in RDCNs. In particular, it evaluates diverse traffic mixes combining TCP variants, UDP, and QUIC transport protocols. The quantitative analysis of the measurements shows that migrated TCP flows suffer from frequent reconfigurations. The effect of reconfigurations on the cost, e.g., increased Flow Completion Time (FCT), depending on the traffic mix is modeled with Machine Learning (ML) methods. The availability of such a model will provide insights into the relationship between the reconfiguration settings and the FCT. Our model explains 88% of the variance in the FCT increase under different reconfiguration settings.

Original languageEnglish
Pages (from-to)1372-1386
Number of pages15
JournalIEEE Transactions on Network and Service Management
Issue number2
StatePublished - 1 Apr 2024


  • QUIC measurements
  • Reconfigurable data center networks
  • TCP measurements


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