Essential Traffic Parameters for Shared Memory Switch Performance

  • Patrick Eugster
  • Alex Kesselman
  • Kirill Kogan
  • Sergey Nikolenko
  • Alexander Sirotkin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9439)


Cloud applications bring new challenges to the design of network elements, in particular accommodating for the burstiness of traffic workloads. Shared memory switches represent the best candidate architecture to exploit buffer capacity; we analyze the performance of this architecture. Our goal is to explore the impact of additional traffic characteristics such as varying processing requirements and packet values on objective functions. The outcome of this work is a better understanding of the relevant parameters for buffer management to achieve better performance in dynamic environments of data centers. We consider a model that captures more of the properties of the target architecture than previous work and consider several scheduling and buffer management algorithms that are specifically designed to optimize its performance. In particular, we provide analytic guarantees for the throughput performance of our algorithms that are independent from specific distributions of packet arrivals. We furthermore report on a comprehensive simulation study which validates our analytic results.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Patrick Eugster
    • 1
    • 2
  • Alex Kesselman
    • 3
  • Kirill Kogan
    • 4
  • Sergey Nikolenko
    • 5
    • 6
  • Alexander Sirotkin
    • 7
    • 8
  1. 1.Purdue UniversityLafayetteUSA
  2. 2.Technical University of DarmstadtDarmstadtGermany
  3. 3.Google Inc.Mountain ViewUSA
  4. 4.IMDEA Networks InstituteMadridSpain
  5. 5.National Research University Higher School of EconomicsSt. PetersburgRussia
  6. 6.Steklov Institute of Mathematics at St.PetersburgSt.PetersburgRussia
  7. 7.International Laboratory for Applied Network ResearchNational Research University Higher School of EconomicsMoscowRussia
  8. 8.St. Petersburg Institute for Informatics and Automation of the RASSt. PetersburgRussia

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