Admission control in shared memory switches

Patrick Eugster (), Alex Kesselman (), Kirill Kogan (), Sergey Nikolenko () and Alexander Sirotkin ()
Additional contact information
Patrick Eugster: University of Lugano
Alex Kesselman: Google Inc.
Kirill Kogan: IMDEA Networks Institute
Sergey Nikolenko: National Research University Higher School of Economics
Alexander Sirotkin: National Research University Higher School of Economics

Journal of Scheduling, 2018, vol. 21, issue 5, No 5, 533-543

Abstract: Abstract Cloud applications bring new challenges to the design of network elements, in particular the burstiness of traffic workloads. A shared memory switch is a good candidate architecture to exploit buffer capacity; in this work, 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.

Keywords: Buffer management; Admission control; Packet scheduling (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10951-018-0564-2 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jsched:v:21:y:2018:i:5:d:10.1007_s10951-018-0564-2

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10951

DOI: 10.1007/s10951-018-0564-2

Access Statistics for this article

Journal of Scheduling is currently edited by Edmund Burke and Michael Pinedo

More articles in Journal of Scheduling from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().