IDTCP: An effective approach to mitigating the TCP incast problem in data center networks
Guodong Wang (),
Yongmao Ren (),
Ke Dou () and
Jun Li ()
Additional contact information
Guodong Wang: Graduate University of Chinese Academy of Sciences
Yongmao Ren: Computer Network Information Center of Chinese Academy of Sciences
Ke Dou: Graduate University of Chinese Academy of Sciences
Jun Li: Computer Network Information Center of Chinese Academy of Sciences
Information Systems Frontiers, 2014, vol. 16, issue 1, No 4, 35-44
Abstract:
Abstract Recently, TCP incast problem in data center networks has attracted a wide range of industrial and academic attention. Lots of attempts have been made to address this problem through experiments and simulations. This paper analyzes the TCP incast problem in data centers by focusing on the relationships between the TCP throughput and the congestion control window size of TCP. The root cause of the TCP incast problem is explored and the essence of the current methods to mitigate the TCP incast is well explained. The rationality of our analysis is verified by simulations. The analysis as well as the simulation results provides significant implications to the TCP incast problem. Based on these implications, an effective approach named IDTCP (Incast Decrease TCP) is proposed to mitigate the TCP incast problem. Analysis and simulation results verify that our approach effectively mitigates the TCP incast problem and noticeably improves the TCP throughput.
Keywords: Congestion control; Data center networks; TCP incast (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://link.springer.com/10.1007/s10796-013-9463-4 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:infosf:v:16:y:2014:i:1:d:10.1007_s10796-013-9463-4
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796
DOI: 10.1007/s10796-013-9463-4
Access Statistics for this article
Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao
More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().