DocumentCode :
3517224
Title :
Network tomography-based unresponsive flow detection and control
Author :
Habib, Ahsan ; Bhargava, Bharat
Author_Institution :
Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA
fYear :
2003
fDate :
28-30 May 2003
Firstpage :
258
Lastpage :
264
Abstract :
To avoid a congestion collapse, network flows should adjust their sending rates. Adaptive flows adjust the rate, while unresponsive flows do not respond to congestion and keep sending packets. Unresponsive flows waste resources by taking their share of the upstream links of a domain and dropping packets later when the downstream links are congested We use network tomography-an edge-to-edge mechanism to infer per-link internal characteristics of a domain-to identify unresponsive flows that cause packet drops in other flows. We have designed an algorithm to dynamically regulate unresponsive flows. The congestion control algorithm is evaluated using both adaptive and unresponsive flows, with sending rates as high as four times of the bottleneck bandwidth, and in presence of short and long-lived background traffic.
Keywords :
frame relay; telecommunication congestion control; telecommunication traffic; tomography; congestion control algorithm; flow control; network tomography; packet drop; packet traffic; unresponsive flow detection; Adaptive control; Algorithm design and analysis; Bandwidth; Computer networks; Computer science education; Computer security; Heuristic algorithms; Information security; Intelligent networks; Tomography;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Distributed Computing Systems, 2003. FTDCS 2003. Proceedings. The Ninth IEEE Workshop on Future Trends of
ISSN :
1071-0485
Print_ISBN :
0-7695-1910-5
Type :
conf
DOI :
10.1109/FTDCS.2003.1204345
Filename :
1204345
Link To Document :
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