DocumentCode :
3047167
Title :
Adversarial analyses of window backoff strategies
Author :
Bender, Michael A. ; Farach-Colton, Martin ; He, Simai ; Kuszmaul, Bradley C. ; Leiserson, Charles E.
fYear :
2004
fDate :
26-30 April 2004
Firstpage :
203
Abstract :
Summary form only given. Backoff strategies have typically been analyzed by making statistical assumptions on the distribution of problem inputs. Although these analyses have provided valuable insights into the efficacy of various backoff strategies, they leave open the question as to which backoff algorithms perform best in the worst case or on inputs, such as bursty inputs, that are not covered by the statistical models. We analyze randomized backoff strategies using worst-case assumptions on the inputs.
Keywords :
computational complexity; distributed algorithms; multiprogramming; randomised algorithms; backoff algorithm; randomized backoff strategy; statistical assumption; window backoff strategy; worst-case assumption; Algorithm design and analysis; Delay effects; Distributed processing; Feedback; Helium; Laboratories; Partitioning algorithms; Performance analysis; Stability; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2004. Proceedings. 18th International
Print_ISBN :
0-7695-2132-0
Type :
conf
DOI :
10.1109/IPDPS.2004.1303230
Filename :
1303230
Link To Document :
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