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
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