DocumentCode
3042280
Title
Probabilistic Self-Stabilization and Random Walks
Author
Yamashita, Masafumi
Author_Institution
Dept. of Inf., Kyushu Univ., Fukuoka, Japan
fYear
2011
fDate
Nov. 30 2011-Dec. 2 2011
Firstpage
1
Lastpage
7
Abstract
A distributed system is said to be probabilistic self-stabilizing, if it eventually converges to legitimate computation with probability 1, starting from any global configuration. Like a self-stabilizing system, a probabilistic self-stabilizing system tolerates any number of transient failures and recovers legitimate computation, but only probabilistically unlike a self-stabilizing system. After introducing the notion of probabilistic self-stabilizing systems, we discuss how to design probabilistic self-stabilizing algorithms.
Keywords
distributed algorithms; random processes; stability; distributed system; legitimate computation; probabilistic self-stabilizing algorithms; random walks; transient failures; Algorithm design and analysis; Communication networks; Computational modeling; Convergence; Markov processes; Probabilistic logic; Transient analysis; Markov chain; cover time; hitting time; probabilistic self-stabilization; random walk; self-stabilization; weak stabilization;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking and Computing (ICNC), 2011 Second International Conference on
Conference_Location
Osaka
Print_ISBN
978-1-4577-1796-3
Type
conf
DOI
10.1109/ICNC.2011.11
Filename
6131787
Link To Document