Award Date
1-1-1993
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Committee Member
Ajoy Kumar Datta
Number of Pages
35
Abstract
A self-stabilizing system is a network of processors, which, when started from an arbitrary (and possibly illegal) initial state, always returns to a legal state in a finite number of steps. Self-stabilization is an evolving paradigm in fault-tolerant computing. This research will be the first time self-stabilization is used in the areas of deadlock detection and prevention. Traditional deadlock detection algorithms have a process initiate a probe. If that probe travels around the system and is received by the initiator, there is a cycle in the system, and deadlock is detected. In order to prevent deadlocks, algorithms usually rank nodes in order to determine if an added edge will create a deadlock in the system. In a self-stabilizing system, perturbances are automatically dealt with. For the deadlock model, the perturbances in the system are requests and releases of resources. So, the self-stabilizing deadlock detection algorithm will automatically detect a deadlock when a request causes a cycle in the wait-for graph. The self-stabilizing prevention algorithm prevents deadlocks in a similar manner. The self-stabilizing algorithms do not have to be initiated by any process because the requests and releases create a perturbance which is dealt with automatically.
Keywords
Algorithms; Deadlock; Distributed; Self; Stabilizing; System
Controlled Subject
Computer science
File Format
File Size
1464.32 KB
Degree Grantor
University of Nevada, Las Vegas
Language
English
Permissions
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Repository Citation
Flatebo, Mitchell Elliott, "Self-stabilizing deadlock algorithms in distributed systems" (1993). UNLV Retrospective Theses & Dissertations. 289.
http://dx.doi.org/10.25669/mt0e-efpw
Rights
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