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Cited 2 time in webofscience Cited 3 time in scopus
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Design and topological analysis of probabilistic distributed mutual exclusion algorithm with unbiased refined ordering

Authors
Bagchi, Susmit
Issue Date
Jun-2019
Publisher
Elsevier BV
Keywords
Distributed computing; Logical clock; Mutual exclusion; Probability; Random variable; Topological spaces
Citation
Future Generation Computer Systems, v.95, pp 175 - 186
Pages
12
Indexed
SCIE
SCOPUS
Journal Title
Future Generation Computer Systems
Volume
95
Start Page
175
End Page
186
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/9102
DOI
10.1016/j.future.2018.12.069
ISSN
0167-739X
1872-7115
Abstract
The applications of distributed computing systems are pervasive in nature involving multiple shared resources. The distributed mutual exclusion algorithms of various classes are employed to control concurrency of accessing shared resources maintaining data consistency. In general, the distributed mutual exclusion algorithms are designed based on fixed or dynamic graph structures formed by a set of processes, where the distributed mutual exclusion mechanisms are realized depending upon timestamp based ordering of events or by employing token circulation in the graph. On the contrary, in large scale heterogeneous distributed systems, an aggregate set of processes can be generated under special circumstances, where processes in a group are equally eligible to enter into critical section. In order to maintain safety and liveness properties of mutual exclusion in such cases, the probabilistic characterization as well as topological analysis of aggregate set in computing space is necessary. This paper proposes a probabilistic algorithm and its topological characterization for mutual exclusion in aggregate set of processes. The analysis of failure model of strictly ordered distributed inclusion-exclusion designs is constructed in the presence of aggregate set. The unbiased probabilistic algorithm is based on two-phased elastic randomization. The algorithm is evaluated through detailed simulation and, the related probabilistic characterization in topological subspace is evaluated. A detailed comparative analysis of the algorithm with respect to other distributed mutual exclusion algorithms is presented. (C) 2019 Elsevier B.V. All rights reserved.
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