Detailed Information

Cited 5 time in webofscience Cited 4 time in scopus
Metadata Downloads

Self-adaptive and reconfigurable distributed computing systems

Authors
Bagchi, Susmit
Issue Date
Sep-2012
Publisher
ELSEVIER
Keywords
Reconfiguration; Stability; Membrane computing; Bio-inspired computing; Cell-signaling; Fault-tolerance; Distributed algorithms
Citation
APPLIED SOFT COMPUTING, v.12, no.9, pp 3023 - 3033
Pages
11
Indexed
SCIE
SCOPUS
Journal Title
APPLIED SOFT COMPUTING
Volume
12
Number
9
Start Page
3023
End Page
3033
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/22066
DOI
10.1016/j.asoc.2012.04.031
ISSN
1568-4946
1872-9681
Abstract
In recent time, the applications of biologically-inspired computing models into various domains of computing fields have gained attention due to a set of advantages. The bio-inspired distributed computing paradigm offers benefits such as, self-detection and self-reconfiguration capabilities of the computing systems. The large scale distributed systems suffer from the arbitrary failure of nodes and dynamic formation of network partitions at any point of time. This paper proposes a novel membrane algorithm for self-detection and self-reconfiguration of large distributed systems on the event of arbitrary node failures resulting in network partitioning. The algorithm is distributed in nature and, it is designed based on the hybridization of biological membrane computing model and cell-signaling mechanisms of biological cells. This paper presents the problem definition, design and analysis of the algorithm. The performance of the algorithm is evaluated through simulation. A detailed comparative analysis of the algorithm with respect to the other contemporary algorithms is presented. (C) 2012 Elsevier B.V. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
공과대학 > Department of Aerospace and Software Engineering > Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE