Cited 4 time in
Self-adaptive and reconfigurable distributed computing systems
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Bagchi, Susmit | - |
| dc.date.accessioned | 2022-12-27T01:44:12Z | - |
| dc.date.available | 2022-12-27T01:44:12Z | - |
| dc.date.issued | 2012-09 | - |
| dc.identifier.issn | 1568-4946 | - |
| dc.identifier.issn | 1872-9681 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/22066 | - |
| dc.description.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. | - |
| dc.format.extent | 11 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | ELSEVIER | - |
| dc.title | Self-adaptive and reconfigurable distributed computing systems | - |
| dc.type | Article | - |
| dc.publisher.location | 네델란드 | - |
| dc.identifier.doi | 10.1016/j.asoc.2012.04.031 | - |
| dc.identifier.scopusid | 2-s2.0-84863445301 | - |
| dc.identifier.wosid | 000306107900028 | - |
| dc.identifier.bibliographicCitation | APPLIED SOFT COMPUTING, v.12, no.9, pp 3023 - 3033 | - |
| dc.citation.title | APPLIED SOFT COMPUTING | - |
| dc.citation.volume | 12 | - |
| dc.citation.number | 9 | - |
| dc.citation.startPage | 3023 | - |
| dc.citation.endPage | 3033 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Computer Science | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
| dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
| dc.subject.keywordAuthor | Reconfiguration | - |
| dc.subject.keywordAuthor | Stability | - |
| dc.subject.keywordAuthor | Membrane computing | - |
| dc.subject.keywordAuthor | Bio-inspired computing | - |
| dc.subject.keywordAuthor | Cell-signaling | - |
| dc.subject.keywordAuthor | Fault-tolerance | - |
| dc.subject.keywordAuthor | Distributed algorithms | - |
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