An analytical model for multi-epidemic information dissemination

dc.contributor.author	Αναγνωστόπουλος, Χρήστος Β.	el
dc.contributor.author	Χατζηευθυμιάδης, Στάθης Π.	el
dc.contributor.author	Ζέρβας, Ευάγγελος	el
dc.date.accessioned	2015-05-23T18:28:40Z
dc.date.available	2015-05-23T18:28:40Z
dc.date.issued	2015-05-23
dc.identifier.uri	http://hdl.handle.net/11400/11012
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	http://www.elsevier.com/	en
dc.subject	Epidemics
dc.subject	Information dissemination
dc.subject	Stochastic process
dc.subject	Transmutation
dc.subject	Επιδημίες
dc.subject	Διάδοση πληροφοριών
dc.subject	Στοχαστική διαδικασία
dc.subject	Μεταλλαγή
dc.title	An analytical model for multi-epidemic information dissemination	en
heal.type	journalArticle
heal.classification	Technology
heal.classification	Electrical engineering
heal.classification	Τεχνολογία
heal.classification	Ηλεκτρολογία Μηχανολογία
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh85133147
heal.classificationURI	http://zbw.eu/stw/descriptor/18426-4
heal.classificationURI	N/A-Τεχνολογία
heal.classificationURI	N/A-Ηλεκτρολογία Μηχανολογία
heal.keywordURI	http://zbw.eu/stw/descriptor/15225-1
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh2001009147
heal.identifier.secondary	DOI: 10.1016/j.jpdc.2010.08.010
heal.language	en
heal.access	campus
heal.publicationDate	2011-01
heal.bibliographicCitation	ANAGNOSTOPOULOS, C.B., HADJIEFTHYMIADES, S.P. & ZERVAS, E. (2011). An analytical model for multi-epidemic information dissemination. Journal of Parallel and Distributed Computing. [online] 71 (1). p. 87-104. Available from: http://www.elsevier.com/[Accessed 01/09/2010]	en
heal.abstract	Contemporary distributed systems usually involve the spreading of information by means of ad-hoc dialogs between nodes (peers). This paradigm resembles the spreading of a virus in the biological perspective (epidemics). Such abstraction allows us to design and implement information dissemination schemes with increased efficiency. In addition, elementary information generated at a certain node can be further processed to obtain more specific, higher-level and more valuable information. Such information carries specific semantic value that can be further interpreted and exploited throughout the network. This is also reflected in the epidemical framework through the idea of virus transmutation which is a key component in our model. We establish an analytical framework for the study of a multi-epidemical information dissemination scheme in which diverse 'transmuted epidemics' are spread. We validate our analytical model through simulations. Key outcomes of this study include the assessment of the efficiency of the proposed scheme and the prediction of the characteristics of the spreading process (multi-epidemical prevalence and decay).	en
heal.publisher	Elsevier	en
heal.journalName	Journal of Parallel and Distributed Computing	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true