DocumentCode
1912734
Title
Effective Data Dissemination for Large-Scale Complex Critical Infrastructures
Author
Esposito, Christian ; Martino, C.D. ; Cinque, Marcello ; Cotroneo, Domenico
Author_Institution
Dipt. di Inf. e Sist. (DIS), Univ. degli studi di Napoli Federico II, Naples, Italy
fYear
2010
fDate
18-25 July 2010
Firstpage
64
Lastpage
69
Abstract
Large-scale complex infrastructures are emerging as new computing platforms for the federation of world-wide mission critical systems over the Internet. However, standard approaches to data dissemination are still not adequate to the scale of these systems. The best-effort delivery guarantees of the Internet and the occurrence of node failures may compromise the correct and timely delivery of data, and hence the mission of the overall infrastructure. This paper presents a peer-to-peer approach for resilient and scalable data dissemination over large-scale complex critical infrastructures. The approach is based on the adoption of epidemic dissemination algorithms between peer groups, combined with the semi-active replication of group leaders. The effectiveness of the approach is shown by means of extensive simulation experiments, based on Stochastic Activity Networks. Results demonstrate that the use of epidemic algorithms over peer-to-peer overlays can achieve a 5 nines (99.999%) resiliency level, compared to the 3 nines (99.9%) of the standard solution.
Keywords
data handling; safety-critical software; software architecture; computing platforms; data dissemination; effective data dissemination; epidemic dissemination; large scale complex critical infrastructures; stochastic activity networks; world wide mission critical systems; Internet; Lead; Organizations; Peer to peer computing; Protocols; Quality of service; Scalability; Availability Assessment; Peer-to-Peer Systems; Petri Net; Publish/Subscribe Middleware;
fLanguage
English
Publisher
ieee
Conference_Titel
Dependability (DEPEND), 2010 Third International Conference on
Conference_Location
Venice
Print_ISBN
978-1-4244-7530-8
Type
conf
DOI
10.1109/DEPEND.2010.18
Filename
5562847
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