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PL
Poddano ocenie zachowanie sieci teleinformatycznych w warunkach celowych działań niszczących (ataków). Przebadano zdolność sieci o topologii bezskalowej do zapewnienia przeżywalności usług w przypadku eliminacji jej istotnych węzłów, zwanych centrami. Ukazano istotne różnice w poziomie jakości odtwarzania usług dla awarii będącej następstwem ataku w zestawieniu z przypadkiem awarii losowej. Zaproponowano również szereg topologicznych miar określających stopień przeżywalności sieci. Przeanalizowano zarówno sztuczne sieci bezskalowe, jak i sieci rzeczywiste o różnym stopniu bezskalowości. Wyniki poddano analizie porównawczej w zestawieniu z analogicznymi rezultatami uzyskanymi dla sieci o topologii regularnej.
EN
This paper evaluates the behavior of wide-area networks under malicious attacks. In particular, it investigates the capability of scale-free networks to provide service survivability under intentional removal of the most important network nodes. It shows a significant difference in the achieved level of service restoration quality between failures being the result of an attack and random failures. Several topological measures to determine the level of a network survivability have been also proposed.
EN
A comparison of service restoration quality in survivable optical transport networks OTN (WDM) degraded due to physical failures or degraded after intentional attack is described. Survivability assumptions are as follows: end-to-end path protection: preplanned node-disjoint backup path for each working path. The lightpaths optimization problem in survivable networks is NP-complete and we propose the heuristic SCNDP algorithm to solve the problem. The original author’s network simulator was used to model five network: National Science Foundation (NSF) network, PIONIER (Polish Optical Internet). Italian optical network, artificial intermediate network (AIN) and artificial scale-free network (ASF), corresponding to parameters of NSF. Single node outages being either a consequence of physical failures, or resulting from malicious attacks were simulated in each of the five networks. We showed that the differences in the effectiveness of service restoration caused by these two mechanisms are rather small in networks having regular topologies (like NSF), but in contrast, are significant in intermediate and scale-free networks (much more vulnerable to attacks). All results are the original contribution and are published for the first time.
EN
Network survivability is a capability of a networked system to provide its services despite failures or attacks. Attacks, e.g., due to acts of war, being potentially damaging events, were basically considered in the historical definitions of a survivability phenomenon. The meaning of the term: "network survivability" evolved in the last decade. Recently, attacks replayed the important role again. Their nature, however, including intrusions, probes, denials of service, differs from the old one. Survivability is strongly related to other fields of study. In particular, quality of service depends on network survivability. We investigate these dependencies in scale-free networks. Many networks are scale-free, i.e., their node degree distribution follows the power law. Nodes of the highest degrees, called centers, are highly vulnerable to attacks. Elimination of these nodes seriously degrades the overall performance of network services. In this paper we propose a model, which, based on traffic parameters of a demand, like delay or bit rate, allows to establish the survivable and attack proof end-to-end connections. The key idea of this model is that for the significant traffic, it establishes paths, which omit centers. The important connections become more resistant to attacks. We show that in the best case, obtained for the highest class of service, the number of broken connections is reduced even by factor 3. Example results are compared to those for the standard distance metrics. Our model is applicable to many network architectures and many classes of service.
4
Content available remote Node-node distance distribution for growing networks
EN
We present a simulation of the time evolution of the distance matrix. The result is a node-node distance distribution for various kinds of networks. For the exponential trees, analytical formulas are derived for the moments of distance distribution.
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