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Applied Mathematical Modelling
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Service reliability modeling of distributed computing systems with virus epidemics

Authors: Li, Yan-Fu; Peng, Rui;

Service reliability modeling of distributed computing systems with virus epidemics

Abstract

Distributed computing (DC) system is widely implemented due to its low setup cost and high computational capability. However, it might be vulnerable to malicious attacks like computer virus due to its network structure. The service reliability, defined as the probability of fulfilling a task before a specified time, is an important metric of the quality of DC system. This paper attempts to model and compute the service reliability for the DC system under virus epidemics. Firstly, the DC system architecture is modeled by an undirected graph whose nodes (i.e. computers) have a continuous-state model representing its computational capability. Then a set of epidemic differential equations are formulated and solved to obtain the state dynamics of each node under the virus epidemics. A universal generating function (UGF) based approach is proposed to calculate the service reliability of DC system. Numerical results show the effectiveness of the proposed method. The sensitivity analysis on the model parameters, the comparison with centralized computing system and the optimization of defense level parameter are also conducted.

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Keywords

universal generating function, distributed computing system, service reliability, virus epidemics, differential equations, [INFO] Computer Science [cs], Distributed systems, Reliability, testing and fault tolerance of networks and computer systems, continuous-state model, continuous- state model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
Green
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