A tool for computing computer network reliability

Younes, Ahmed Mohamed Mosallem; Girgis, Moheb R.

doi:10.1080/0020716031000103385

Cited by 10 publications

(9 citation statements)

References 7 publications

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“…Table compares the execution times of the Simple Algorithm for Computing Network Reliability (SACNR), LPCA, and P‐LPCA for each network in Table . The first three columns represent the runtimes of the three algorithms, and the last two columns indicate the speed up of P‐LPCA over LPCA and SACNR.…”

Section: Methodsmentioning

confidence: 99%

“…Heidtmann compared his algorithm with Abraham's in terms of statistics and characteristics. Younes and Girgis developed a simple approach for finding the two‐terminal network reliability based on the link matrix. Several approaches for calculating terminal‐pair reliability based on SDP have also been developed.…”

Section: Related Workmentioning

confidence: 99%

“…43 Network 10 is from the study of Rai et al 44 , and Network 12 is from Rocco and Muselli's paper. 55 46 LPCA, and P-LPCA for each network in Table II. The first three columns represent the runtimes of the three algorithms, and the last two columns indicate the speed up of P-LPCA over LPCA and SACNR.…”

Section: Experimental Networkmentioning

confidence: 99%

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A Parallel Strategy for the Logical‐probabilistic Calculus‐based Method to Calculate Two‐terminal Reliability

Nguyen

2015

Quality & Reliability Eng

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The theory of network reliability has been applied to many complicated network structures, such as computer and communication networks, piping systems, electricity networks, and traffic networks. The theory is used to evaluate the operational performance of networks that can be modeled by probabilistic graphs. Although evaluating network reliability is an Non-deterministic Polynomial-time hard problem, numerous solutions have been proposed. However, most of them are based on sequential computing, which under-utilizes the benefits of multi-core processor architectures. This paper addresses this limitation by proposing an efficient strategy for calculating the two-terminal (terminal-pair) reliability of a binary-state network that uses parallel computing. Existing methods are analyzed. Then, an efficient method for calculating terminal-pair reliability based on logical-probabilistic calculus is proposed. Finally, a parallel version of the proposed algorithm is developed. This is the first study to implement an algorithm for estimating terminal-pair reliability in parallel on multicore processor architectures. The experimental results show that the proposed algorithm and its parallel version outperform an existing sequential algorithm in terms of execution time.

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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A Parallel Strategy for the Logical‐probabilistic Calculus‐based Method to Calculate Two‐terminal Reliability

Nguyen

2015

Quality & Reliability Eng

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“…Similarly, in modeling a telecommunication network, it often represents a communication cable or plug-in card or field replaceable unit. Available literature on reliable networks can be broadly classified into two streams: literature that address the problem of evaluating the performance of a reliable network [6]- [12], and literature that deal with the problem of designing a reliable network with the aim of minimizing the network establishment cost and simultaneously optimizing the network performance [13]- [15].…”

Section: Introductionmentioning

confidence: 99%

Speeding Up the Estimation of the Expected Value of Maximum Flow Through Reliable Networks

Sharma

Ghosh

2013

IEEE Trans. Rel.

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A common measure of performance of a reliable network, i.e., a network in which elements are failure prone, is the expected value of the maximum flow between a pre-specified source node and a pre-specified terminal node in the network. The problem of determining the expected value of maximum flow is computationally hard. Therefore, for practical sized networks, it is estimated through Monte Carlo based simulation methods which estimate the measure by evaluating the maximum flows in a large sample of network states. Such methods are computationally expensive. In this paper, we present an algorithm which speeds up the process of evaluating maximum flows in the sampled states by a factor of three on two difficult classes of randomly generated networks. This speed-up allows us to compute the measure for larger networks than is currently possible. It also allows us to obtain more accurate estimates on similar sized problems within similar execution times. Index Terms-Expected value of maximumflow, Monte Carlo simulation, network flows.

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“…Failure data of X2 (Complete Data) [17] The following failure times (days) was obtained by testing 15 The result is shown in Figure 7.3.…”

Section: S1mentioning

confidence: 99%

Development of a software tool for reliability estimation

Li¹

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Development of a Software Tool for Reliability Estimation Chihui Li This thesis presents Version 2.0 of Software Tool for Reliability Estimation (STORE 2.0). It expands on the work done by Parekh [1] by revising the algorithm for tie-set and cut-set calculation, by including fault tree reliability analysis, by analyzing state dependent system, and by integrating component and system reliability analysis. This thesis also presents an approach to the simplification of complex systems by collapsing series and parallel components into a subsystem. The approach was illustrated on an example described by Nelson et al. [2]. The example had 16 components resulting in ten cut-sets and fifty five tie-sets. Upon simplification, the problem was reduced to one tie-set only. STORE 2.0 integrates parameter estimation, component reliability analysis, system reliability analysis, estimation of reliability of state dependent systems, and fault tree analysis. It was verified and validated on several examples taken from the open literature. The software was developed in Visual Basic 2008 with SQL as the database.

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A tool for computing computer network reliability

Cited by 10 publications

References 7 publications

A Parallel Strategy for the Logical‐probabilistic Calculus‐based Method to Calculate Two‐terminal Reliability

A Parallel Strategy for the Logical‐probabilistic Calculus‐based Method to Calculate Two‐terminal Reliability

Speeding Up the Estimation of the Expected Value of Maximum Flow Through Reliable Networks

Development of a software tool for reliability estimation

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