Communication Network Availability Predictions Based on Measurement Data

Spragins, J.; Markov, Jelena; Magimai.-Doss, Mathew; Mitchell, Stella; Squire, D.

doi:10.1109/tcom.1981.1094888

Cited by 7 publications

(5 citation statements)

References 9 publications

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“…Along with computer simulation data confirming the model's correctness, a heuristic approach for calculating availabilities for more complicated systems is offered. The findings allow for more accurate availability forecasts than could previously be computed for typical forms of the network [19].…”

Section: Introductionmentioning

confidence: 88%

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Modeling the Causes of Power-Related Network Outages Using Discrete-Time Markov Chains

Gedel,

Iddrisu

2023

Wireless Communications and Mobile Computing

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In this paper, we model the causes of power-related network outages in Ghana using discrete-time Markov chains. We used data consisting of 2,756 small-scale carrier telecommunications outages occurring in Ghana, with accompanying root causes over a period of 5 years and 8 months, from August 2015 to April 2021. The results indicate that the majority (n = 1,404) of the network outages were caused by the generators while the least number (18) of outages were caused by a communication equipment. However, longer network outages were caused by fuel issues with an average outage time of 1,027.82 min over the study period. The transition probability matrix obtained from the data revealed that regardless of the present cause of the network outage, the probability that the next network outage will be caused by the generators is higher than the probability that the outage will be attributable to any other cause. The steady-state distribution indicates that in the long run (n ≥ 16), 51% of the network outages will be caused by the “Generators” while 10.8% of the network outages will be caused by the “Batteries.” We also checked and simulated the probabilities of a network outage caused by any of the 12 possible root causes for 12 steps. It seemed apparent from the simulations that generators are the most likely cause of network outages from Step 1 up to Step 7, irrespective of what the initial cause of the network outage is. With these findings, players in the telecommunications industry can clearly plan better to reduce future network outages.

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Section: Introductionmentioning

confidence: 88%

“…In a different study by Spragins et al [19], the duration of failures and single-line availabilities' probability distribution functions are provided. Along with computer simulation data confirming the model's correctness, a heuristic approach for calculating availabilities for more complicated systems is offered.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Causes of Power-Related Network Outages Using Discrete-Time Markov Chains

Gedel,

Iddrisu

2023

Wireless Communications and Mobile Computing

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“…The methods of network reliability also allow link-failure probabilities that are significant fractions of one, ruling out some simplifying numerical approximations that can be useful where the availability of elements is well over 99.9%. As Spragins also has argued [21], [30], [32], we need to consider the availability of specific path configurations through networks, with detailed functional consideration of the failure and reconfiguration mechanisms, not measures of the graphtheoretic extent to which a topology alone remains connected in the presence of accumulating failures. Spragins has also pioneered the treatment of dependent failure issues [35]- [37], which we also consider in our specific context.…”

Section: Literaturementioning

confidence: 99%

High availability path design in ring-based optical networks

Grover¹

1999

IEEE/ACM Trans. Networking

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This work develops mathematical models for path availability and provisioning resources required in various strategies for realizing high availability service paths in a transport environment of bidirectional line-switched rings or shared protection optical (wavelength division multiplexing) rings. The work originated in response to user requests for SONET service paths with unavailabilities under 30 s/year. A number of schemes for redundant routing and ring interconnection are considered as options to meet such a demanding target in the most economic way. An analytical framework for comparison of various provisioning schemes allows a "cost effectiveness" assessment of four highperformance alternatives, in terms of total resource investment and the corresponding service unavailability relative to a singlefed path construction. The logical models of cost and availability can be used in a variety of SONET or optical-ring transport planning studies or perhaps in future automated provisioning tools. An important finding is that while the availability benefit of dual-ring interconnection is high in metro-ring networks, the availability of paths through long-haul ring networks may be relatively poor due to lower limits from two-failure intra-ring combinations.

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“…In particular, the reliability prediction allow us to determine the redundancy requirements in the given net-work, the ability of a network to maintain an acceptable reliability level under extreme environmental conditions and assess the impact of design changes on the reliability of the overall network [17]. Similarly, the availability prediction allows us to evaluate various maintenance design options to achieve the desired availability of the network [18].…”

Section: Introductionmentioning

confidence: 99%

“…work, the ability of a network to maintain an acceptable reliability level under extreme environmental conditions and assess the impact of design changes on the reliability of the overall network [17]. Similarly, the availability prediction allows us to evaluate various maintenance design options to achieve the desired availability of the network [18].The qualitative and quantitative reliability analysis requires the selection of an appropriate mathematical modeling and analysis technique. The modeling technique must be able to effectively capture the important parameters of the real system and the analysis technique should be capable of providing insights into the system behavior without running (or executing) the real system.…”

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confidence: 99%

Reliability modeling and analysis of communication networks

Ahmed

Hasan

Pervez

et al. 2017

Journal of Network and Computer Applications

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In recent times, the functioning of various aspects of modern society-ranging from the various infrastructural utilities such as electrical power, water to socio-economical aspects such as telecommunications, business, commerce, education-has become critically reliant on communication networks, and particularly on the Internet. With the migration of critical facilities to the Internet, it has become vitally important to ensure the reliability and availability of networks. In this paper, we study various modeling and analysis techniques that can aid in the study of reliability of communication networks. In this regard, we provide background on the modeling techniques (such as reliability block diagrams, fault trees, Markov chains, etc.) and analysis techniques (such as mathematical analytical methods, simulation methods, and formal methods). Apart from providing the necessary background, we also critically evaluate the pros and cons of different approaches, and provide a detailed survey of their applications in communication networks. To the best of our knowledge, this is the first in-depth review of the application of reliability modeling and analysis techniques in communication networks. work, the ability of a network to maintain an acceptable reliability level under extreme environmental conditions and assess the impact of design changes on the reliability of the overall network [17]. Similarly, the availability prediction allows us to evaluate various maintenance design options to achieve the desired availability of the network [18].The qualitative and quantitative reliability analysis requires the selection of an appropriate mathematical modeling and analysis technique. The modeling technique must be able to effectively capture the important parameters of the real system and the analysis technique should be capable of providing insights into the system behavior without running (or executing) the real system. There are numerous techniques that can provide analysis in the early phase, when only initial details are available of the design, and there are other techniques that cater the analysis of the later design phases, when more precise implementation details are available [16]. Some of the most widely used formalisms/techniques for modeling reliability and availability of communication networks are: Reliability Block Diagram (RBD) [19], Fault Tree (FT) [20], and Markov Chain (MC) [21]. Traditionally, the models developed using these techniques are analyzed using analytical methods or simulation tools.Recently, the computer networks community has shown great interest in the utilization of formal methods [22] as a reliability analysis technique for communication networks. Formal methods use mathematical logic to precisely model the system's intended behavior and deploy mathematical reasoning to construct an irrefutable proof that the given system satisfies its requirements. This kind of mathematical modeling and analysis makes formal methods an accurate and rigorous analysis method compared to the traditional a...

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Communication Network Availability Predictions Based on Measurement Data

Cited by 7 publications

References 9 publications

Modeling the Causes of Power-Related Network Outages Using Discrete-Time Markov Chains

Modeling the Causes of Power-Related Network Outages Using Discrete-Time Markov Chains

High availability path design in ring-based optical networks

Reliability modeling and analysis of communication networks

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