Network Resilience in Future Optical Networks

Wosinska, Lena; Colle, Didier; Demeester, Piet; Katrinis, Kostas; Lackovic, M.; Lapčević, Ozren; Lievens, Ilse; Markidis, George; Mikac, Branko; Pickavet, Mario; Puype, Bart; Skorin-Kapov, Nina; Staessens, Dimitri; Tzanakaki, Anna

doi:10.1007/978-3-642-01524-3_10

Cited by 11 publications

(8 citation statements)

References 20 publications

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“…Based on real data presented in [30], [9], we set failure dependency between cables contained in the same SRLG to be 0.7. The consequence of this failure dependency is that, on average, 70% of the time a failure of a part of cable contained in SRLG will affect both cables, and the rest of the time will affect only one.…”

Section: B Simulation Results For Network Unavailabilitymentioning

confidence: 99%

Impact evaluation of physical length of shared risk link groups on optical network availability using Monte Carlo simulation

Miletić

Mikac

Džanko

2013

Proceedings of the 2013 18th European Conference on Network and Optical Communications &Amp; 2013 8th Conference on Optical Cab

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In optical networks a group of logically distinct links can unintentionally share a physical resource (e.g. a cable or a duct). Such a group, called shared risk link group (SRLG), introduces a situation where a single failure of common resource can cause multiple failures. Failure of common resource usually occurs due to physical force (e.g. digging or earthquake) and causes failures of multiple links. Specifically, such a failure can cause both working and spare wavelength path of a logical connection between two edge nodes to fail at the same time, leaving them disconnected until a repair is done. The usual approach to solving this problem consists of introducing more spare capacity to the network and also using a routing algorithm that takes SRLGs into account when computing paths. Such a routing algorithm avoids creating working and spare path pairs that have links contained in the same SRLG, to minimize the negative impact of SRLG failure on logical connection availability. In this paper the impact of physical length of the SRLGs on network availability is evaluated using Monte Carlo simulation. New simulation model for availability evaluation is implemented by discrete-event network simulator ns-3. Implementation approach is discussed, and an overview of model features is provided. For simple cases, Monte Carlo simulation results obtained by using the model are compared to analytical results. The availability results for the general case are obtained using Monte Carlo simulation and discussed.

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Section: B Simulation Results For Network Unavailabilitymentioning

confidence: 99%

Impact evaluation of physical length of shared risk link groups on optical network availability using Monte Carlo simulation

Miletić

Mikac

Džanko

2013

Proceedings of the 2013 18th European Conference on Network and Optical Communications &Amp; 2013 8th Conference on Optical Cab

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“…The problem of a lack of such data is evident, and the models and simulations based on assumed values of failure rate and mean time to repair are often used in the literature [1,2].…”

Section: Failure Analysis Of Optical Cable Networkmentioning

confidence: 99%

Heuristic approach to availability calculation of path protected optical network based on the analysis of cable failures

Jurdana

Mikac

Kreso³

2011

2011 13th International Conference on Transparent Optical Networks

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This paper presents a new method of calculating the availability of path protected optical network through a heuristic approach. The algorithm for finding and calculating the availability of working and protection paths according to the criterion of highest availability includes parameters called weighting factors. Weighting factors are defined and classified based on the analysis of cable failures at the physical layer of a real optical network. The results of calculating the availability via the proposed method and standard method for the same segment of the referent optical network were compared and analyzed.

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“…In order to evaluate the availability of complex network structures with possible dependent failures Monte Carlo simulation can be used according to Wosinska et al (2009 Kulkarni et al (2010).…”

Section: Review Of Monte Carlo Simulation Application In Optical Netwmentioning

confidence: 99%

Estimation of Optical Access Network Bandwidth Demand Using Monte Carlo Simulation

Mikavica¹,

Radojicic²,

Kostic-Ljubisavljevic³

2015

IJTTE

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Continuous forecast of bandwidth demand in order to achieve a proper network planning and dimensioning is one of the key challenges that network operators need to deal with. The importance of this issue is highlighted with the necessity of proper decision making regarding capital investments and the permanent increase in traffic volume. Under-investing in network resources lead to low network performances and hence dissatisfied customers, while over-investing may cause over-dimensioned capacities which leads to lower resource utilization and opportunity losses. In that perspective, it is essential to determine whether current network capacities satisfy bandwidth requirements. If it does, determining relevant time period is of great significance. As the bandwidth demand increases by the development of new services, the existing broadband networks need to be upgraded. The growing bottleneck can be solved rolling out optical access network. These networks are characterized by greater bandwidth supply enhancement compared to bandwidth demand. That fact emphasizes the need of appropriate bandwidth forecast. This paper presents model for in optical access networks future bandwidth demand and network resource utilisation estimation. In order to appropriately address valid demand of all households in a given area, Monte Carlo simulation is applied.

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Network Resilience in Future Optical Networks

Cited by 11 publications

References 20 publications

Impact evaluation of physical length of shared risk link groups on optical network availability using Monte Carlo simulation

Impact evaluation of physical length of shared risk link groups on optical network availability using Monte Carlo simulation

Heuristic approach to availability calculation of path protected optical network based on the analysis of cable failures

Estimation of Optical Access Network Bandwidth Demand Using Monte Carlo Simulation

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