Dynamic provisioning of availability-constrained optical circuits in the presence of optical node failures

Pandi, Z.; Tacca, Marco; Fumagalli, Andrea; Wosinska, Lena

doi:10.1109/jlt.2006.879505

Cited by 16 publications

(9 citation statements)

References 17 publications

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“…We also show that ignoring the dependence between link failures can lead to suboptimal solutions of our network design problem. We tested our model over the Italian WDM backbone network, extracted from [18], where the marginal failure probabilities p e are computed as a function of the length of each link. Inspired by [8], we introduced a correlation using the distance d ef between the midpoint of a pair of links e and f , given by ρ ef = exp(−θ d ef ) rounded to the first decimal and using θ = 2.…”

Section: Computational Examplementioning

confidence: 99%

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Topological optimization of reliable networks under dependent failures

Barrera

Cancela

Moreno

2015

Operations Research Letters

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Section: Computational Examplementioning

confidence: 99%

“…maximum allowable, keeping the same marginal failure probabilities for all links. We repeat this procedure increasing correlation between links (0, 2) and (0, 3), links (6,8) and (3,7), and links (12,14) and (14,18). We denote these instances as I2, I3 and I4, respectively.…”

Section: Computational Examplementioning

confidence: 99%

Topological optimization of reliable networks under dependent failures

Barrera

Cancela

Moreno

2015

Operations Research Letters

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“…The mean time to failure (MTTF) and mean time to repair (MTTR) values of each component can be obtained from the literature [9]- [11]. Note that the link failure rate is considered to be directly proportional to the length of the fiber link, and the OXC node failure rate is proportional to the degree of the node, whereas the mean repair time of nodes and links are independent of the links' lengths and nodes' degrees, respectively [12]. In this paper, since the probability that three components have overlapped (in time) failures is small enough to be ignored, 2 the assumption that at most two components fail at the same time is made.…”

Section: Failure Modelmentioning

confidence: 99%

“…The connection source and destination nodes are randomly (uniform distribution) selected. According to [9]- [12], the nodes' (transmitter, receiver, OXC node, and OEO converter) MTTR is 6 hours, and the links' MTTR is 12 hours. The failure rate in FIT (1 FIT = 1 failure in 10 9 hours) is shown in Table I.…”

Section: A Simulation Settingsmentioning

confidence: 99%

QoT- and SLA-Aware Survivable Resource Allocation in Translucent Optical Networks

Zhao

Subramaniam

2015

2015 IEEE Global Communications Conference (GLOBECOM)

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Survivability is a critical issue in highcapacity wavelength division multiplexing based optical networks, since even a disruption for a very short time could result in the loss of a large amount of data. Each accepted connection request brings revenue to the network. On the other hand, a service level agreement (SLA) requirement (e.g., 99.9% uptime in terms of availability) is associated with a connection, and a penalty is paid if the requirement is violated. In addition, physical impairments degrade the quality of signals as they traverse along lightpaths. In this paper, the survivable routing and wavelength assignment problem is studied for dynamic traffic in translucent optical networks considering randomly occurring failures of optical fibers and nodes, so that the quality of transmission (QoT) requirement of each connection is satisfied, and the network-level performance metric of total profit is maximized. Two heuristics are developed -the first one aims to allocate resources to each connection to minimize the expected penalty; while the other heuristic prefers to allocate the minimum possible resources to each connection. Simulation results are presented to demonstrate their effectiveness.

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“…Dynamic ones must establish the working/backup lightpaths on demand and thus, there is not much time to compute the lightpath allocation. For that reason, heuristics are the most used approach to solve the problem, as in [10,13,16,20]. In a static scenario instead, the set of connections to establish are known a priori and there is enough time to run optimization techniques such as integer linear programming (ILP) models.…”

Section: Introductionmentioning

confidence: 99%

Availability‐driven optimal design of shared path protection in WDM networks

2016

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2016. Availability-driven optimal design of shared path protection in WDM networks. Networks, 68(3), pp. 224-237. ISSN 0028-3045 [Article]Abstract Availability, defined as the fraction of time a network service is operative, is a key network service parameter.Dedicated protection increases availability but also the cost. Shared protection instead decreases the cost, but also the availability.In this paper, we formulate and solve an integer linear programming (ILP) model for the problem of minimizing the backup resources required by a shared-protected static optical network whilst guaranteeing an availability target per connection. The main research challenge is dealing with the non-linear expression for the availability constraint.Taking the working/backup routes and the availability requirements as input data, the ILP model identifies the set of connections sharing backup resources in any given network link.We also propose a greedy heuristic to solve large instances in much shorter time than the ILP model with low levels of relative error (2.49% average error in the instances studied) and modify the ILP model to evaluate the impact of wavelength conversion.Results show that considering availability requirements can lead up to 56.4% higher backup resource requirements than not considering them at all, highlighting the importance of availability requirements in budget estimation.

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Dynamic provisioning of availability-constrained optical circuits in the presence of optical node failures

Cited by 16 publications

References 17 publications

Topological optimization of reliable networks under dependent failures

Topological optimization of reliable networks under dependent failures

QoT- and SLA-Aware Survivable Resource Allocation in Translucent Optical Networks

Availability‐driven optimal design of shared path protection in WDM networks

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