Routing post-disaster traffic floods in optical core networks

Nasralla, Zaid H.; El-Gorashi, Taisir E. H.; Musa, Mohamed O. I.; Elmirghani, Jaafar M. H.

doi:10.1109/ondm.2016.7494055

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…Post-disaster traffic has a higher influence on the QoT of light paths in all-optical networks and failure of few seconds may cause massive losses both in terms of data volumes and decline of revenue. Nasralla et al in Reference [123] proposed a MILP to handle capacity exhaustion problem due to post-disaster traffic floods. Authors evaluated the network blocking for single node flooding with different traffic flood sizes.…”

Section: Congestion-aware Routing and Wavelength Assignmentmentioning

confidence: 99%

“…Capacity exhaustion has become an acute problem due to post-disaster traffic floods as indicated in Reference [123]. To deal with the critical demand of ICT services during traffic fluctuations and upsurges, Least-Congested Distributed Light path Allocation (LC-DLA), as proposed in Reference [119] for large-scale networks, should be studied to mitigate capacity exhaustion problem while considering a huge number of connection requests and heavy traffic loads.…”

Section: Challenges In Disaster-resilient Optical Network Survivabilitymentioning

confidence: 99%

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Disaster-Resilient Optical Network Survivability: A Comprehensive Survey

et al. 2018

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Network survivability endeavors to ensure the uninterrupted provisioning of services by the network operators in case of a disaster event. Studies and news reports show that network failures caused by physical attacks and natural disasters have significant impacts on the optical networks. Such network failures may lead to a section of a network to cease to function, resulting in non-availability of services and may increase the congestion within the rest of the network. Therefore, fault tolerant and disaster-resilient optical networks have grasped the attention of the research community and have been a critical concern in network studies during the last decade. Several studies on protection and restoration techniques have been conducted to address the network component failures. This study reviews related previous research studies to critically discuss the issues regarding protection, restoration, cascading failures, disaster-based failures, and congestion-aware routing. We have also focused on the problem of simultaneous cascading failures (which may disturb the data traffic within a layer or disrupt the services at upper layers) along with their mitigating techniques, and disaster-aware network survivability. Since traffic floods and network congestion are pertinent problems, they have therefore been discussed in a separate section. In the end, we have highlighted some open issues in the disaster-resilient network survivability for research challenges and discussed them along with their possible solutions.

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Section: Congestion-aware Routing and Wavelength Assignmentmentioning

confidence: 99%

Section: Challenges In Disaster-resilient Optical Network Survivabilitymentioning

confidence: 99%

Disaster-Resilient Optical Network Survivability: A Comprehensive Survey

et al. 2018

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“…Nonetheless, multiple anomalies can be caused under special circumstances, e.g., when a disaster affects the network [16]. In such scenarios, several ODs leaving from a common origin node (o→(M⊂R)) or arriving to a common destination node ((N⊂R)→d) can be produced, where M represents the set of destinations from o and N is the set of origins to d. Here, reconfiguring the virtual network after an individual OD traffic anomaly is detected can result in both, an intolerable number of virtual network reconfiguration and traffic losses and in a far from optimal network configuration in terms of resource utilization.…”

Section: Od Traffic Anomaliesmentioning

confidence: 99%

Distributing data analytics for efficient multiple traffic anomalies detection

Vela

Ruiz

Velasco

2017

Computer Communications

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Traffic anomalies can create network congestion, so its prompt and accurate detection would allow network operators to make decisions to guarantee the network performance avoiding services to experience any perturbation. In this paper, we focus on origin–destination (OD) traffic anomalies; to efficiently detect those, we study two different anomaly detection methods based on data analytics and combine them with three monitoring strategies. In view of the short monitoring period needed to reduce anomaly detection, which entails large amount of monitoring data to be collected and analyzed in a centralized repository, we propose bringing data analytics to the network nodes to efficiently detect traffic anomalies, while keeping traffic estimation centralized. Once an OD traffic anomaly is detected, a network reconfiguration can be triggered to adapt the network to the new traffic conditions. However, an external event might cause multiple related traffic anomalies. In the case of triggering a network reconfiguration just after one traffic anomaly is detected, some Key Performance Indicators (KPI) such as the number of network reconfigurations and the total reconfiguration time would be unnecessarily high. In light of that, we propose the Anomaly and Network Reconfiguration (ALCOR) method to anticipate whether other ODs are anomalous after detecting one anomalous OD pair. Exhaustive simulation results on a realistic network scenario show that the monitoring period should be as low as possible (e.g., 1 min) to keep anomaly detection times low, which clearly motivates to place traffic anomaly detection function in the network nodes. In the case of multiple anomalies, results show that ALCOR can significantly improve KPIs such as the number of network reconfigurations, total reconfiguration time, as well as traffic losses.Peer ReviewedPostprint (author's final draft

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“…In previous work [6], we discussed post-disasters traffic floods, which is mainly caused by the enormous amount of data traffic. These floods contains social media traffic, VoIP, user generated videos.…”

Section: Introductionmentioning

confidence: 99%

“…In our previous work [6], we developed a Mixed Integer Linear Programming (MILP) model to simulate the optical core network performance during single node flooding with different flood sizes. Then we studied the four mitigation approaches to serve more floods by exploiting link excess capacity, rerouting, selective traffic filtering and differentiated-services.…”

Section: Introductionmentioning

confidence: 99%