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M.A.F. Muhammad Iqbal
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Networks are typically embedded in non-homogeneous areas and different parts/regions of the network may therefore be at risk from different types of disasters. This non-homogeneity leads to difficulties in protecting the network against (the risk of) disasters. Network operators need to be able to integrate predictions on possible future disaster events in the planning of their network operation. Especially the (future) availability of network links is crucial in configuring network connections, since the requested availability of network connections is stipulated in Service Level Agreements and must be satisfied, even under the threat of disasters. In this paper, we propose (1) a novel model to characterize disaster areas, with occurrences of each type of disaster represented by a temporal distribution (e.g., Poisson process), and (2) two metrics, namely a betweenness-centrality metric for network regions and an impact metric that indicates the magnitude of the threat posed by disasters within a network region during a given time period.
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Networks are typically embedded in non-homogeneous areas and different parts/regions of the network may therefore be at risk from different types of disasters. This non-homogeneity leads to difficulties in protecting the network against (the risk of) disasters. Network operators need to be able to integrate predictions on possible future disaster events in the planning of their network operation. Especially the (future) availability of network links is crucial in configuring network connections, since the requested availability of network connections is stipulated in Service Level Agreements and must be satisfied, even under the threat of disasters. In this paper, we propose (1) a novel model to characterize disaster areas, with occurrences of each type of disaster represented by a temporal distribution (e.g., Poisson process), and (2) two metrics, namely a betweenness-centrality metric for network regions and an impact metric that indicates the magnitude of the threat posed by disasters within a network region during a given time period.
Optical networks facilitate the configurations of high-speed network connections with tremendous bandwidth between the optical switches. Optical switches are interconnected by optical fibers that act as the mediums in which data are transferred using lightpaths. Due to the importance of optical networks to many societal needs, e.g., the Internet and banking services, network connections must be configured as efficient and reliable as possible. This thesis focus on two important research topics related to the management and survivability of network connections, namely routing and disaster awareness. Routing enables the assignment of the optimal end-to-end path to each network connection, while disaster awareness increases the preparedness of network operators in ensuring that network connections are protected against the adverse impacts of disasters. The first part of the thesis, namely Chapters 2, 3 and 4 relate to the topic of routing, specifically on technology-aware routing, impairment-aware routing and risk-averse routing. Technology-aware routing is required for establishing network connections across multi-domain networks with technology incompatibilities, impairment-aware routing enables network operators to establish network connections in the presence of transmission impairments, and risk-averse routing enables connections to be assigned with the safest paths (against failing due to disasters). The second part of the thesis, namely Chapters 4 and 5 relate to the topic of disaster awareness, by proposing approaches for ensuring the survivability of network connections in the risk of disasters, such as modeling of (spatiotemporal) disasters, identifying vulnerable connections, detecting spatially-close fiber segments, computing spatially-close intervals of spatially close fibers, and grouping spatially-close fibers efficiently. Though the thesis emphasizes on optical network use cases, the provided insights and contributions in each chapter are general enough to be extended for application in other network types as well.
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Optical networks facilitate the configurations of high-speed network connections with tremendous bandwidth between the optical switches. Optical switches are interconnected by optical fibers that act as the mediums in which data are transferred using lightpaths. Due to the importance of optical networks to many societal needs, e.g., the Internet and banking services, network connections must be configured as efficient and reliable as possible. This thesis focus on two important research topics related to the management and survivability of network connections, namely routing and disaster awareness. Routing enables the assignment of the optimal end-to-end path to each network connection, while disaster awareness increases the preparedness of network operators in ensuring that network connections are protected against the adverse impacts of disasters. The first part of the thesis, namely Chapters 2, 3 and 4 relate to the topic of routing, specifically on technology-aware routing, impairment-aware routing and risk-averse routing. Technology-aware routing is required for establishing network connections across multi-domain networks with technology incompatibilities, impairment-aware routing enables network operators to establish network connections in the presence of transmission impairments, and risk-averse routing enables connections to be assigned with the safest paths (against failing due to disasters). The second part of the thesis, namely Chapters 4 and 5 relate to the topic of disaster awareness, by proposing approaches for ensuring the survivability of network connections in the risk of disasters, such as modeling of (spatiotemporal) disasters, identifying vulnerable connections, detecting spatially-close fiber segments, computing spatially-close intervals of spatially close fibers, and grouping spatially-close fibers efficiently. Though the thesis emphasizes on optical network use cases, the provided insights and contributions in each chapter are general enough to be extended for application in other network types as well.
A cyber-physical system is often designed as a network in which critical information is transmitted. However, network links may fail, possibly as the result of a disaster. Disasters tend to display spatiotemporal characteristics, and consequently link availabilities may vary in time. Yet, the requested connection availability of traffic must be satisfied at all times, even under disasters. In this paper, we argue that often the spatiotemporal impact of disasters can be predicted, such that suitable actions can be taken, before the disaster manifests, to ensure the availability of connections. Our main contributions are three-fold: (1) we propose a generic grid-based model to represent the risk profile of a network area and relate the risk profile to the availability of links and connections, (2) we propose a polynomial-time algorithm to identify connections that are vulnerable to an emerging disaster risk, and (3) we consider the predicted spatiotemporal disaster impact, and propose a polynomial-time algorithm based on an auxiliary graph to find the most risk-averse path under a time constraint.
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A cyber-physical system is often designed as a network in which critical information is transmitted. However, network links may fail, possibly as the result of a disaster. Disasters tend to display spatiotemporal characteristics, and consequently link availabilities may vary in time. Yet, the requested connection availability of traffic must be satisfied at all times, even under disasters. In this paper, we argue that often the spatiotemporal impact of disasters can be predicted, such that suitable actions can be taken, before the disaster manifests, to ensure the availability of connections. Our main contributions are three-fold: (1) we propose a generic grid-based model to represent the risk profile of a network area and relate the risk profile to the availability of links and connections, (2) we propose a polynomial-time algorithm to identify connections that are vulnerable to an emerging disaster risk, and (3) we consider the predicted spatiotemporal disaster impact, and propose a polynomial-time algorithm based on an auxiliary graph to find the most risk-averse path under a time constraint.
Spatially-close network fibers have a significant chance of failing simultaneously in the event of man-made or natural disasters within their geographic area. Network operators are interested in the proper detection and grouping of any existing spatially-close fiber segments, to avoid service disruptions due to simultaneous fiber failures. Moreover, spatially-close fibers can further be differentiated by computing the intervals over which they are spatially close. In this paper, we propose (1) polynomial-time algorithms for detecting all the spatially-close fiber segments of different fibers, (2) a polynomial-time algorithm for finding the spatially-close intervals of a fiber to a set of other fibers, and (3) a fast exact algorithm for grouping spatially-close fibers using the minimum number of distinct risk groups. All of our algorithms have a fast running time when simulated on three real-world network topologies.
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Spatially-close network fibers have a significant chance of failing simultaneously in the event of man-made or natural disasters within their geographic area. Network operators are interested in the proper detection and grouping of any existing spatially-close fiber segments, to avoid service disruptions due to simultaneous fiber failures. Moreover, spatially-close fibers can further be differentiated by computing the intervals over which they are spatially close. In this paper, we propose (1) polynomial-time algorithms for detecting all the spatially-close fiber segments of different fibers, (2) a polynomial-time algorithm for finding the spatially-close intervals of a fiber to a set of other fibers, and (3) a fast exact algorithm for grouping spatially-close fibers using the minimum number of distinct risk groups. All of our algorithms have a fast running time when simulated on three real-world network topologies.
The past century of telecommunications has shown that failures in networks are prevalent. Failure recovery processes are therefore needed. Failure recovery is mainly influenced by (1) detection of the failure, and (2) circumvention of the detected failure. However, especially in SDNs where controllers recompute network state reactively, this leads to high delays. Hence, next to primary rules, backup rules should be installed in the switches to quickly detour traffic once a failure occurs. In this work, we propose algorithms for computing an all-to-all primary and backup network forwarding configuration that is capable of circumventing link and node failures. After initial recovery, we recompute network configuration to guarantee protection from future failures. Our algorithms use packet-labeling to guarantee correct and shortest detour forwarding and are able to discriminate between link and node failures. The computational complexity of our solution is comparable to that of all-to-all shortest paths computations. Our experimental evaluation shows that network configuration complexity decreases significantly compared to classic disjoint paths computations. Finally, we provide a proof-of-concept OpenFlow controller in which our proposed configuration is implemented, demonstrating that it readily can be applied in production networks.
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The past century of telecommunications has shown that failures in networks are prevalent. Failure recovery processes are therefore needed. Failure recovery is mainly influenced by (1) detection of the failure, and (2) circumvention of the detected failure. However, especially in SDNs where controllers recompute network state reactively, this leads to high delays. Hence, next to primary rules, backup rules should be installed in the switches to quickly detour traffic once a failure occurs. In this work, we propose algorithms for computing an all-to-all primary and backup network forwarding configuration that is capable of circumventing link and node failures. After initial recovery, we recompute network configuration to guarantee protection from future failures. Our algorithms use packet-labeling to guarantee correct and shortest detour forwarding and are able to discriminate between link and node failures. The computational complexity of our solution is comparable to that of all-to-all shortest paths computations. Our experimental evaluation shows that network configuration complexity decreases significantly compared to classic disjoint paths computations. Finally, we provide a proof-of-concept OpenFlow controller in which our proposed configuration is implemented, demonstrating that it readily can be applied in production networks.
Transporting Big Data requires high-speed connections between end-hosts. Research and educational networks typically are state-of-the-art networks that facilitate such high-speed user-created network connections, possibly spanning multiple domains. However, there are many different high-speed optical data plane standards and implementations, and vendors do not always create compatible data plane implementations. These technology incompatibilities may prevent direct communication between domains and therefore complicate the configuration of connections. However, some domains may have adaptation capabilities that can lift the technology incompatibility constraint in establishing paths between incompatible domains. Within this context, we address two problems, namely: (1) how to model the technology incompatibilities of multi-domain multi-layer networks, and (2) how to optimally establish paths in such networks. We introduce the inclusion of the information of the supported technologies and adaptation capabilities of each domain and inter-domain link in our model. We subsequently propose technology-aware routing algorithms for finding the shortest feasible path in a multi-domain multi-layer network.
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Transporting Big Data requires high-speed connections between end-hosts. Research and educational networks typically are state-of-the-art networks that facilitate such high-speed user-created network connections, possibly spanning multiple domains. However, there are many different high-speed optical data plane standards and implementations, and vendors do not always create compatible data plane implementations. These technology incompatibilities may prevent direct communication between domains and therefore complicate the configuration of connections. However, some domains may have adaptation capabilities that can lift the technology incompatibility constraint in establishing paths between incompatible domains. Within this context, we address two problems, namely: (1) how to model the technology incompatibilities of multi-domain multi-layer networks, and (2) how to optimally establish paths in such networks. We introduce the inclusion of the information of the supported technologies and adaptation capabilities of each domain and inter-domain link in our model. We subsequently propose technology-aware routing algorithms for finding the shortest feasible path in a multi-domain multi-layer network.