At backbone network planning, an important task is to identify the failures to get prepared for. Technically, a list of link sets, called Shared Risk Link Groups (SRLG), is defined. The observed reliability of network services strongly depends on how carefully this list was selected and whether it contains every high-risk failure event. Regional failures often cause the breakdown of multiple elements of the network, which are physically close to each other. In this article, we show that operators should prepare a network for only a small number of possible regional failure events. In particular, we give an approach to generate the list of SRLGs that hit every possible circular disk shaped disaster of a given radius r. We show that this list has O((n + x)ρr) SRLGs, where n is the number of nodes in the network and x is the number of link crossings, and ρ, is the maximal number of links that could be hit by a circular disaster of radius r. We give a fast polynomial algorithm to enumerate the list of SRLGs and show that its worst-case time complexity is asymptotically optimal under some practical restrictions. Finally, through extensive simulations, we show that this list in practice has a size of ≈ 1.2n.

Shared Risk Link Group (SRLG) is a failure the network is prepared for, which contains a set of links subject to a common risk of single failure. During planning a backbone network, the list of SRLGs must be defined very carefully, because leaving out one likely failure event will significantly degrade the observed reliability of the network. Regional failures are manifested at multiple locations of the network, which are physically close to each other. In this paper we show that operators should prepare a network for only a small number of possible regional failure events. In particular, we give a fast systematic approach to generate the list of SRLGs that cover every possible circular disk failure of a given radius r. We show that this list has O((n + x)σr) SRLGs, where n is the number of nodes in the network, x is the number of link crossings, and σris the maximal number of links that could be hit by a disk failure of radius r. Finally through extensive simulations we show that this list in practice has size of ≈ 1.2 n.

Network-wide local unambiguous failure localization (NL-UFL) has been demonstrated as an interesting scenario of monitoring trails (m-trails). It attempts to enable every node to autonomously localize any failure event in the network in a distributed and all-optical manner by inspecting a set of m-trails traversing through the node. This paper investigates the m-trail allocation problem under the NL-UFL scenario by taking each link and node failure event into consideration. Bound analysis is performed using combinatorial group testing (CGT) theory and this is followed by the introduction of a novel heuristic on general topologies. Extensive simulation is conducted to examine the proposed heuristic in terms of the required cover length and the number of m-trails to achieve NL-UFL.

This paper deals with fast node failure localization in optical networks with monitoring trails (m-trails). It is based on Network-wide local unambiguous failure localization, which enables every node to autonomously localize any single node failure in the network in a distributed and all-optical manner by inspecting the m-trails traversing through the node. A new and innovative heuristic algorithm is presented which is based on recursion and constrained matching algorithms in general graphs. Extensive simulation is conducted to examine the proposed heuristic in terms of the required cover length to achieve NL-UFL. In our experiments the new heuristic can reduce the computation time by 1000-10000 times compared to prior art.

Finding the correlation among Quality of Experience (QoE) for video, measured Quality of Service (QoS) parameters in the network, and objective video performance metrics is a challenging task. This paper provides some analysis results on this issue. Our motivation is that streaming media content gets dominant position in the global traffic mix within the next few years. With the evolution of personal devices, demand for High Definition (HD) resolution contents is dynamically increasing. Traversing real-time media across public packet-switched networks is a complex task, especially if quality of service should be sustained. The issue gets more complicated when the traffic is forwarded through heterogeneous infrastructures. Media content with various resolutions and bit rates show different sensitivity to transmission anomalies. Our paper investigates the correlation between subjective quality assessment (i.e., Mean Opinion Score, MOS evaluation), measured QoS parameters (packet loss, jitter) and objective video performance metrics (Video Quality Metric - VQM, Structural Similarity - SSIM, Peak Signal Noise Ratio - PSNR) in the context of real-time HD video streaming (i.e., IPTV and MobileTV). In twelve scenarios, packet-level perturbations were emulated in our laboratory testbed during the transmission of short video sequences with three different resolutions (480p, 720p and 1080p). Later the videos were evaluated using subjective and objective assessment methods.