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The surge of video traffic is a challenge for service providers that need to maximize Quality of Experience (QoE) while optimizing the cost of their infrastructure. In this paper, we address the problem of routing multiple HTTP-based Adaptive Streaming (HAS) sessions to maximize QoE. We first design a QoS-QoE model incorporating different QoE metrics which is able to learn online network variations and predict their impact on representative classes of adaptation logic, video motion and client resolution. Different QoE metrics are then combined into a QoE score based on ITU-T Rec. P.1202.2. This rich score is used to formulate the routing problem. We show that, even with a piece-wise linear QoE function in the objective, the routing problem without controlled rate allocation is non-linear. We therefore express a routing-plus-rate allocation problem and make it scalable with a dual subgradient approach based on Lagrangian relaxation where subproblems select a single path for each request with a trivial search, thereby connecting explicitly QoE, QoE and HAS bitrate. We show with ns-3 simulations that our algorithm provides values for HAS QoE metrics (quality, rebufferings, variation) equivalent to MILP and better than QoS-based approaches.

Adaptive streaming addresses the increasing and heterogeneous demand of multimedia content over the Internet by offering several encoded versions for each video sequence. Each version (or representation) is characterized by a resolution and a bit rate, and it is aimed at a specific set of users, like TV or mobile phone clients. While most existing works on adaptive streaming deal with effective playout-buffer control strategies on the client side, in this article we take a providers' perspective and propose solutions to improve user satisfaction by optimizing the set of available representations. We formulate an integer linear program that maximizes users' average satisfaction, taking into account network dynamics, type of video content, and user population characteristics. The solution of the optimization is a set of encoding parameters corresponding to the representations set that maximizes user satisfaction. We evaluate this solution by simulating multiple adaptive streaming sessions characterized by realistic network statistics, showing that the proposed solution outperforms commonly used vendor recommendations, in terms of user satisfaction but also in terms of fairness and outage probability. The simulation results show that video content information as well as network constraints and users' statistics play a crucial role in selecting proper encoding parameters to provide fairness among users and to reduce network resource usage. We finally propose a few theoretical guidelines that can be used, in realistic settings, to choose the encoding parameters based on the user characteristics, the network capacity and the type of video content.

International audience; 5G services and 4K will stress even more the future access/aggregation networks, where video contents have already become the main traffic contributor. The deployment in the convergent access of local micro data-centers (DCs) nodes is one promising approach to successfully manage this challenge. These nodes will be responsible for switching enormous amounts of traffic and simultaneously performing heavy CPU tasks (such as video or radio base band processing). Only a flexible management of these nodes based on NFV, SDN and data analytics will enable to meet these tasks. In this paper, we present a consistent and complete cost model collecting main trade-offs between energy savings and CPU processing suitable to be used in such a flexible management framework.

This paper investigates the merits of the SR–VTCA (stable routing–virtual topology capacity adjustment) approach as a mechanism to find a beneficial trade-off between network stability and reduction in capital expenditures (CapEx). These are two main objectives for the entities that own the optical infrastructure, such as network operators (NOs), and those also acting as Internet service providers (ISPs). The SR–VTCA scheme is a novel approach to adapt transparent optical networks to time-varying traffic by adjusting the number of lightpaths between node pairs, while keeping the IP routing unchanged. Lightpath bundling (LB) and anycast (AS) switching are combined in SR–VTCA operation to advertise lightpath additions/removals to the IP layer as mere adjustments (increments or decrements) in the capacity, allowing to keep the IP routing stable, and thus, simplifying control plane operations. On the contrary, a fully-reconfigurable (FR) network design, where IP routing can be also modified, would increase the burden in the control plane, but at a higher CapEx reduction, since the optical infrastructure is used more efficiently. In this work, we investigate the CapEx overprovision introduced by SR–VTCA with respect to a FR scheme. In order to do this, SR–VTCA planning problem is first modeled as a MILP formulation. A heuristic procedure based on traffic domination is then proposed to solve large instances of the problem. Exhaustive experiments are conducted comparing the SR–VTCA solutions obtained by the aforementioned MILP and heuristic proposal with solutions found by other optimization methods presented in the literature to solve the FR planning problem. Finally, the results show that SR–VTCA can achieve similar results to the FR case in terms of CapEx reduction, while a huge number of IP reroutings are saved by maintaining IP stability. Thus, SR–VTCA provides an advantageous balance between CapEx overprovisioning and the control plane overhead associated with IP rerouting.

The evolution of novel access networks is dominated by two major changes: first, an increasing convergence of fixed optical and mobile wireless access networks (driven by the industry interested in mutualizing infrastructure); and secondly, a surge in video traffic (expected to represent 80 percent of all consumer Internet traffic in 2019). This motivates the introduction of video delivery optimization in the design of the novel fixed-mobile convergent access to obtain more energy efficient networks with better Quality of Experience (QoE) perceived by the end-user. In this paper, we study how the joint optimization of video adaptive streaming decisions (like the video bit rate selection) and access resource allocations (like optical and radio equipment placement) could yield to maximize the QoE at the same time as power consumption is reduced.

International audience; Transport protocols that can exploit multiple paths, especially MPTCP, do not match the requirements of video streaming: high average transmission delay, too strict reliability, and frequent head-of-line phenomenons resulting in abrupt throughput drops. In this paper, we address this mismatch by introducing a cross-layer scheduler, which leverages information from both application and transport layers to reorder the transmission of data and prioritize the most significant parts of the video. Our objective is to maximize the amount of video data that is received in time at the client. We show that current technologies enable the implementation of this cross-layer scheduler without much overhead. We then demonstrate the validity of our approach by studying the performance of an optimal cross-layer scheduler. The gap between the performance of the traditional scheduler versus the optimal scheduler justifies our motivation to implement a cross-layer scheduler in practice. We propose one implementation with basic cross-layer awareness. To evaluate the performance of our proposal, we aggregate a dataset of real MPTCP sessions and we use video stream encoded with HEVC. Our results show that our cross-layer proposal outperforms the traditional scheduler. Viewers not only benefit from the inherent advantages of using MPTCP (such as a better resilience to path failure) but also get a better QoE compared to the traditional scheduler.

In translucent optical networks, the physical layer impairments degrading the optical signal are considered in the network planning. In this paper, we investigate the offline problem of routing and wavelength assignment (RWA) and regenerator placement (RP) in translucent networks, minimizing the lightpath blocking and regenerator equipment cost. We address two variants of the problem, which correspond to two different types of quality of transmission (QoT) estimators, called linear and nonlinear. In a nonlinear QoT, nonlinear impairments like crosstalk or cross-phase modulation, which account for the interferences from neighboring lightpaths in the network are explicitly computed. Then, the QoT estimated for a lightpath depends on the routes of other lightpaths in the network. In the linear QoT, the effects of the nonlinear impairments are overestimated and accumulated to the rest of the impairments in the QoT calculation. As a result, the QoT estimation of a lightpath solely depends on its route. For the linear case, we formulate an optimal integer linear programming model of the problem, to the best of the authors' knowledge, for the first time in the literature. Its simplicity allows us to test it for small- and medium-size networks. Also, we propose two heuristic methods, namely, lightpath segmentation and three-step, and a tight lower bound for the regenerator equipment cost. For the nonlinear QoT case, we propose a new heuristic called iterative RP (IRP). Both the IRP and three-step algorithms are designed to guarantee that no lightpath blocking is produced by signal degradation. This is a relevant difference with respect to earlier proposals. The performance and the scalability of our proposals are then investigated by carrying out extensive tests. Results reveal that the solutions obtained by the heuristic algorithms are optimal or close to optimal, and outperform the earlier proposals in the literature.

International audience; Adaptive streaming addresses the increasing and heterogenous demand of multimedia content over the Internet by offering several streams for each video. Each stream has a different resolution and bit rate, aimed at a specific set of users, e.g., TV, mobile phone. While most existing works on adaptive streaming deal with optimal playout-control strategies at the client side, in this paper we concentrate on the providers' side, showing how to improve user satisfaction by optimizing the encoding parameters. We formulate an integer linear program that maximizes users' average satisfaction, taking into account the network characteristics, the type of video content, and the user population. The solution of the optimization is a set of encoding parameters that outperforms commonly used vendor recommendations, in terms of user satisfaction and total delivery cost. Results show that video content information as well as network constraints and users' statistics play a crucial role in selecting proper encoding parameters to provide fairness among users and reduce network usage. By combining patterns common to several representative cases, we propose a few practical guidelines that can be used to choose the encoding parameters based on the user base characteristics, the network capacity and the type of video content.

New time-slotted subwavelength switching paradigms have been proposed as promising solutions to exploit the subwavelength bandwidth overcoming many limitations of traditional optical burst switching (OBS) schemes. Since these new paradigms are based on fix-sized bursts transmitted during time slots, the efficient assembly of IP packets into optical bursts is the first mile stone to reach in the way of the real deployment of all-optical transport networks based on them. Then, in this paper, we propose alternate architectures for implementing such networks and we assess them by studying the efficiency of several burst assembly policies. The study is performed by analyzing real internet traffic extracted from the national transport network of Orange. This is the first time to our knowledge that such study is performed. In this paper we identify the architectures that are viable, in terms of assembly process, for the deployment of such new paradigms in an all-optical core network.

Optical network operators face the challenge of upgrading the WDM network capacity to adapt to estimated traffic growths. Network upgrades are commonly carried out in scheduled intervals (i.e. every six months), using traffic forecasts. The uncertainty in the forecasts is a major issue in the capacity upgrading process. If it is not handled appropriately, the network is exposed to service degradation caused by an unexpected traffic progression. Despite of its relevance, the effects of uncertainty in the forecasts is a factor that has not been well studied in the literature. In this paper, we apply the robust optimization paradigm to incorporate this uncertainty into the network upgrade problem. Under this robust network upgrade model, we can dimension the network by tuning the tradeoff between network cost and robustness level. This proposal is applied to a case study where several experiments are conducted comparing different levels of robustness and different WDM technologies, namely pure 10G (single line rate), pure 40G SLR, pure 100G SLR and 10/40/100G MLR (mixed line rate).

Today’s Transparent Optical Networks (TONs) are highly vulnerable to various physical-layer attacks, such as high-power jamming, which can cause severe service disruption or even service denial. The transparency of TONs enables certain attacks to propagate through the network, not only increasing their damage proportions, but also making source identification and attack localization more difficult. High-power jamming attacks causing in-band crosstalk in switches are amongst the most malicious of such attacks. In this paper, we propose a wavelength assignment scheme to reduce their damage assuming limited attack propagation capabilities. This complements our previous work in Furdek et al. (M. Furdek, N. Skorin-Kapov, M. Grbac, Attack-aware wavelength assignment for localization of in-band crosstalk attack propagation, IEEE/OSA Journal of Optical Communications and Networking 2 (11) (2010) 1000–1009) where we investigated infinite jamming attack propagation to find an upper bound on the network vulnerability to such attacks. Here, we consider a more realistic scenario where crosstalk attacks can spread only via primary and/or secondary attackers and define new objective criteria for wavelength assignment, called the PAR (Primary Attack Radius) and SAR (Secondary Attack Radius), accordingly. We formulate the problem variants as integer linear programs (ILPs) with the objectives of minimizing the PAR and SAR values. Due to the intractability of the ILP formulations, for larger instances we propose GRASP (Greedy Randomized Adaptive Search Procedure) heuristic algorithms to find suboptimal solutions in reasonable time. Results show that these approaches can obtain solutions using the same number of wavelengths as classical wavelength assignment, while significantly reducing jamming attack damage proportions in optical networks.

This paper addresses offline virtual topology design in transparent optical networks under given periodic traffic. We call this planning problem ldquoScheduled Virtual Topology Designrdquo. Two problem variants are considered: for a network based on non-reconfigurable equipment and for a network based on reconfigurable equipment. Two MILP (Mixed Integer Linear Program) formulations are proposed, one for each alternative. The number of transceivers in the network is the selected cost figure to minimize. Tests are performed to evaluate the benefits of using reconfigurable equipment under different traffic conditions and network sizes. The reduction in the number of transceivers obtained by allowing temporal variations in the virtual topology seems low in all cases, indicating that using reconfigurable equipment may not be cost-effective for periodic traffic. The work described in this paper was carried out with the support of the BONE-project ("Building the Future Optical Network in Europe”), a Network of Excellence funded by the European Commission through the 7th ICT-Framework Programme, the support of the MEC Spanish project TEC2007-67966-01/TCM CONPARTE-1, the support of the Fundación Séneca project FORMA 00002/CS/08, and developed in the framework of "Programa de Ayudas a Grupos de Excelencia de la Región de Murcia, de la Fundación Séneca (Plan Regional de Ciencia y Tecnología 2007/2010)”.