Protocols engineering of IP/MPLS networks are constantly improving with new separated features and new resilience mechanisms. In the transportation of audiovisual signals domain we must compose with multicast protocols which are designed from other scientific developments. This audiovisual traffic due to his non springy nature presents a very huge sensitivity to network recovery after a failure and these effects can be amplified by end devices (encoding, decoding and MPEG IP encapsulation). In this way when we choose between engineering solutions the unique criterion of availability is not enough, we must complete by an impact analysis on the service made by the network resilience technics. In this paper, we propose a first approach to analyze the behavior of different protocols engineering to improve selection. We propose using Bayesian networks to compare performance on different criteria and we will illustrate with two engineering models. The results focus on a real improvement of availability by choosing the adapted engineering solution.

In content delivery network, Quality of Experience (QoE) provides two major performance indicators that are availability and continuity of service. As a consequence, network robustness has become a major concern for network operators. TDF operates a traditional transport network for video and audio transport. Any failure on the network causes a recovery time implying loss and an impact in the content viewing. This illustrate that service continuity is a direct consequence of network availability. This work aims to propose a Software Defined Networking (SDN) architecture [1] in which the controller uses its knowledge of the performance and bandwidth allocation to compute redundant disjoint paths. Two maximally linkindependent paths carrying the same stream over the network are deployed. When a failure occurs, at least one of the paths is still active, eliminating any discontinuity on the content viewing. This paper is focused on the Path Computation Element, which is based on Suurballe-Tarjan algorithm [2].

In Content Delivery Networks (CDN), Quality of Experience (QoE) provides two major performance indicators that are availability and continuity of service. As a consequence, network robustness has become a major concern for network operators. TDF operates a traditional transport network for video and audio transport through multicast. Any failure on the network causes a recovery time implying loss and an impact in the content viewing. This illustrate that service continuity is a direct consequence of network availability. This work aims to propose a Software Defined Networking (SDN) architecture [1] in which a central controller uses its knowledge of the performance and bandwidth allocation to compute redundant disjoint multicast trees. Two maximally independent trees carrying the same stream over the network are deployed. When a failure occurs, at least one of the trees is still active, eliminating any discontinuity on the content viewing. This paper is focused on the Path Computation Element (PCE), which is based on previous works and the Suurballe-Tarjan algorithm [2]. Two algorithms are presented in this paper, which both fulfill the requirement of the architecture.

This research examines the factors that influence the adoption of new energy-saving technologies among U.S. manufacturing plants and explores their potential impact on aggregate energy efficiency. We conduct this analysis using two models: a conventional diffusion model and a stand-alone model of new technology adoption we develop in this paper. The latter model allows us to compute effects on aggregate efficiency based solely on adoption data.Our estimates of diffusion speed find a remarkable consistency across technologies and industries. We estimate that half the population of users adopts a new technology in roughly seven years, regardless of industry or technology. Based on a 959oconfidence interval, we estimate that at ten percent rise in energy prices would, at most, decrease the average adoption time by about one year. The obvious problem with this model is that while it explains how the diffusion of individual technologies maybe sped up, it does not address the process of developing these new technologies. In a model focused on individual technologies, this process dominates long-run behavior.Focusing instead on adoption of any technology rather than specific ones, we identify two statistically significant predictors of adoption: profitability and energy prices. Based on a 9570 confidence interval, these variables at most raise the rate of adoption by 370and 10YO, respectively, when each variable is increased by 10$ZO. In our adoption model, these increases directly translate into changes in the growth rate of energy efficiency. With an aggregate growth rate of roughly"19?0, this would indicate an increase to at most 1.1!ZO. At this rate, energy use will have fallen by 4370 instead of 39?Z0 after fifty years-a relatively small gain for fifty years of higher energy prices.From these results we draw two important policy conclusions. Since we find that profitability has a significant effect on adoption, it will be important to consider the impact of public policy on firm revenue. For example, policies that immediately raise prices without allowing firms to anticipate those changes may lead to declining adoption rates if their financial health is adversely affected. Second and more significantly, these results put a damper on the idea that technology can substantially reduce the trade-off between economic costs and environmental protection. Since energy efficiency improvements currently progress at only 1% per year, even a large increase in this growth rate will take many years to translate into significant reductions in aggregate efficiency. The only possibility for significant technology effects will be if public policy can encourage the development of large, non-incremental technologies-unlike the small, incremental technologies considered in this paper.

For audiovisual network operators, end-users satisfaction is a major issue. This is the case for TDF who operates a nationwide network in France whose main purpose is to carry Digital Terrestrial Television (DTT) streams. Such audiovisual content is forwarded through multicast real-time streams which require continuity of service. Therefore, the main goal of this work is to define a new architecture to prevent impact during network healing time. The proposed architecture aims to use a pair of redundant multicast trees, and ensure their seamless resiliency. This architecture called "Seamless Multicast" takes advantage of the networkend equipment's ability to receive and combine two identical streams, complete or not. The main contribution of this paper is the development and evaluation of an algorithm for the computation of a pair of multicast trees and the associated hitless deployment scheme. Implementation requires an Software-Defined Networking (SDN) architecture, in which performance knowledge and bandwidth management are centralized in a controller. A proof of concept controller has been used for validation of the architecture's global behaviour using a virtualized environment in multiple scenarios.