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Bernard Cousin

Bio: Bernard Cousin is an academic researcher from University of Rennes. The author has contributed to research in topics: Multicast & Source-specific multicast. The author has an hindex of 20, co-authored 136 publications receiving 1239 citations. Previous affiliations of Bernard Cousin include Institut de Recherche en Informatique et Systèmes Aléatoires & University of Rennes 1.


Papers
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Journal ArticleDOI
TL;DR: The Architectural Solutions for Services Enhancing digital Television (ASSET) project as discussed by the authors aims to overcome the limitations of custom specific implementations in a digital system for TV content creation, such as the misfit of interfaces between software layers, proprietary application program interfaces (APIs) of equipment from different vendors, and the lack of a generalized middleware for multimedia content management with openly defined interfaces.
Abstract: Applications and products currently available for the broadcasting market are vertically integrated or proprietary. They are based on components requiring specific and costly development to interoperate and typically rely on a single manufacturer or system integrator. Hence, they are not fully compliant with broadcasters' requirements. Architectural Solutions for Services Enhancing digital Television (ASSET) is a European-funded project. Its main goal is to overcome the limitations of custom specific implementations in a digital system for TV content creation. These limitations are generally due to the misfit of interfaces between software layers, proprietary application program interfaces (APIs) of equipment from different vendors, and the lack of a generalized middleware for multimedia content management with openly defined interfaces. Besides presenting the ASSET-proposed architecture and concepts, this paper describes the prototype under development to test and demonstrate the project proposals.

2 citations

Journal ArticleDOI
TL;DR: This paper exposed a distributed architecture of controllers and then a module based on an adaptive load balancing algorithm that is fault tolerant and fluctuates controller loads that shows a significant gain in efficiency of the solution.

2 citations

Proceedings ArticleDOI
18 Dec 2009
TL;DR: The routing and wavelength assignment (RWA) problem for multipoint-to-point communications in all-optical wavelength division multiplexing (WDM) networks is investigated and two efficient algorithms are proposed, namely Reverse Shortest Path Tree routing (RSPT) and k-Bounded Edge Disjoint Path routing (EDPR).
Abstract: The routing and wavelength assignment (RWA) problem for multipoint-to-point communications in all-optical wavelength division multiplexing (WDM) networks is investigated in this paper. Two efficient algorithms, namely Reverse Shortest Path Tree routing (RSPT) and k-Bounded Edge Disjoint Path routing (EDPR), are proposed. The problem of minimizing the total cost while establishing a multipoint-to-point session can be solved by RSPT algorithm in polynomial time. Nevertheless, EDPR algorithm produces a significant reduction in the maximum number of wavelengths required per link (i.e., the link stress) by a multipoint-to-point session. Simulations demonstrate the efficiencies of these two algorithms in supporting multipoint-to- point communications in WDM networks.

2 citations

Proceedings ArticleDOI
26 Jun 2018
TL;DR: This paper proposes an exact method based on an Integer Linear Programming (ILP) formulation for the two node-disjoint paths with energy-aware routing (TNDP-EAR) problem, known to be NP-hard, and proposes a heuristic-based algorithm called GreenTNDP.
Abstract: Carrier grade networks are in general over-dimensioned in order to protect against network resource failures and to handle probable traffic peaks. Such network design exhibits non-negligible energy waste. As well known, during network operation, the traffic load varies remarkably over day hours. Typically, a significant amount of energy saving can be achieved by turning off redundant and underutilized resources. Ensuring a sufficient level of reliability while taking into account energy saving objective is a very challenging task. In this paper, we study the multi-commodity reliable network design for carrier Ethernet networks. Each traffic demand is routed along one working path, and a corresponding backup path computed considering dedicated protection scheme. The primary and backup path must be node-disjoint. We also assume that the links of the carrier grade networks are made of multiple physical cables called bundles. We propose an exact method based on an Integer Linear Programming (ILP) formulation for the two node-disjoint paths with energy-aware routing (TNDP-EAR) problem. The studied problem is known to be NP-hard. In order to solve it efficiently, we propose a heuristic-based algorithm called GreenTNDP. Preliminary experimental results show the effectiveness of our algorithms to solve the problem.

2 citations

Journal ArticleDOI
TL;DR: A new algorithm is proposed exploiting the SRLG structures to enhance the admission control and improve the protection rate and, it reduces in distributed environments the average number of messages sent to manage the bandwidth information necessary for the backup path computation.

2 citations


Cited by
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Journal ArticleDOI
TL;DR: To support bursty traffic on the Internet (and especially WWW) efficiently, optical burst switching (OBS) is proposed as a way to streamline both protocols and hardware in building the future gener...
Abstract: To support bursty traffic on the Internet (and especially WWW) efficiently, optical burst switching (OBS) is proposed as a way to streamline both protocols and hardware in building the future gener...

674 citations

Book
01 Dec 1981

609 citations

Journal ArticleDOI
TL;DR: A comprehensive survey on RA in HetNets for 5G communications is provided and two potential structures for 6G communications are provided, such as a learning-based RA structure and a control- based RA structure.
Abstract: In the fifth-generation (5G) mobile communication system, various service requirements of different communication environments are expected to be satisfied. As a new evolution network structure, heterogeneous network (HetNet) has been studied in recent years. Compared with homogeneous networks, HetNets can increase the opportunity in the spatial resource reuse and improve users’ quality of service by developing small cells into the coverage of macrocells. Since there is mutual interference among different users and the limited spectrum resource in HetNets, however, efficient resource allocation (RA) algorithms are vitally important to reduce the mutual interference and achieve spectrum sharing. In this article, we provide a comprehensive survey on RA in HetNets for 5G communications. Specifically, we first introduce the definition and different network scenarios of HetNets. Second, RA models are discussed. Then, we present a classification to analyze current RA algorithms for the existing works. Finally, some challenging issues and future research trends are discussed. Accordingly, we provide two potential structures for 6G communications to solve the RA problems of the next-generation HetNets, such as a learning-based RA structure and a control-based RA structure. The goal of this article is to provide important information on HetNets, which could be used to guide the development of more efficient techniques in this research area.

321 citations

Posted Content
TL;DR: In this article, the authors provide a comprehensive tutorial on the main concepts of machine learning, in general, and artificial neural networks (ANNs), in particular, and their potential applications in wireless communications.
Abstract: Next-generation wireless networks must support ultra-reliable, low-latency communication and intelligently manage a massive number of Internet of Things (IoT) devices in real-time, within a highly dynamic environment. This need for stringent communication quality-of-service (QoS) requirements as well as mobile edge and core intelligence can only be realized by integrating fundamental notions of artificial intelligence (AI) and machine learning across the wireless infrastructure and end-user devices. In this context, this paper provides a comprehensive tutorial that introduces the main concepts of machine learning, in general, and artificial neural networks (ANNs), in particular, and their potential applications in wireless communications. For this purpose, we present a comprehensive overview on a number of key types of neural networks that include feed-forward, recurrent, spiking, and deep neural networks. For each type of neural network, we present the basic architecture and training procedure, as well as the associated challenges and opportunities. Then, we provide an in-depth overview on the variety of wireless communication problems that can be addressed using ANNs, ranging from communication using unmanned aerial vehicles to virtual reality and edge caching.For each individual application, we present the main motivation for using ANNs along with the associated challenges while also providing a detailed example for a use case scenario and outlining future works that can be addressed using ANNs. In a nutshell, this article constitutes one of the first holistic tutorials on the development of machine learning techniques tailored to the needs of future wireless networks.

265 citations