A New Approach to Manage QoS in Distributed Multimedia Systems

Dealing with network congestion is a criterion used to enhance quality of service (QoS) in distributed multimedia systems. The existing solutions for the problem of network congestion ignore scalability considerations because they maintain a separate classification for each video stream. In this paper, we propose a new method allowing to control QoS provided to clients according to the network congestion, by discarding some frames when needed. The technique proposed, called (m,k)-frame, is scalable with little degradation in application performances. (m,k)-frame method is issued from the notion of (m,k)-firm realtime constraints which means that among k invocations of a task, m invocations must meet their deadline. Our simulation studies show the usefulness of (m,k)-frame method to adapt the QoS to the real conditions in a multimedia application, according to the current system load. Notably, the system must adjust the QoS provided to active clients1 when their number varies, i.e. dynamic arrival of clients.Comment: 10 pages, International Journal of Computer Science and Information Security (IJCSIS

Toward the Design of an Efficient and Secure System Based on the Software-Defined Network Paradigm for Vehicular Networks

The advent of Intelligent Transport Systems (ITS) has led to the appearance of vehicles increasingly connected to their environment on global road networks. Due to the strict requirements for low latency and secure interactions in a vehicular environment, the proposal of new architectures is a crucial topic for discussion. This paper aims to develop a vehicular network using several access technologies based on SDN (Software Defined Network) paradigm, to take advantage of the capacities of the various access networks and provide flexibility in their control and management. Confidentiality, integrity, and authentication are essential services to prevent an adversary from compromising the security of vehicular networks. Therefore, good security and privacy management system is necessary to ensure this protection. We represent then a hybrid SDN-VANET architecture that can address all of the challenges we mentioned earlier. We are in the process of implementing a dynamic approach to optimize the positioning of controllers according to changes in network topology due to fluctuations in road traffic. We will also detail the topology estimation service based on machine learning techniques to provide network control functions with potential insight into the future state of the network, unlocking proactive and intelligent network control. We also provide a scheme that prevents and informs about basic and compound attacks and reacts to the privacy and security conditions of the vehicular network, managing the requirements of security management systems. The simulation results showed the effectiveness of the proposed schemes in terms of message loss rates, packet delivery rates (PDR), Round Trip Time (RTT), and delays. With used our scheme, the performance of the network is improved when SDN triggers the change of the RSU entity. Such as we notice that the average RTT is lowered by 68 ms and that the PDR remains around 94%. We also notice with the integration of the security and privacy scheme (SPS) that the performance of the network is improved, the average RTT is reduced by 51 ms and the PDR persists around 99%

From a Master Server Architecture to a Feedback Control Architecture

International audienceToday's multimedia applications ask for a complex set of quality of service (QoS) requirements. These ap- plications define time, bandwidth and synchronization constraints and manage large quantities of data. Due to the similarities existing between multimedia appli- cations and real-time database systems (RTDBSs), we propose, in this paper, an approach which consists in exploiting some works related to the QoS management in RTDBSs in order to apply them to multimedia sys- tems. We particularly propose a FCS-MS1 architecture, an improvement of the original master server architec- ture, which deals with QoS management by optimizing the resources use and reducing significantly the system overloads

Overload control in distributed multimedia systems

International audienceThe multimedia applications manage voluminous quantities of data. Its exploitation must respect the temporal constraints permitting to read the video packets with a certain fluidity. When the temporal constraints are not met, the quality of service (QoS) provided to users decreases. Considering there are similarities between the multimedia applications and the Real-Time Databases Systems (RTDBSs), our approach consists to exploit the works concerning the management of the QoS for the multimedia system. In this paper, we exploit some results obtained in QoS management in RTDBSs, and we apply them to multimedia applications, because of similarities existing between these two fields. We propose a new method allowing to have an efficient management of data and to control the QoS provided to clients according to the system congestion

A New Method to Improve Network Exchanges of Multimedia Stream

International audienceMultimedia applications usually manage large quantities of data in the form of frames of certain types. To ensure a good trafic of these frames through the network, temporal constraints must be respected when sending and receiving these frames. If the temporal constraints are not met, then the quality of service (QoS) provided to users decreases. In this paper, we exploit some results obtained in QoS management in Real-Time Databases Systems (RTDBSs), and we apply them to multimedia applications, because of similarities existing between these two fields. We propose a new method allowing to control the QoS provided to clients according to the network congestion, by discarding some frames when needed

Gestion de qualité de service dans les systèmes multimédia distribués

LE HAVRE-BU Centrale (763512101) / SudocSudocFranceF

Payoff-based dynamic segment replication policy in distributed VOD system

International audienc

Feedback architecture for multimedia systems

International audienc

(m,k)-frame: A Method to Control the Quality of Service in Distributed Multimedia Systems

International audienceMultimedia applications usually manage large quantities of data in the form of frames of certain types. To ensure a good trafic of these frames through the network, temporal constraints must be respected when sending and receiving these frames. If the temporal constraints are not met, then the quality of service (QoS) provided to users decreases. In this paper, we exploit some results obtained in QoS management in Real-Time Database Systems (RTDBSs), and we apply them to multimedia applications, because of similarities existing between these two fields. We propose a new method allowing to control the QoS provided to clients according to the network congestion, by discarding some frames when needed

Towards Misbehavior Intelligent Detection Using Guided Machine Learning in Vehicular Ad-hoc Networks (VANET)

C-ITS (Cooperative Intelligent Transport Systems) est une nouvelle technologie qui contribue à la réduction des accidents de la circulation et à l'amélioration de la sécurité routière. VANET ( V ehicular A d hoc Networks) sont un système STI basé sur la communication inter-véhicules par la transmission de messages de sécurité de base (BSM), qui sont vulnérables à une variété de comportements inappropriés. Pour résoudre ce défi, nous avons développé dans cet article un système de détection de mauvais comportement (MDS) basé sur une approche d'apprentissage automatisé pour identifier et catégoriser les messages de mauvais comportement délivrés par un véhicule sur les VANET à l'aide de la base de données d'extension VeReMi. Cette étude examine différents types de classification : dans la classification binaire, toutes sortes d'inconduites ont été regroupées en une seule catégorie « inconduite » ; cependant, dans la classification multi-classes pour trois classes, la mauvaise conduite a été divisée en deux classes : les attaques et les fautes. Le classificateur a des problèmes substantiels lors de l'apprentissage à partir de données déséquilibrées wLorsque vous travaillez avec des problèmes multi-classes, cela devient considérablement plus complexe. Les relations entre les catégories ne sont plus bien définies et il est facile de perdre en efficacité dans une classe tout en s'améliorant dans une autre. En conséquence, les résultats ne sont pas cohérents dans l'approche d'apprentissage classique pour la classification multi-classes lors de la classification des comportements répréhensibles dans différents types de classes de comportements répréhensibles. Pour résoudre ce problème, nous avons développé une approche nouvelle et puissante appelée "Approche d'apprentissage guidé pour la classification multi-classes" pour réduire le nombre de classes en combinant des comportements inappropriés comparables en un seul. Selon les résultats, le classificateur Random Forest surpasse les autres classificateurs