QoS Bandwidth Optimization in an Inductive Routing System for Multimedia Real‐Time Applications

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QoS‐Based Adaptive Approaches

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Un routage inductif pour une meilleure garantie de service dans les réseaux de communication

International audienceLa nature des flux circulant sur le reseau et la constante progression des besoins des utilisateurs induisent de maniere in- trinseque un trafic tres variable se caracterisant de plus en plus par des anomalies ayant pour consequence des changements detats imprevisibles dans le reseau. Lintegration de ce nouveau phenomene dans les politiques de decision afin de repondre au mieux aux aspects lies a la qualite de service constitue un vaste sujet de recherche et a fait lobjet de nombreuses techniques proposees dans la litterature. Lobjectif de cet article est de proposer une approche modulaire lexicographique permettant de faire une optimisation combinee de criteres statiques et dynamiques appliquee a la problematique du routage adaptatif dans un reseau de communication a trafic irregulier. La politique de routage developpee dans cet article s'appuie sur la technique de routage multi-chemins combinee avec un algorithme adaptatif de type Q-learning. Dans la partie experimentation, nous analysons puis comparons les performances de l'approche proposee a celles des algorithmes plus classiques bases sur la recherche des plus courts chemins

La perception de l’usager comme paramètre pilote dans le routage inductif des applications temps réel au sein d’un réseau opérateur

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An Evidential Approach for Network Interface Selection in Heterogeneous Wireless Networks

International audienceWhen several networks (e.g., Wi-Fi, UMTS, and LTE) cover the same region, the mobile terminals that are equipped with multiple network interfaces provide the possibility for mobile end-users to select their believed best network. This is known as the network selection problem, which is a decision making problem with multiple criteria (network conditions, service requirements, terminal characteristics, and user needs). Many network selection solutions using different mathematical theories have been proposed in the literature to allow the best connectivity for applications, users, and terminals. Unfortunately, most approaches for the network selection do not make effective selection decisions, since they are vulnerable to the uncertainty and imprecision related to network state information. In this paper, we investigate the belief functions theory to devise an efficient lightweight uncertainty- aware network interface selection scheme. We provide analytical studies and simulation experiments to demonstrate the efficiency of the proposed solution

Quality of Experience for Multimedia

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QoE‐based Routing for Content Distribution Network Architecture

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A Multi‐criteria Master Nodes Selection Mechanism for Knowledge Dissemination In Autonomic Networks

Autonomic Networks represent a concept inspired by the biological world that aims at making a network independent of any human monitoring. To reach such autonomy, knowledge should be disseminated over the network, which remains an open problem. In fact, disseminating the knowledgeover all nodes leads to a big overhead. That is why we need to select a subset of nodes in charge of knowledge management. A single criterion-based selection mechanism has been proposed in a previous work but such a mechanism seems to be very simplistic. In this paper, we present a new multi-criteria selection mechanism based on Pareto. The simulation results show that, over all the selected criteria, the new approach significantly improves performances

User to user adaptive routing based on QoE

International audienceService quality can be defined as “the collective effect of service performances which determine the degree of satisfaction of a user of the service” [1]. In other words, quality is the customer's perception of a delivered service. As larger varieties of services are offered to customers, the impact of network performance on the quality of service will be more complex. It is vital that service engineers identify network-performance issues that impact customer service. They also must quantify revenue lost due to service degradation. The Quality of Experience (QoE) becomes recently the most important tendency to guarantee the quality of network services. QoE represents the subjective perception of end-users using network services with network functions such as admission control, resource management, routing, traffic control, etc. In this paper, our main focus is routing mechanism driven by QoE end-users. With the purpose of avoiding the NP-complete problem and reducing the complexity problem for the future Internet, we propose two protocols based on user QoE measurement in routing paradigm to construct an adaptive and evolutionary system. Our first approach is a routing driven by terminal QoE basing on a least squares reinforcement learning technique called Least Squares Policy Iteration. The second approach, namely QQAR (QoE Q-learning based Adaptive Routing), is a improvement of the first one. QQAR basing on Q-Learning, a Reinforcement Learning algorithm, uses Pseudo Subjective Quality Assessment (PSQA), a real-time QoE assessment tool based on Random Neural Network, to evaluate QoE. Experimental results showed a significant performance against over other traditional routing protocols

Utility function‐Based TOPSIS for Network Interface Selection in Heterogeneous Wireless Networks

International audienceThe presence of constitutive alkali-labile sites (ALS) has been investigated using a protocol of DNA breakage detection-fluorescence in situ hybridization and comet assay in spermatozoa of donkey (Equus asinus) and stallion (Equus caballus). These results were compared with those obtained using a similar experimental approach using somatic cells. The relative abundance of ALS was of the order of four times more in spermatozoa than in somatic cells. Alkali-labile sites showed a tendency to cluster localized at the equatorial-distal regions of the sperm. The amount of hybridized signal in the ALS in the sperm of donkey (Equus asinus) was 1.3 times greater than in stallion (Equus caballus), and the length of the comet tail obtained in donkey sperm was 1.6 times longer than that observed in stallion (P<0.05); however, these differences were not appreciated in somatic cells. In conclusion, ALS localization in sperm is not a randomized event and a different pattern of ALS distribution occurs for each species. These results suggest that ALS represents a species-specific issue related to chromatin organization in sperm and somatic cells in mammalian species, and they might diverge even with very short phylogenetic distances