Abstract

This paper addresses the issue of multiservice support in IEEE 802.16 or WiMAX networks. The capacity for supporting multiple service classes is indeed important for any access technology where bandwidth is limited, which is the case for IEEE 802.16. The standard currently proposes four traffic classes, and specifies that for uplink traffic, the first one (UGS) receives periodic grants whereas the other three are served via polling. Supporting two different scheduling mechanisms may have a significant impact on the complexity of network interface cards, and therefore on the CAPEX for WiMAX networks. Based on this analysis, the present work investigates whether a 802.16 network that only supports the 3 polling based classes is still capable of providing the QoS levels expected for all types of applications. Both the transfer plane QoS, in terms of latency and jitter, and the command plane QoS, in terms of blocking probability are assessed. In particular, a simple, multiservice call admission control (CAC) mechanism is proposed that significantly improves on a previously proposed CAC mechanism by favouring real time traffic over non real time traffic. The outcome of this study shows that it is indeed possible to support stringent QoS with only polling based traffic classes, and fairly simple traffic engineering mechanisms fully described in the paper.

Abstract

International audience; The objective of the work presented here is a bayesian calibration of parameters describing the mechanical characteristics of high-speed train suspensions for maintenance purposes. This calibration is achieved by comparing simulation results to on-track accelerometric measurements. It requires the estimation on the multidimensionnal admissible set of the parameters of the likelihood function of the train dynamic response. This estimation is achieved thanks to the identification of a kriging metamodel of this likelihood function to reduce the numerical cost. From this metamodel, the posterior probability density function of the parameters is estimated using an MCMC algorithm.

Abstract

Best paper award; International audience; Clustering is a common operation in statistics. When data considered are functional in nature, like curves, dedicated algorithms exist, mostly based on truncated expansions on Hilbert basis. When additional constraints are put on the curves, like in applications related to air traffic where operational considerations are to be taken into account, usual procedures are no longer applicable. A new approach based on entropy minimization and Lie group modeling is presented here, yielding an efficient unsupervised algorithm suitable for automated traffic analysis. It outputs cluster centroids with low curvature, making it a valuable tool in airspace design applications or route planning. Keywords–curve clustering; probability distribution estimation; functional statistics; minimum entropy; air traffic management. I. INTRODUCTION Clustering aircraft trajectories is an important problem in Air Traffic Management (ATM). It is a central question in the design of procedures at takeoff and landing, the so called sid-star (Standard Instrument Departure and Standard Terminal Arrival Routes). In such a case, one wants to minimize the noise and pollutants exposure of nearby residents while ensuring runway efficiency in terms of the number of aircraft managed per time unit. The same question arises with cruising aircraft, this time the mean flight path in each cluster being used to optimally design the airspace elements (sectors and airways). This information is also crucial in the context of future air traffic management systems where reference trajectories will be negotiated in advance so as to reduce congestion. A special instance of this problem is the automatic generation of safe and efficient trajectories, but in such a way that the resulting flight paths are still manageable by human operators. Clustering is a key component for such tools: major traffic flows must be organized in such a way that the overall pattern is not too far from the current organization, with aircraft flying along airways. The classification algorithm has thus not only to cluster similar trajectories but at the same time make them as close as possible to operational trajectories. In particular, straightness of the flight segments must be enforced, along with a global structure close to a graph with nodes corresponding to merging/splitting points and edges the airways.

Abstract

International audience; In air transportation, especially in airport safety, radar tracks are continuously recorded and may be used for detecting incidents on airport surface. However, all known statistical algorithms, even those based on functional data, are unable to distinguish between a safety critical flight and another one departing from standard behavior, but otherwise safe. In this work, we propose a change of paradigm by representing curves as points in a shape manifold. In this framework, it is possible to use Finsler distances between shapes that explicitly take into account the second derivative and can be able to 1 correctly detect skid situations from deviant trajectories that cannot be considered as a slipped trajectory. This metric is next used in curve clustering for detecting bad runway conditions. Some results on datasets of synthetic and real trajectories are presented, as well as a comparison of existing metrics.; Sur la plupart des plateformes aéroportuaires, les déplacements des aéronefs sont enregistrés en continu par des radars de surveillance et les trajectoires ainsi obtenues peuvent être utilisées pour détecter ou prévenir des incidents lors du roulage, en particu-lier des dérapages. Cependant, l'exploitation de ces données est rendue difficile par le fait que les algorithmes statistiques connus, même ceux basés sur des données fonctionnelles, ne sont pas capables de distinguer les situations réellement dangereuses des déviations au comportement standard qui sont sans gravité. Dans cette étude, nous proposons un chan-gement de paradigme en représentant les trajectoires comme des points dans un espace de formes. Dans ce nouveau cadre, il est possible de construire des distances de type Fins-ler, prenant explicitement en compte les dérivées secondes des trajectoires, et qui sont en mesure de bien séparer les trajectoires présentant un dérapage de celles dont la déviation par rapport au comportement nominal n'est pas due à un manque d'adhérence. Cette métrique est ensuite utilisée dans des méthodes de clustering pour détecter un mauvais état de la piste d'atterrissage. Des résultats sur des jeux de données de trajectoires syn-thétiques et réelles sont présentés ainsi qu'une comparaison avec des métriques existantes. Mots-clés. Similarité entre courbes, espace de formes, données fonctionnelles, classification non supervisée de courbes, sécurité aéroportuaire.

Abstract

International audience; ECOFRAME ring is a novel network technology for the metropolitan transport that exploits optical packet switching and optical transparency. Each station in this ring is equipped with a tunable transmitter and a number of fixed receivers, able to extract traffic from a predefined set of wavelengths (number of wvl. ≥ 1). Receivers can be shared by different destinations, of- fering to this technology an ability to achieve significant CAPEX savings by using the optimum number of network resources, if properly dimensioned. In this paper we present a wide set of conclusions obtained when applying different network planning and traffic engineering tools in investigating an optimal design and evaluating performances of an ECOFRAME ring. More precisely, regarding network planning issues, we have estimated equipment costs, identified different network configurations and studied their impact on ring performances. Finally, we have found the potential savings when ring is properly designed. On the other hand, based on the previous results, we have identified the optimal ring configuration from price, capacity and scheduling point of view, suggested a cheap and fair scheduling policy for a general case and evaluated the positive impact of statistical multiplexing due to the WDM dimension, on the ring capacity. We have shown that an OPS ring that is properly dimensioned can achieve a solid QoS performance without slot reservation mechanisms.