Cycle Accurate Simulation Model Generation for SoC Prototyping

RR 2004-18, ENS-Lyon, 24 pagesWe present new results concerning the integration of high level designed ips into a complete System on Chip. We first introduce a new compu- tation model that can be used for cycle accurate simulation of register transfer level synthesized hardware. Then we provide simulation of a SoC integrating a data-flow ip synthesized with MMAlpha and the So- cLib cycle accurate simulation environment. This integration also vali- dates an efficient generic interface mechanism for data-flow ips

Analyses statistiques des communications sur puce

This PhD is composed of two main parts. The first one focuses on Internet traffic modelling. From the analysis of many traffic traces, we have proposed a parsimonious model (Gamma-Farima) adapted to aggregated throughput traces and valid for wide range of aggregation levels. In order to produce synthetic traffic from this model, we have also studied the generation of sample path of non-gaussian and long memory stochastic processes. We have then used the Gamma-Farima model in order to build an anomaly detection method. To this end we have introduced a multiresolution model that can differentiate a regular traffic from a malicious one (including a DDoS attack). This method was evaluated both on real traces and simulations. Finally, we have studied the production of long range dependent traffic in a network simulator (NS-2). The second part of this PhD deals with the analysis and synthesis of on-chip traffic, i.e. the traffic occurring in a system on chip. In such systems, the introduction of networks on chip (NOC) has brought the interconnection system on top of the design flow. In order to prototype these NOC rapidly, fast simulations need to be done, and replacing the components by traffic generators is a good way to achieve this purpose. So, we have set up and developed a complete and flexible on-chip traffic generation environment that is able to replay a previously recorded trace, to generate a random load on the network, to produce a stochastic traffic fitted to a reference trace and to take into account traffic phases. Indeed most of the traffic traces we have obtained were non-stationary, we therefore need to split them into reasonably stationary parts in order to perform a meaningful stochastic fit. We have performed many experiments in the SOCLIB simulation environment that demonstrate that i) our traffic generation procedure is correct, ii) our segmentation algorithm provides promising results and iii) multiphase stochastic traffic generation is a good tradeoff between replay and simple random traffic generation. Finally, we have investigated the presence of long memory in the trace as well as the impact of long memory on the NoC performance.Cette thèse est composée de deux parties. La première explore la problématique de la modélisation de trafic Internet. Nous avons proposé, à partir de l'étude de nombreuses traces, un modèle basé sur des processus stochastiques non-gaussiens à longue mémoire (Gamma-Farima) permettant de modéliser de manière pertinente les traces de débit agrégé, et ce pour une large gamme de niveau d'agrégation. Afin de pouvoir générer du trafic synthétique, nous avons proposé une méthode de synthèse de tels processus. Nous avons ensuite, à partir du modèle Gamma-Farima, proposé un modèle multirésolution permettant de différencier un trafic régulier, d'un trafic contenant une attaque (de type déni de service distribuée). Ceci nous a permis de proposer une méthode de détection d'anomalie que nous avons évalué sur des traces réelles et en simulation. Enfin nous avons étudié expérimentalement le problème de la production de trafic à longue mémoire dans un simulateur de réseaux (NS-2). La deuxième partie traite la problématique de la génération de trafic au sein des systèmes sur puce (SOC). Dans ce domaine, l'arrivée de véritable réseaux sur puce place la conception de l'interconnexion au premier plan, et pour accélérer les simulations, il convient de remplacer les composants par des générateurs de trafic. Nous avons mis en place un environnement complet de génération de trafic sur puce permettant de rejouer une trace, de produire une charge aléatoire sur le réseau, de produire un trafic stochastique ajusté sur une trace de référence et de tenir compte des phases dans le trafic. Nous avons effectué de nombreuses simulations dans l'environnement de simulation de SOC académique SOCLIB qui nous ont permis de valider notre approche, d'évaluer notre algorithme de segmentation ainsi que la génération de trafic stochastique multiphase que nous avons introduite. Nous avons aussi exploré la présence de longue mémoire dans le trafic des processeurs sur puce, ainsi que l'impact de cette caractéristique sur les performances du réseau sur puce

How to evaluate community predictions without thresholding?

Stacked species distribution models (S-SDM) provide a tool to make spatial predictions about communities by first modelling individual species and then stacking the modelled predictions to form assemblages. The evaluation of the predictive performance is usually based on a comparison of the observed and predicted community properties (e.g. species richness, composition). However, the most available and widely used evaluation metrics require the thresholding of single species' predicted probabilities of occurrence to obtain binary outcomes (i.e. presence/absence). This binarization can introduce unnecessary bias and error. Herein, we present and demonstrate the use of several groups of new or rarely used evaluation approaches and metrics for both species richness and community composition that do not require thresholding but instead directly compare the predicted probabilities of occurrences of species to the presence/absence observations in the assemblages. Community AUC, which is based on traditional AUC, measures the ability of a model to differentiate between species presences or absences at a given site according to their predicted probabilities of occurrence. Summing the probabilities gives the expected species richness and allows the estimation of the probability that the observed species richness is not different from the expected species richness based on the species' probabilities of occurrence. The traditional Sorensen and Jaccard similarity indices (which are based on presences/absences) were adapted to maxSorensen and maxJaccard and to probSorensen and probJaccard (which use probabilities directly). A further approach (improvement over null models) compares the predictions based on S-SDMs with the expectations from the null models to estimate the improvement in both species richness and composition predictions. Additionally, all metrics can be described against the environmental conditions of sites (e.g. elevation) to highlight the abilities of models to detect the variation in the strength of the community assembly processes in different environments. These metrics offer an unbiased view of the performance of community predictions compared to metrics that requiring thresholding. As such, they allow more straightforward comparisons of model performance among studies (i.e. they are not influenced by any subjective thresholding decisions).Peer reviewe

Loi de puissance et caractérisation des réseaux dynamiques

National audienceCaractériser la dynamique et l'évolution au cours du temps d'un réseau sans fil multi sauts (réseaux ad hoc, réseaux de senseurs) apparaît comme un problème important car cela doit permettre de comprendre, de modéliser et de développer des algorithmes et des protocoles adaptés. A partir des traces expérimentales collectées lors de la conférence Infocom 2005 [1], nous proposons une analyse plus avancée de la structure évolutive de ce genre de réseaux. Plus précisément, nous montrons que la seule caractérisation au travers d'une loi de puissance des contacts et inter-contacts entre individus/noeuds n'est pas suffisante pour capturer et rendre l'évolution du réseau. A partir d'une analyse combinant trois approches [2] qui se révèlent très complémentaires (théorie des graphes, processus aléatoires et fouille de données), nous proposons un modèle simple mettant en évidence la complexité de la structure évolutive

Revisiting an old friend: On the observability of the relation between Long Range Dependence and Heavy Tail

International audienceTaqqu's Theorem plays a fundamental role in Internet traffic modeling, for two reasons: First, its theoretical formulation matches closely and in a meaningful manner some of the key network mechanisms controlling traffic characteristics; Second, it offers a plau- sible explanation for the origin of the long range dependence property in relation with the heavy tail nature of the traffic components. Numerous attempts have since been made to observe its predictions empirically, either from real Internet traffic data or from numerical simulations based on popular traffic models, yet rarely has this resulted in a satisfactory quantitative agreement. This raised in the literature a number of comments and questions, ranging from the adequacy of the theorem to real world data to the relevance of the statistical tools involved in practical analyses. The present contribution aims at studying under which conditions this fundamental theorem can be actually seen at work on real or simulated data. To do so, numerical simulations based on standard traffic models are analyzed in a wavelet framework. The key time scales involved are derived, enabling a discussion of the origin and nature of the difficulties encountered in attempts to empirically observe Taqqu's Theorem

Biogeophysical controls on soil-atmosphere thermal differences : implications on warming Arctic ecosystems

Soil temperature (ST) has a key role in Arctic ecosystem functioning and global environmental change. However, soil thermal conditions do not necessarily follow synoptic temperature variations. This is because local biogeophysical processes can lead to a pronounced soil-atmosphere thermal offset (Delta T) while altering the coupling (beta Tau) between ST and ambient air temperature (AAT). Here, we aim to uncover the spatiotemporal variation in these parameters and identify their main environmental drivers. By deploying a unique network of 322 temperature loggers and surveying biogeophysical processes across an Arctic landscape, we found that the spatial variation in Delta T during the AAT 0 period, Delta T was controlled by soil characteristics, vegetation and solar radiation (Delta T = -0.6 degrees C +/- 1.0 degrees C). Importantly, Delta T was not constant throughout the seasons reflecting the influence of beta Tau on the rate of local soil warming being stronger after (mean beta Tau = 0.8 +/- 0.1) than before (beta Tau = 0.2 +/- 0.2) snowmelt. Our results highlight the need for continuous microclimatic and local environmental monitoring, and suggest a potential for large buffering and non-uniform warming of snow-dominated Arctic ecosystems under projected temperature increase.Peer reviewe

La stratégie de l’Union européenne contre la criminalité organisée : entre lacunes et inquiétudes

La criminalité transnationale organisée (CTO) est devenue un élément majeur des agendas des institutions internationales. La mobilisation de la communauté internationale a donné lieu à un nombre impressionnant de réponses institutionnelles à ce qui a été décrit comme un défi d’envergure mondiale. L’agenda JAI de l’UE n’a pas fait exception, et a constamment inclus la lutte contre la CTO au rang de ses priorités depuis le milieu des années 1990. Afin de comprendre l’état actuel de la stratégie de l’UE contre la criminalité organisée, et en tenant compte des derniers développements en la matière, cet article examine successivement le cadre légal de l’UE, ainsi que ses mécanismes de coopération, et notamment le rôle et le mandat d’Europol et d’Eurojust.Transnational Organised Crime (TOC) has risen up on international institutions’ agenda. The international community’s mobilisation against organised crime has led to an impressive elaboration of institutional responses to what has been depicted as a global challenge. The EU JHA agenda has not been an exception, which has constantly addressed this issue since the middle of the 1990s. In order to understand the current state of the EU strategy against organised crime, this article examines the existing EU legislative framework, as well as the European justice and police co-operation mechanisms (specifically the role and mandate of Europol and Eurojust)

Detection of linear trends in multi-sensor time series in the presence of autocorrelated noise: Application to the chlorophyll-a SeaWiFS and MERIS datasets and extrapolation to the incoming Sentinel 3-OLCI mission

The detection of long-term trends in geophysical time series is a key issue in climate change studies. This detection is affected by many factors: the size of the trend to be detected, the length of the available data sets, and the noise properties. Although the noise autocorrelation observed in geophysical time series does not bias the trend estimate, it affects the estimation of its uncertainty and consequently the ability to detect, or not, a significant trend. Ignoring the noise autocorrelation level typically leads to an overdetection of significant trends. Due to satellite lifetime, usually between 5 and 10 years, sea surface time series do not cover the same period and are acquired by different sensors with different characteristics. These differences lead to unknown level shifts (biases) between the datasets, which affect the trend detection. In this work, we develop a generic framework to detect and evaluate linear trends and level shifts in multisensor time series of satellite chlorophyll-a concentrations, as provided by the Medium Resolution Imaging Spectrometer instrument (MERIS) and sea-viewing wide field-of-view sensor (SeaWiFS) ocean-color missions. We also discuss the optimization of the observation networks, in terms of needed time overlap between successive time series to reduce the uncertainty on the detection of long-term trends. For the incoming Sentinel 3-Ocean and Land Color Instrument (3-OLCI)mission that should be launched at the end of 2014, we propose a global map of the number of months of observations to enhance the trend detection performed with the joint SeaWiFS-MERIS analysis

Two-Dimensional Electrophoresis of Tau Mutants Reveals Specific Phosphorylation Pattern Likely Linked to Early Tau Conformational Changes

The role of Tau phosphorylation in neurofibrillary degeneration linked to Alzheimer's disease remains to be established. While transgenic mice based on FTDP-17 Tau mutations recapitulate hallmarks of neurofibrillary degeneration, cell models could be helpful for exploratory studies on molecular mechanisms underlying Tau pathology. Here, “human neuronal cell lines” overexpressing Wild Type or mutated Tau were established. Two-dimensional electrophoresis highlights that mutated Tau displayed a specific phosphorylation pattern, which occurs in parallel to the formation of Tau clusters as visualized by electron microscopy. In fact, this pattern is also displayed before Tau pathology onset in a well established mouse model relevant to Tau aggregation in Alzheimer's disease. This study suggests first that pathological Tau mutations may change the distribution of phosphate groups. Secondly, it is possible that this molecular event could be one of the first Tau modifications in the neurofibrillary degenerative process, as this phenomenon appears prior to Tau pathology in an in vivo model and is linked to early steps of Tau nucleation in Tau mutants cell lines. Such cell lines consist in suitable and evolving models to investigate additional factors involved in molecular pathways leading to whole Tau aggregation