Events in May–June 2018
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April 30, 2018
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MayMay 1, 2018 |
May 2, 2018
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May 3, 2018
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May 4, 2018(1 event)
A data structure for analyzing spatio-temporal correlations of alarms, by Anne Bouillard (Nokia)A data structure for analyzing spatio-temporal correlations of alarms, by Anne Bouillard (Nokia) – In this talk, I will present a data structure for the analysis of correlations of alarms, for root-cause analysis or prediction purposes. This is a joint work with Marc-Olivier Buob and Maxime Raynal (intern). A sequence of alarms is modeled by a directed acyclic graph. The nodes of the graph are the alarms, that are represented by a symbol and an interval of time. An arc of the graph is interpreted as a potential causality between two alarms. I will first show how to build a "compact" structure storing all the potential causal sequences of alarms and then how to weight this structure so that the actual correlations can be detected. The efficiency of the approach will be demonstrated on toy examples. Bâtiment IMAG (442) |
May 5, 2018
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May 7, 2018
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May 8, 2018
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May 9, 2018
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May 11, 2018
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May 12, 2018
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May 13, 2018
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May 14, 2018
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May 15, 2018
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May 16, 2018
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May 17, 2018
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May 18, 2018
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May 19, 2018
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May 20, 2018
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May 21, 2018
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May 22, 2018
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May 23, 2018
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May 24, 2018
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May 25, 2018
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May 26, 2018
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May 27, 2018
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May 28, 2018
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May 29, 2018
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May 30, 2018
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May 31, 2018(1 event)
Analytical Modeling for Flow-level Performance of Randomly Placed Wireless Networks by George Arvanitakis (postdoc, Polaris)Analytical Modeling for Flow-level Performance of Randomly Placed Wireless Networks by George Arvanitakis (postdoc, Polaris) – The recent evolution of mobile communications and the widespread use of ``smart'' mobile devices have radically changed the behavior and the needs of the mobile user. In the developed world, people that use their mobile devices just to place some calls and to text some SMS can be characterized as endangered species. Ubiquitous access to Internet, videos/songs streaming and upload/download data flows on the fly are some of the modern demands of the mobile user. It would not be an exaggeration to say that modern users have almost the same demands regardless if they are connected through wire to the network from their personal computers or if they have established a wireless connection through their cellular devices. On the one hand the overall network load increases on the other hand base stations have limited resources due to the fact that are able to operate only to a limited part of the electromagnetic spectrum. Some (temporal) solutions for the aforementioned problem are the expansion of frequency operational bands (mm wave) or the use of more antennas (massive MIMO) or the denser deployment of small cells. In this talk, we are interested in the promising case of denser small cells that will be tighter integrated with the macro cell. Unfortunately to deploy optimally a small cell network is not trivial. A small cell network is usually deployed in an ad-hoc style and not all at once, so a part of the network exists already and cannot be planned. Additionally, there are natural obstacles and physical limitations that do not allow to deploy base stations wherever we want. So, the small cell network's topology is quite different from the traditional (macro cell) well-structure one. From our point of view, the future of mobile communications will approach the following: A mass of users - will cause a nondescript data traffic - that will be served from an irregular planed and heterogeneous network. This chaotic picture however makes the problem of network modeling and performance analysis extremely challenging. To this end, the our primary focus is to build up an analytical framework in order to analyze the performance of a randomly placed network, which serves randomly placed users. To achieve this, we based our analysis on two main tools: (a) stochastic geometry, to understand the impact of topological randomness and coverage maps and (b) queueing theory, to model the competition between concurrent flows within the same BS. The second goal is to propose, based on this analysis, some general design guidelines and insights about specific communication scenarios that mainly involve LTE and WiFi networks. Bat. IMAG, 206 |
JuneJune 1, 2018 |
June 2, 2018
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June 3, 2018
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June 4, 2018
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June 5, 2018
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June 6, 2018
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June 7, 2018(1 event)
Keynote du LIG: Erol GelenbeKeynote du LIG: Erol Gelenbe – TBA |
June 8, 2018
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June 9, 2018
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June 10, 2018
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June 11, 2018
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June 12, 2018
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June 13, 2018
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June 14, 2018(1 event)
Towards a control-theory approach for minimizing unused grid resources, by Agustín Yabo (Master 2, Datamove + Ctrl-A)Towards a control-theory approach for minimizing unused grid resources, by Agustín Yabo (Master 2, Datamove + Ctrl-A) – HPC systems are facing more and more variability in their behavior, related to e.g., performance and power consumption, and the fact that they are less predictable requires more runtime management. This can be done in an Autonomic Management feedback loop, in response to monitored information in the systems, by analysis of this data and utilization of the results in order to activate appropriate system-level or application-level feedback mechanisms (e.g., informing schedulers, down-clocking CPUs). Bat. IMAG, 206 |
June 15, 2018
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June 16, 2018
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June 17, 2018
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June 18, 2018
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June 19, 2018
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June 20, 2018
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June 21, 2018(2 events)
Pré-soutenances M2R DATAMOVE/POLARISPré-soutenances M2R DATAMOVE/POLARIS –
Bâtiment IMAG (206) A Flexible Distributed Optimization Scheme with Asynchronous, Scarse, and Sparse Communications, by Franck Iutzeler (LJK)A Flexible Distributed Optimization Scheme with Asynchronous, Scarse, and Sparse Communications, by Franck Iutzeler (LJK) – We present an asynchronous algorithm for distributed convex optimization when the objective writes a sum of smooth functions, local to each worker, and a non-smooth function. This kind of problem typically appears when learning over distributed data. Unlike many existing methods, our algorithm is adjustable to various levels of communication cost, delays, machines computational power. Moreover, for L1-regularized problems, this algorithm identifies near-optimal sparsity patterns and leverages on it to improve the efficiency of communications. Bat. IMAG, 306 |
June 22, 2018(2 events)
Pré-soutenances M2R DATAMOVE/POLARISPré-soutenances M2R DATAMOVE/POLARIS –
Bâtiment IMAG (206) Pré-soutenance de thèse de Benoit VinotPré-soutenance de thèse de Benoit Vinot – Conception d'un système d'information distribué pour la conduite des flexibilités dans un réseau de distribution électrique: modélisation, simulation et implémentation Résumé français : Le secteur industriel de l'énergie, et les réseaux électriques en particulier, rendent à nos sociétés modernes d'immenses services dont nous ne pouvons plus nous passer. Ils présentent aussi, hélas, un certain nombre de graves inconvénients, notamment en matière d'impact environnemental. Ces inconvénients apparaissent aujourd'hui comme inacceptables; le secteur de l'énergie s'efforce donc actuellement de les amoindrir autant que possible, dans le cadre de ce qu'on appelle la transition énergétique. Outre d'indispensables efforts en matière de sobriété et d'efficacité énergétique, deux grands axes d'amélioration se dessinent: d'une part, le remplacement progressif de certains moyens de production L'intégration au réseau électrique de ces nouveaux types de dispositifs pose cependant des difficultés techniques considérables, qui motivent depuis le début des années 2000 de nombreux travaux sur le thème de ce que l'on appelle aujourd'hui les "smart grids": des réseaux électriques compatibles avec les exigences de Parmi les difficultés susmentionnées, qui limitent la capacité d'accueil du réseau, figurent les congestions, c'est-à-dire les limites physiques à la puissance que l'on peut faire transiter d'un point à un autre sur une infrastructure donnée. C'est à la gestion des congestions que nos travaux sont consacrés. À ce sujet, la question L'objet de cette thèse est de participer à l'élaboration des outils conceptuels et informatiques qui nous permettront de répondre à la question fondamentale ci-dessus. Nos travaux portent ainsi sur la question de la modélisation des réseaux de distribution d'électricité "flexibles", et sur l'implémentation concrète des modèles retenus sous forme d'un logiciel de simulation ad hoc, parfaitement adapté à l'étude de ce type de réseaux. Abstract : The energy sector and the electrical networks in particular, provide great and indispensable services to our modern societies. Unfortunately, they also bring some serious drawbacks, especially with regard to the environment. These drawbacks are becoming more and more unacceptable; that is why the energy sector is In addition to mandatory efforts in terms of energy efficiency and sobriety, two major directions of improvement have been identified: on the one hand, the progressive replacement of some conventional power plants with renewable production units; and on the other hand, the transfer of several non-electrical usages towards electricity --- in particular in the area of mobility. The integration of these new devices into electrical networks raise new technical challenges which, since the early 2000s, have been driving a lot of work about so-called "smart grids": electrical networks compatible with the requirements of the energy transition, ie. able to host new devices like photovoltaic solar panels and charging stations for electric vehicles, notably through the increasing usage of new information and communications technologies. Among the difficulties mentioned above, which limit the hosting capacity of the network, there are congestions ie physical constraints limiting the amount of power that may be transmitted through a given infrastructure. Our work is devoted to the management of congestions. The fundamental issue thereon is to define a sequence of decisions, computations, communications and in fine actions that allows to move from a constrained situation on the electrical distribution network, to a situation in which the action of local flexibilities has lifted the constraint; in other words, to a situation where increasing or decreasing local generation and/or consumption, or taking some other control action, relieved the network. The aim of this thesis is to contribute to the development of conceptual and computing tools that will allow us to answer the fundamental aforementioned issue. Our work thus deals with the modelling of flexible electrical distribution networks, and with the tangible implementation of selected models in the form of Bâtiment IMAG Saint-Martin-d'Hères, 38400 France |
June 23, 2018
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June 24, 2018
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June 25, 2018
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June 26, 2018
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June 27, 2018
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June 28, 2018(1 event)
Real-Time Scheduling Policy Selection using Machine Learning by Raphael Camargo(Sao Paulo)Real-Time Scheduling Policy Selection using Machine Learning by Raphael Camargo(Sao Paulo) – We present a real-time scheduling policy selection algorithm, which takes as input the running queue job characteristics and machine states. We evaluated the use of logistic regression and support vector machines to perform the mapping from queue and machine state to selected scheduling policy. The machine learning algorithms are trained and evaluated using simulations configured using HPC platform traces. When selecting among 5 (five) scheduling policies and using SVM with polynomial kernel, we obtained an accuracy above 80%, when compared to the best possible selection. When simulating the online real-time selection of policies for a period of one year, the method had a performance between selecting the best possible selection of policies and random selection, when considering the mean queue waiting time. Bâtiment IMAG (206) |
June 29, 2018
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June 30, 2018
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JulyJuly 1, 2018 |