Toward Behavioral Modeling of a Grid System: Mining the Logging and Bookkeeping files

International audienceGrid systems are complex heterogeneous systems, and their modeling constitutes a highly challenging goal. This paper is interested in modeling the jobs handled by the EGEE grid, by mining the Logging and Bookkeeping files. The goal is to discover meaningful job clusters, going beyond the coarse categories of ”successfully terminated jobs” and ”other jobs”. The presented approach is a threestep process: i) Data slicing is used to alleviate the job heterogeneity and afford discriminant learning; ii) Constructive induction proceeds by learning discriminant hypotheses from each data slice; iii) Finally, double clustering is used on the representation built by constructive induction; the clusters are fully validated after the stability criteria proposed by Meila (2006). Lastly, the job clusters are submitted to the experts and some meaningful interpretations are foun

Discovering Piecewise Linear Models of Grid Workload

International audienceDespite extensive research focused on enabling QoS for grid users through economic and intelligent resource provisioning, no consensus has emerged on the most promising strategies. On top of intrinsically challenging problems, the complexity and size of data has so far drastically limited the number of comparative experiments. An alternative to experimenting on real, large, and complex data, is to look for well-founded and parsimonious representations. This study is based on exhaustive information about the gLite-monitored jobs from the EGEE grid, representative of a significant fraction of e-science computing activity in Europe. Our main contributions are twofold. First we found that workload models for this grid can consistently be discovered from the real data, and that limiting the range of models to piecewise linear time series models is sufficiently powerful. Second, we present a bootstrapping strategy for building more robust models from the limited samples at hand

The Grid Observatory

International audienceThe goal of the Grid Observatory project (GO) is to contribute to an experimental theory of large grid systems by integrating the collection of data on the behaviour of the flagship European Grid Infrastructure (EGI) and its users, the development of models, and an ontology for the domain knowledge. The GO gives access to a database of grid usage traces available to the wider computer science community without the need of grid credentials. The paper presents the architecture of the digital curation process enacted by the GO and examples of their exploitation.L'objectif du projet Grid Observatoiry (GO) est de contribuer à une théorie expérimentale de systèmes globalisés à grande échelle en intégrant l'acquisition de données sur le comportement de l'infrastructure de la grille européenne phare (EGI) et de ses utilisateurs, avec le développement de modèles, et d'une ontologie du domaine. Le GO donne accès à une base de données des traces d'utilisation de la grille, mise à la disposition de la communauté scientifique. L'article présente l'architecture du processus de conservation numérique adoptée par le GO et des exemples de l'exploitation des traces collectées

The discovery of Halictivirus resolves the Sinaivirus phylogeny.

By providing pollination services, bees are among the most important insects, both in ecological and economical terms. Combined next-generation and classical sequencing approaches were applied to discover and study new insect viruses potentially harmful to bees. A bioinformatics virus discovery pipeline was used on individual Illumina transcriptomes of 13 wild bees from three species from the genus Halictus and 30 ants from six species of the genera Messor and Aphaenogaster. This allowed the discovery and description of three sequences of a new virus termed Halictus scabiosae Adlikon virus (HsAV). Phylogenetic analyses of ORF1, RNA-dependent RNA-polymerase (RdRp) and capsid genes showed that HsAV is closely related to (+)ssRNA viruses of the unassigned Sinaivirus genus but distant enough to belong to a different new genus we called Halictivirus. In addition, our study of ant transcriptomes revealed the first four sinaivirus sequences from ants (Messor barbarus, M. capitatus and M. concolor). Maximum likelihood phylogenetic analyses were performed on a 594 nt fragment of the ORF1/RdRp region from 84 sinaivirus sequences, including 31 new Lake Sinai viruses (LSVs) from honey bees collected in five countries across the globe and the four ant viral sequences. The phylogeny revealed four main clades potentially representing different viral species infecting honey bees. Moreover, the ant viruses belonged to the LSV4 clade, suggesting a possible cross-species transmission between bees and ants. Lastly, wide honey bee screening showed that all four LSV clades have worldwide distributions with no obvious geographical segregation

All-sky search for long-duration gravitational wave transients with initial LIGO

We present the results of a search for long-duration gravitational wave transients in two sets of data collected by the LIGO Hanford and LIGO Livingston detectors between November 5, 2005 and September 30, 2007, and July 7, 2009 and October 20, 2010, with a total observational time of 283.0 days and 132.9 days, respectively. The search targets gravitational wave transients of duration 10-500 s in a frequency band of 40-1000 Hz, with minimal assumptions about the signal waveform, polarization, source direction, or time of occurrence. All candidate triggers were consistent with the expected background; as a result we set 90% confidence upper limits on the rate of long-duration gravitational wave transients for different types of gravitational wave signals. For signals from black hole accretion disk instabilities, we set upper limits on the source rate density between 3.4×10-5 and 9.4×10-4 Mpc-3 yr-1 at 90% confidence. These are the first results from an all-sky search for unmodeled long-duration transient gravitational waves. © 2016 American Physical Society

All-sky search for long-duration gravitational wave transients with initial LIGO

We present the results of a search for long-duration gravitational wave transients in two sets of data collected by the LIGO Hanford and LIGO Livingston detectors between November 5, 2005 and September 30, 2007, and July 7, 2009 and October 20, 2010, with a total observational time of 283.0 days and 132.9 days, respectively. The search targets gravitational wave transients of duration 10-500 s in a frequency band of 40-1000 Hz, with minimal assumptions about the signal waveform, polarization, source direction, or time of occurrence. All candidate triggers were consistent with the expected background; as a result we set 90% confidence upper limits on the rate of long-duration gravitational wave transients for different types of gravitational wave signals. For signals from black hole accretion disk instabilities, we set upper limits on the source rate density between 3.4×10-5 and 9.4×10-4 Mpc-3 yr-1 at 90% confidence. These are the first results from an all-sky search for unmodeled long-duration transient gravitational waves. © 2016 American Physical Society

Search for gravitational waves from Scorpius X-1 in the second Advanced LIGO observing run with an improved hidden Markov model

We present results from a semicoherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to track spin wandering. This search improves on previous HMM-based searches of LIGO data by using an improved frequency domain matched filter, the J-statistic, and by analyzing data from Advanced LIGO's second observing run. In the frequency range searched, from 60 to 650 Hz, we find no evidence of gravitational radiation. At 194.6 Hz, the most sensitive search frequency, we report an upper limit on gravitational wave strain (at 95% confidence) of h095%=3.47×10-25 when marginalizing over source inclination angle. This is the most sensitive search for Scorpius X-1, to date, that is specifically designed to be robust in the presence of spin wandering. © 2019 American Physical Society

Search for Tensor, Vector, and Scalar Polarizations in the Stochastic Gravitational-Wave Background

The detection of gravitational waves with Advanced LIGO and Advanced Virgo has enabled novel tests of general relativity, including direct study of the polarization of gravitational waves. While general relativity allows for only two tensor gravitational-wave polarizations, general metric theories can additionally predict two vector and two scalar polarizations. The polarization of gravitational waves is encoded in the spectral shape of the stochastic gravitational-wave background, formed by the superposition of cosmological and individually unresolved astrophysical sources. Using data recorded by Advanced LIGO during its first observing run, we search for a stochastic background of generically polarized gravitational waves. We find no evidence for a background of any polarization, and place the first direct bounds on the contributions of vector and scalar polarizations to the stochastic background. Under log-uniform priors for the energy in each polarization, we limit the energy densities of tensor, vector, and scalar modes at 95% credibility to Ω0T<5.58×10-8, Ω0V<6.35×10-8, and Ω0S<1.08×10-7 at a reference frequency f0=25 Hz. © 2018 American Physical Society

Towards Non-Stationary Grid Models

International audienceDespite intense research on grid scheduling, differentiated quality of service remains an open question, and no consensus has emerged on the most promising strategy. The difficulties of experimentation might be one of the root causes of this stalling. An alternative to experimenting on real, large, and complex data is to look for well-founded and parsimonious representations, which may also contribute to the a-priori knowledge required for operational Autonomics. The goal of this paper is thus to explore explanatory and generative models rather than predictive ones: is it possible to exhibit and validate consistent models of the grid workload? Most existing work on modeling grid behavior describes grids as complex systems, but assumes stationarity and concludes to some form of long-range dependence. But the physical (economic and sociologic) processes governing the grid behavior dispel the stationarity hypothesis. This paper considers an appealing different class of models: a sequence of stationary processes separated by breakpoints. The model selection question is now defined as identifying the breakpoints and fitting the processes in each segment. Experimenting with data from the EGEE/EGI grid, we found that a non-stationary model can consistently be identified from empirical data, and that limiting the range of models to piecewise affine (autoregressive) time series is sufficiently powerful. We propose and experiment a validation methodology that empirically addresses the current lack of theoretical results concerning the quality of the estimated model parameters. Finally, we present a bootstrapping strategy for building more robust models from the limited samples at hand

Création, mise en place et évaluation d'un carnet de suivi médical destiné à des patients séjournant en altitude

LYON1-BU Santé (693882101) / SudocSudocFranceF