Grid Observatory

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The Grid Observatory cluster of Enabling Grids for E-sciencE (EGEE) collects, publishes and analyses data on the behaviour of the EGEE grid. Its aim is to develop a scientific view of the dynamics of grid behaviour and usage. This helps both computer science researchers working in the field of autonomic computing and grid developers seeking to improve reliability, stability and performance.
Grid infrastructures, as well as data centers, consist of a variety of hardware and software components, which are, in their own right, complex systems. Grids federate independently managed resources, and answer the requests of communities with evolving behaviour patterns.
With extensive monitoring facilities already in place, EGEE grid offers an unprecedented opportunity to observe, and gain understanding of, new computing practices of e-Science.


Activity leader Cécile Germain-Renaud

Ongoing actions

  • Data Collection and Publication
    • Integration of Dashboard data
    • Collection of LFC logs
    • Building ontologies (with MIS and LPC)
  • Models of the grid dynamics
    • Evaluation of the performance of the estimated response time (request from JRA1)
    • Real-time clustering
    • Multi-objective scheduling
  • Dissemination, collaborations


Istanbul community meeting September 2008
London team meeting June 2008
CEI defense May 2008
Portal design May 2008
Analysis meeting November 2007
Budapest session October 2007
Budapest group meeting October 2007
Analysis kickoff meeting October 2007


Internal mailing list
Collaboration mailing list
The Grid Observatory infosheet
Poster at Digiteo 1st annual forum
Requirements from other EGEE activities
Technical documentation
The Grid Ontology action (in French)


Presentation at the joint session From grid monitoring to analysis at OGF/UF Catania


Xiangliang Zhang, Michele Sebag, Cecile Germain-Renaud. Multi-scale grid monitoring with job stream mining. In CCGrid 2009 pdf

Germain-Renaud C., Perez J., Kegl B., Loomis C. Grid Differentiated Services: a Reinforcement Learning Approach In 8th IEEE International Symposium on Cluster Computing and the Grid (2008) pdf

Julien Perez , Cecile Germain-Renaud , Balazs Kegl , C. Loomis Utility-based Reinforcement Learning for Reactive Grids In The 5th IEEE International Conference on Autonomic Computing (2008) pdf

Xiangliang Zhang, Cyril Furtlehner, Michele Sebag Distributed and Incremental Clustering Based on Weighted Affinity Propagation In the fourth European Starting AI Researcher Symposium (STAIRS) (2008) pdf

Xiangliang Zhang, Cyril Furtlehner, Michele Sebag Frugal and Online Affinity Propagation In Conference francophone sur l'Apprentissage (CAP) (2008) inria-00287381, version 1 pdf

Xiangliang Zhang, Michele Sebag, Cecile Germain Le modelage des travaux d'un Systeme de Grille In 16th congr sefrancophone AFRIF-AFIA Reconnaissance des Formes et Intelligence Artificielle (RFIA) (2008) pdf

Xiangliang Zhang, Cyril Furtlehner, Michele Sebag Data Streaming with Affinity Propagation In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (2008) pdf

-- CharlesLoomis - 22 Jul 2008

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Topic revision: r6 - 2009-03-14 - CecileGermainR
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