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Modeling Grid Job Time Properties

Modeling Grid Job Time Properties. Lovro Ilijašić Lorenza Saitta University of Eastern Piedmont, Italy. Grid Observatory. The Grid Observatory cluster of EGEE – the scientific view Data collection, analysis of behaviour and usage 20 months of data, more than 28 million jobs

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Modeling Grid Job Time Properties

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  1. Modeling Grid JobTime Properties Lovro Ilijašić Lorenza Saitta University of Eastern Piedmont, Italy

  2. Grid Observatory • The Grid Observatory cluster of EGEE – the scientific view • Data collection, analysis of behaviour and usage • 20 months of data, more than 28 million jobs • Development of models • Grid is more than just a sum of its parts Modeling Grid JobTime Properties

  3. Emergent Behaviour Properties that are apparent only on higher levels of organization and are not present on the lower ones Emergent Behaviour is observable on all levels of reality Modeling Grid Job Time Properties

  4. Power Law Pareto distribution Zipf’s law 80-20 rule Self similarity Modeling Grid Job Time Properties

  5. Degree Distributions In- and out-degree distributions: How users connect (use) CEs Weighted degrees: Distribution of number of jobs Modeling Grid Job Time Properties

  6. Job Lifecycle Analysis Modeling Grid Job Time Properties

  7. Distributions of Job Lengths Modeling Grid Job Time Properties

  8. Distributions in log-log scale Modeling Grid Job Time Properties

  9. Power-law vs. Log-normal Power-law: preferential attachment Power-law: optimization of the average amount of information per unit transmission cost Power-law: monkeys typing randomly Probabilities of letters not equal: power-law or log-normal? Modeling Grid Job Time Properties

  10. Log-normal vs. Power-law Log-normal: multiplicative processes At each step, the event (Xt) may grow or shrink, according to a random variable Ft: Xt = Ft Xt-1 Multiplicative models can also generate Pareto distribution if there is not a minimum size of event. Otherwise it is log-normal Intermixing of generations, where t is random variable, leads to power law. Modeling Grid Job Time Properties

  11. Log-normal Fitted Distributions Modeling Grid Job Time Properties

  12. Alternatives Double Pareto distribution Double Pareto log-normal distribution More distribution parameters that allow better fitting Modeling Grid Job Time Properties

  13. Modeling Grid JobTime Properties Lovro Ilijašić Lorenza Saitta University of Eastern Piedmont, Italy

  14. Modeling Grid Job Time Properties

  15. Complex Networks Complex Networks – Complex systems represented as graphs Gathered experiences from Physics, Chemistry, Biology, Computer Science, Sociology, Economics… Representing Grid as a Complex Network 20 months of log data, more than 28 million jobs Edges representing jobs go from Users to CEs Modeling Grid Job Time Properties

  16. Number of jobs for each user Modeling Grid Job Time Properties

  17. Modeling Grid Job Time Properties

  18. Modeling Grid Job Time Properties

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