CPU Load Prediction Model for Distributed Computing

Kadda Beghdad Bey , Farid Benhammadi , Aicha Mokhtari , Zahia Guessoum (1)

1 SMA - Systèmes Multi-Agents

Resources performance forecasting constitutes one of particularly significant research problems in distributed computing. To ensure an adequate use of the computing resources in a metacomputing environment, there is a need for effective and flexible forecasting method to determine the available performance on each resource. In this paper, we present a modeling approach to estimating the future value of CPU load. This modeling prediction approach uses the combination of adaptive network-based fuzzy inference systems (ANFIS) and the clustering process applied on the CPU Load time series. Experiments show the feasibility and effectiveness of this approach that achieves significant improvement and outperforms the existing CPU load prediction models reported in literature.

Domaines: Informatique [cs]

Kadda Beghdad Bey, Farid Benhammadi, Aicha Mokhtari, Zahia Guessoum. CPU Load Prediction Model for Distributed Computing. 8th International Symposium on Parallel and Distributed Computing, Jun 2009, Lisbon, Portugal. pp.39-45, ⟨10.1109/ISPDC.2009.8⟩. ⟨hal-01294978⟩