An enhanced load balancing mechanism based on deadline control on GridSim
Future Generation Computer Systems
A pattern fusion model for multi-step-ahead CPU load prediction
Journal of Systems and Software
| Hi-index | 0.00 |
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.