摘要
Performance of load balancing scheduling policies in Web server cluster systems is greatly impacted by the characteristics of workload. Based on the analysis of the load characteristics for scheduling algorithm, a prediction-based adaptive load balancing model (RR-MMMCS-A-P) is proposed in this paper. Monitoring the workload characteristics and its variation, the arrival rate and the size of the follow-up request are predicted by RR-MMMCS-A-P and rapid adjustment of the corresponding parameters to balance the load between servers. Experiments have shown that compared with CPU-based and CPU-memory based scheduling strategy, RR-MMMCS-A-P have better performance in reducing average response time for both calculation-intensive and data-intensive jobs.
- 出版日期2012
- 单位郑州大学