Name
Abstract | ||
|---|---|---|
This paper presents an analysis of the performance effects of burstiness in multi-tiered systems. We introduce a compact characterization of burstiness based on autocorrelation that can be used in capacity planning, performance prediction, and admission control. We show that if autocorrelation exists either in the arrival or the service process of any of the tiers in a multi-tiered system, then autocorrelation propagates to all tiers of the system. We also observe the surprising result that in spite of the fact that the bottleneck resource in the system is far from saturation and that the measured throughput and utilizations of other resources are also modest, user response times are very high. When autocorrelation is not considered, this underutilization of resources falsely indicates that the system can sustain higher capacities. We examine the behavior of a small queuing system that helps us understand this counter-intuitive behavior and quantify the performance degradation that originates from autocorrelated flows. We present a case study in an experimental multi-tiered Internet server and devise a model to capture the observed behavior. Our evaluation indicates that the model is in excellent agreement with experimental results and captures the propagation of autocorrelation in the multi-tiered system and resulting performance trends. Finally, we analyze an admission control algorithm that takes autocorrelation into account and improves performance by reducing the long tail of the response time distribution. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.peva.2007.06.016 | Performance Evaluation |
Keywords | DocType | Volume |
stochastic characteristic,capacity planning,workload characterization,workload characterization study,performance trend,autocorrelation propagates,resource management policy,autocorrelation,general problem,multi-tiered systems,counter-intuitive behavior,admission control,multi-tiered system,observed behavior,autocorrelated flow,bottleneck identification,performance degradation,queuing networks,service time,performance effect,experimental multi-tiered internet server,performance impact,performance prediction,service level,resource manager | Journal | 64 |
Issue | ISSN | Citations |
9-12 | Performance Evaluation | 44 |
PageRank | References | Authors |
2.03 | 25 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ningfang Mi | 1 | 664 | 47.66 |
| Qi Zhang | 2 | 414 | 22.77 |
| Alma Riska | 3 | 683 | 48.63 |
| Evgenia Smirni | 4 | 1857 | 161.97 |
| Erik Riedel | 5 | 1037 | 142.99 |