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Adaptive Random Sampling for Load Change Detection Adaptive Random Sampling for Load Change Detection Adaptive Random Sampling for Load Change Detection
| Content Provider | Semantic Scholar |
|---|---|
| Author | Park, Jaesung Choi, Baek-Young Zhang, Zhi-Li |
| Copyright Year | 2002 |
| Abstract | Abst ract Timely detection of changes in traac is critical for initiating appropriate traac engineering mechanisms. Accurate measurement of traac is an essential step towards change detection and traac engineering. However, precise traac measurement involves inspecting every packet traversing a link, resulting in signiicant overhead, particularly on routers with high speed links. Sampling techniques for traac estimation are proposed as a way to limit the measurement overhead. Since the eecacy of change detection depends on the accuracy of traac estimation, it is necessary to control error in estimation due to sampling. In this paper, we address the problem of bounding sampling error within a pre-speciied tolerance level. We derive a relationship between the number of samples, the accuracy of estimation and the squared coeecient of variation of packet size distribution. Based on this relationship, we propose an adaptive random sampling technique that determines the minimum sampling probability adaptively according to traac dynamics. Using real network traac traces, we show that the proposed adaptive random sampling technique indeed produces the desired accuracy, while also yielding signiicant reduction in the amount of traac samples. We also investigate the impact of sampling errors on the performance of load change detection. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.cs.umn.edu/tech_reports_upload/tr2001/01-041.pdf |
| Alternate Webpage(s) | https://www.cs.umn.edu/sites/cs.umn.edu/files/tech_reports/01-041.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
