Difference between revisions of "Open Problems:13"
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When processing very fast streams, it is not feasible to run a streaming algorithm on the entire stream, even one that can process each element in $O(1)$ time. Rather it is necessary to sample from the stream and to process the sub-stream using a streaming algorithm. For standard problems such as estimating $F_0$, how does the sub-sampling affect that the accuracy of the streaming algorithms? How should the sampling rate and the per-element time-complexity of a streaming algorithm be traded-off to achieve optimal results? | When processing very fast streams, it is not feasible to run a streaming algorithm on the entire stream, even one that can process each element in $O(1)$ time. Rather it is necessary to sample from the stream and to process the sub-stream using a streaming algorithm. For standard problems such as estimating $F_0$, how does the sub-sampling affect that the accuracy of the streaming algorithms? How should the sampling rate and the per-element time-complexity of a streaming algorithm be traded-off to achieve optimal results? | ||
Revision as of 05:08, 16 November 2012
| Suggested by | Yossi Matias |
|---|---|
| Source | Kanpur 2006 |
| Short link | https://sublinear.info/13 |
When processing very fast streams, it is not feasible to run a streaming algorithm on the entire stream, even one that can process each element in $O(1)$ time. Rather it is necessary to sample from the stream and to process the sub-stream using a streaming algorithm. For standard problems such as estimating $F_0$, how does the sub-sampling affect that the accuracy of the streaming algorithms? How should the sampling rate and the per-element time-complexity of a streaming algorithm be traded-off to achieve optimal results?
Another way to formalize this question, suggested by Muthukrishnan, is in terms of what part of the stream to skip and which to stream. A formal definition of the model and algorithms for estimating $F_2$ and others can be found in [BhattacharyyaMMY-07].
