A stratified traffic sampling methodology for seeing the big picture ...
This work explores the use of statistical techniques, namely stratified sampling and cluster analysis, as powerful tools for deriving traffic properties at the flow level. Our results show that the adequate selection of samples leads to significant improvements allowing further important statistical analysis. Although stratified sampling is a well-known technique, the way we classify the data ...
Request PDF | A stratified traffic sampling methodology for seeing the big picture | This work explores the use of statistical techniques, namely stratified sampling and cluster analysis, as ...
A stratified traffic sampling methodology for seeing the big picture
This work explores the use of statistical techniques, namely stratified sampling and cluster analysis, as powerful tools for deriving traffic properties at the flow level. Our results show that the adequate selection of samples leads to significant improvements allowing further important statistical analysis. Although stratified sampling is a well-known technique, the way we classify the data ...
This work explores the use of statistical techniques, namely stratified sampling and cluster analysis, as powerful tools for deriving traffic properties at the flow level by evaluating two partitioning clustering methods and showing that using flow sizes to divide the population can obtain accurate estimates for both size and flow durations. This work explores the use of statistical techniques ...
Computer Networks
Research articleFull text access A stratified traffic sampling methodology for seeing the big picture Stênio Fernandes, Carlos Kamienski, Judith Kelner, Dênio Mariz, Djamel Sadok Pages 2677-2689 View PDF Article preview
Traffic monitoring is important for network engineering. Commonly used monitoring tools lack scalability. Sampling is a proven strategy to deal with high - volume network traffic data. This work aims to introduce a new flow classification methodology using stratified sampling and cluster analysis to reduce the amount of traffic data needed for characterizing traffic flows.
Overview of A Stratified Traffic Sampling Methodology For Seeing The Big Picture
Fernandes, S., Kamienski, C., Kelner, J., Mariz, D., & Sadok, D. (2008). A stratified traffic sampling methodology for seeing the big picture . Computer Networks, 52 ...
Article [19] shows how the estimation accuracy can be improved without increasing the size of the sample using stratified sampling techniques. Throughout the article are investigated different stratification strategies with regard to the possible reduction of the number of packages sampled.…"
An Investigation of the Application of Stratified Sampling in Probe ...
A methodology for application of stratified sampling for probe-based traffic monitoring is developed and implemented using a heavily traveled suburban traffic network simulation as a case study. Also, the authors discuss results of the implementation and the future direction of research.
The authors conclude that stratified sampling is a method well-suited for probe-based traffic monitoring. By choosing the stratification variables, varying the number and boundaries of strata, and using different methods to allocate sample sizes to strata, multiple stratified sampling designs can be developed.