Publication Details
Title: Characterizing the Variability of Arrival Processes with Indices of Dispersion
Author: R. Gusella
Group: ICSI Technical Reports
Date: September 1990
PDF: http://www.icsi.berkeley.edu/pubs/techreports/tr-90-051.pdf
Overview:
We propose to characterize the burstiness of packet arrival processes with indices of dispersion for intervals and for counts. These indices, which are functions of the variance of intervals and counts, are relatively straightforward to estimate and convey much more information than simpler indices, such as the coefficient of variation, that are often used to describe burstiness quantitatively. We define and evaluate the indices of dispersion for some of the simple analytical models that are frequently used to represent highly variable processes. We then estimate the indices for a number of measured point processes which were generated by workstations communicating to file servers over a local-area network. We show that nonstationary components in the measured packet arrival data distort the shape of the indices and propose ways to handle nonstationary data. Finally, to show how to incorporate measures of variability into analytical models and to offer an example of how to model our measured packet arrival processes, we describe a fitting procedure based on the index of dispersion for counts for the Markov-modulated Poisson process.
Bibliographic Information:
ICSI Technical Report TR-90-051
Bibliographic Reference:
R. Gusella. Characterizing the Variability of Arrival Processes with Indices of Dispersion. ICSI Technical Report TR-90-051, September 1990
Author: R. Gusella
Group: ICSI Technical Reports
Date: September 1990
PDF: http://www.icsi.berkeley.edu/pubs/techreports/tr-90-051.pdf
Overview:
We propose to characterize the burstiness of packet arrival processes with indices of dispersion for intervals and for counts. These indices, which are functions of the variance of intervals and counts, are relatively straightforward to estimate and convey much more information than simpler indices, such as the coefficient of variation, that are often used to describe burstiness quantitatively. We define and evaluate the indices of dispersion for some of the simple analytical models that are frequently used to represent highly variable processes. We then estimate the indices for a number of measured point processes which were generated by workstations communicating to file servers over a local-area network. We show that nonstationary components in the measured packet arrival data distort the shape of the indices and propose ways to handle nonstationary data. Finally, to show how to incorporate measures of variability into analytical models and to offer an example of how to model our measured packet arrival processes, we describe a fitting procedure based on the index of dispersion for counts for the Markov-modulated Poisson process.
Bibliographic Information:
ICSI Technical Report TR-90-051
Bibliographic Reference:
R. Gusella. Characterizing the Variability of Arrival Processes with Indices of Dispersion. ICSI Technical Report TR-90-051, September 1990