Investigating dependence in packet queues with the index of dispersion for work

The authors continue an investigation of the way diverse traffic from different data applications affects the performance of packet queues. This traffic often exhibits significant dependence among successive interarrival times, among successive service times, and between interarrival times and service times, which can cause a significant degradation of performance under heavy loads (and often even under moderate loads). This dependence and its effects on performance (specifically, the mean steady-state workload) are partially characterized here by the cumulative correlations in the total input process of work, which is referred to as the index of dispersion for work (IDW). The authors evaluate approximations for the mean steady-state workload based on the IDW by making comparisons with computer simulations. >

[1]  Raj Jain,et al.  Packet Trains-Measurements and a New Model for Computer Network Traffic , 1986, IEEE J. Sel. Areas Commun..

[2]  David R. Cox,et al.  The statistical analysis of series of events , 1966 .

[3]  D. Iglehart,et al.  Multiple channel queues in heavy traffic. II: sequences, networks, and batches , 1970, Advances in Applied Probability.

[4]  Ward Whitt,et al.  Characterizing Superposition Arrival Processes in Packet Multiplexers for Voice and Data , 1986, IEEE J. Sel. Areas Commun..

[5]  Ward Whitt,et al.  Some Useful Functions for Functional Limit Theorems , 1980, Math. Oper. Res..

[6]  Ward Whitt,et al.  A Queueing Network Analyzer for Manufacturing , 1989 .

[7]  Shaler Stidham,et al.  The Relation between Customer and Time Averages in Queues , 1980, Oper. Res..

[8]  Ichiro Ide,et al.  Superposition of Interrupted Poisson Processes and Its Application to Packetized Voice Multiplexers , 1988 .

[9]  D. Burman,et al.  Asymptotic analysis of a queueing model with bursty traffic , 1983, The Bell System Technical Journal.

[10]  Susan L. Albin,et al.  Approximating a Point Process by a Renewal Process, II: Superposition Arrival Processes to Queues , 1984, Oper. Res..

[11]  G. F. Newell APPROXIMATIONS FOR SUPERPOSITION ARRIVAL PROCESSES IN QUEUES , 1984 .

[12]  Ward Whitt,et al.  An Interpolation Approximation for the Mean Workload in a GI/G/1 Queue , 1989, Oper. Res..

[13]  Ronald W. Wolff,et al.  Poisson Arrivals See Time Averages , 1982, Oper. Res..

[14]  H. Heffes,et al.  A class of data traffic processes — covariance function characterization and related queuing results , 1980, The Bell System Technical Journal.

[15]  David M. Lucantoni,et al.  A Markov Modulated Characterization of Packetized Voice and Data Traffic and Related Statistical Multiplexer Performance , 1986, IEEE J. Sel. Areas Commun..

[16]  W. Whitt,et al.  The Queueing Network Analyzer , 1983, The Bell System Technical Journal.

[17]  Vincent Hodgson,et al.  The Single Server Queue. , 1972 .

[18]  S.-Q. Li Traffic characterization for integrated services networks , 1990, IEEE Trans. Commun..

[19]  David M. Lucantoni,et al.  Traffic smoothing effects of bit dropping in a packet voice multiplexer , 1989, IEEE Trans. Commun..

[20]  W. Whitt Queues with superposition arrival processes in heavy traffic , 1985 .

[21]  Ward Whitt,et al.  Dependence in packet queues , 1989, IEEE Trans. Commun..

[22]  Ward Whitt,et al.  Measurements and approximations to describe the offered traffic and predict the average workload in a single-server queue , 1989, Proc. IEEE.

[23]  A. Descloux CONTENTION PROBABILITIES IN PACKET SWITCHING NETWORKS WITH STRUNG INPUT PROCESSES , 1988 .

[24]  Ward Whitt,et al.  Approximating a Point Process by a Renewal Process, I: Two Basic Methods , 1982, Oper. Res..

[25]  Martin I. Reiman,et al.  An Interpolation Approximation for Queueing Systems with Poisson Input , 1988, Oper. Res..

[26]  M. Bartlett The Spectral Analysis of Point Processes , 1963 .