Scheduling policies for real-time and non-real-time traffic in a statistical multiplexer

The performance of several policies for scheduling real-time and non-real-time messages in a statistical multiplexer is examined. The performance metric for the real-time traffic is the percentage of messages not transmitted within their deadlines; the performance metric for the non-real-time traffic is the average delay. The scheduling policies are: (1) first-come first-served (FCFS); (2) head of the line priority, in which real-time packets are given priority; (3) minimum-laxity threshold (MLT) policy; and (4) queue-length threshold (QLT) policy. Under the MLT policy, priority is given to the real-time traffic when the minimum laxity is below some threshold. The QLT policy gives priority to the non-real-time traffic whenever the number of queued non-real-time packets is above some threshold. Results show that the FCFS policy causes relatively high losses for the real-time traffic while providing relatively low message delays for the non-real-time traffic; the converse holds true for the strict priority discipline. Both the MLT and QLT disciplines allow the designer to explicitly trade off the performance realized by each traffic class by using an appropriately chosen value for the threshold parameter. Little difference is observed in the performance tradeoffs available, so it is concluded that the QLT policy is more practical, as it is simpler to implement.<<ETX>>

[1]  V. Ramaswami,et al.  Algorithmic Analysis of a Dynamic Priority Queue , 1982 .

[2]  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..

[3]  Marcel F. Neuts,et al.  Matrix-analytic methods in queuing theory☆ , 1984 .

[4]  Y. Lim,et al.  Analysis of a delay-dependent priority discipline in a multi-class traffic packet switching node , 1988, IEEE INFOCOM '88,Seventh Annual Joint Conference of the IEEE Computer and Communcations Societies. Networks: Evolution or Revolution?.

[5]  Keith W. Ross,et al.  Optimal priority assignment with hard constraint , 1986 .

[6]  Joseph D. Langford,et al.  Models for analysis of packet voice communications systems , 1986, IEEE J. Sel. Areas Commun..

[7]  Christos G. Cassandras,et al.  Optimal scheduling of two competing queues with blocking , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[8]  Anthony S. Acampora,et al.  The Knockout Switch: A Simple, Modular Architecture for High-Performance Packet Switching , 1987, IEEE J. Sel. Areas Commun..

[9]  Keith W. Ross,et al.  Optimal multiplexing of heterogeneous traffic with hard constraint , 1986, SIGMETRICS '86/PERFORMANCE '86.

[10]  Mischa Schwartz,et al.  Optimal fixed frame multiplexing in integrated line- and packet-switched communication networks , 1982, IEEE Trans. Inf. Theory.

[11]  Bart W. Stuck,et al.  A Computer and Communication Network Performance Analysis Primer (Prentice Hall, Englewood Cliffs, NJ, 1985; revised, 1987) , 1987, Int. CMG Conference.

[12]  Izhak Rubin,et al.  Performance boundaries for prioritized multiplexing systems , 1987, IEEE Trans. Inf. Theory.

[13]  Anthony Ephremides,et al.  Optimal switching of voice and data at a network node , 1987, 26th IEEE Conference on Decision and Control.

[14]  Don Towsley,et al.  The Analysis of a Statistical Multiplexer with Nonindependent Arrivals and Errors , 1980, IEEE Trans. Commun..