Title :
A probabilistic analysis of admission control policies for deadline-driven service disciplines
Author :
Simon, Robert ; Znati, Taieb
Author_Institution :
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Abstract :
In a communication network, deadline-driven packet scheduling policies provide real-time performance guarantees by associating a deadline with each packet and then transmitting packets according to increasing orders of deadlines. New connections must undergo an admission control test before they are accepted for service. The paper develops a probabilistic model to analyze admission control methods for the general class of non-preemptive deadline-oriented packet scheduling policies. The authors present a general-purpose schedulability theorem for non-preemptive earliest deadline first packet scheduling. They then show how to use a stochastic knapsack to compute acceptance probabilities. A large-scale simulation study demonstrates that the method provides highly accurate predictions of acceptance rates for multiple types of traffic requests
Keywords :
packet switching; probability; queueing theory; real-time systems; scheduling; simulation; stochastic processes; telecommunication congestion control; telecommunication traffic; acceptance probabilities; acceptance rates; admission control policies; admission control test; communication network; deadline-driven packet scheduling policies; deadline-driven service disciplines; general-purpose schedulability theorem; large-scale simulation study; new connections; nonpreemptive deadline-oriented packet scheduling policies; nonpreemptive earliest deadline first packet scheduling; packet transmission; probabilistic analysis; real-time performance guarantees; stochastic knapsack; traffic requests; Admission control; Communication networks; Computational modeling; Large-scale systems; Predictive models; Processor scheduling; Scheduling algorithm; Stochastic processes; Testing; Traffic control;
Conference_Titel :
Simulation Symposium, 1998. Proceedings. 31st Annual
Conference_Location :
Boston, MA
Print_ISBN :
0-8186-8418-6
DOI :
10.1109/SIMSYM.1998.668463