Performance analysis of FCFS and improved FCFS scheduling algorithms for dynamic real-time computer systems

A study is made of the performance of FCFS (first-come, first-served) and improved FCFS scheduling algorithms for dynamic real-time computer systems in which tasks arrive as a random process and each task has a laxity specifying the maximum time a task can wait for the service. The general solution for M/M/1 systems in which the FCFS or an improved FCFS scheduling algorithm is used is obtained. In particular, explicit expressions for the unfinished work distribution, the task loss ratio, and the CPU utilization for M/M/1+M systems are derived. The last M in M/M/1+M means that the task laxity is exponentially distributed. The steady-state performance of those systems depends not only on the offered load rho (as in the non-real-time arena), but also on the normalized mean laxity, which is equal to the mean laxity divided by the mean service time. An analysis also shows that using the improved FCFS scheduling algorithm results in significant improvement over using the original FCFS algorithm. In many circumstances, the improved FCFS has almost identical or very similar performance to that of the minimum-laxity-first (MLF) algorithm, which has been shown to be optimal. The advantage of the improved FCFS algorithm is that it takes O(1) time while the MLF algorithm needs O(log n) time.<<ETX>>

[1]  Krithi Ramamritham,et al.  Virtual Time CSMA Protocols for Hard Real-Time Communication , 1987, IEEE Transactions on Software Engineering.

[2]  Donald F. Towsley,et al.  Optimal scheduling policies for a class of queues with customer deadlines to the beginning of service , 1988, JACM.

[3]  Krithi Ramamritham,et al.  Scheduling Tasks with Resource Requirements in Hard Real-Time Systems , 1987, IEEE Transactions on Software Engineering.

[4]  G. Pile Étude des délais d'attente des aéronefs à l'atterrissage , 1955 .

[5]  Krithi Ramamritham,et al.  Hard Real-Time Systems , 1988 .

[6]  Krithi Ramamritham,et al.  Meta-Level Control in Distributed Real-Time Systems , 1987, ICDCS.

[7]  Krithi Ramamritham,et al.  Dynamic Task Scheduling in Distributed Real-Time Systems , 1984, ICDCS.

[8]  D. Y. Barrer Queuing with Impatient Customers and Indifferent Clerks , 1957 .

[9]  Krithi Ramamritham,et al.  Dynamic Task Scheduling in Hard Real-Time Distributed systems , 1984, IEEE Software.

[10]  James F. Kurose,et al.  Load Sharing in Soft Real-Time Distributed Computer Systems , 1987, IEEE Transactions on Computers.

[11]  R. Haugen,et al.  Queueing Systems with Stochastic Time out , 1980, IEEE Trans. Commun..

[12]  M. Thomas Queueing Systems. Volume 1: Theory (Leonard Kleinrock) , 1976 .

[13]  Robert E. Stanford,et al.  Reneging Phenomena in Single Channel Queues , 1979, Math. Oper. Res..

[14]  Suresh Singh,et al.  A Study of Quasi-Dynamic Load Sharing in Soft Real-Time Distributed Computer Systems , 1986, RTSS.

[15]  F. Baccelli,et al.  Single-server queues with impatient customers , 1984, Advances in Applied Probability.

[16]  Donald F. Towsley,et al.  A Performance Analysis of Minimum Laxity and Earliest Deadline Scheduling in a Real-Time System , 1989, IEEE Trans. Computers.

[17]  L. Takács Investigation of waiting time problems by reduction to Markov processes , 1955 .

[18]  François Baccelli,et al.  ON QUEUES WITH IMPATIENT CUSTOMERS. , 1981 .

[19]  Bezalel Gavish,et al.  The Markovian Queue with Bounded Waiting time , 1977 .