Performance Optimization Based on Analytical Modeling in a Real-Time System with Constrained Time/Utility Functions

We consider a single-processor firm real-time (FRT) system with exponential interarrival and execution times for jobs with relative deadlines following a general distribution. The scheduling policy of the system is first-come first-served (FCFS) and the capacity of the system is arbitrary. This system is subject to an arbitrary-shaped time/utility function (TUF), which determines the accrued utility of each job according to its completion time. It is considered that the system power consumption at different working states is predetermined for each processor speed. We have proposed an exact analytical method for the calculation of specific performance and power-related measures of the system. The resulting analytical formulations for the performance measures are functions of the processor speed and system capacity. These measures are optimized through appropriate selections of the speed using derivatives and the capacity employing numerical search methods. Some experimental results are presented for different unimodal TUFs in systems with deterministic and exponential relative deadlines. For the latter distribution, the results are compared against similar results obtained through simulation for the nonpreemptive earliest-deadline-first (NP-EDF) scheduling policy. The comparisons show that FCFS is superior to NP-EDF for some measures and TUFs.

[1]  Ali Movaghar-Rahimabadi,et al.  A Method for Performance Analysis of Earliest-Deadline-First Scheduling Policy , 2004, DSN.

[2]  Kang G. Shin,et al.  Real-time dynamic voltage scaling for low-power embedded operating systems , 2001, SOSP.

[3]  Alan Burns,et al.  Weakly Hard Real-Time Systems , 2001, IEEE Trans. Computers.

[4]  Eldon Hansen,et al.  Global optimization using interval analysis , 1992, Pure and applied mathematics.

[5]  Alan Jay Smith,et al.  PACE: a new approach to dynamic voltage scaling , 2004, IEEE Transactions on Computers.

[6]  Binoy Ravindran,et al.  Time/utility function decomposition techniques for utility accrual scheduling algorithms in real-time distributed systems , 2005, IEEE Transactions on Computers.

[7]  Peng Li,et al.  Utility Accrual Real-Time Scheduling: Models and Algorithms , 2004 .

[8]  Binoy Ravindran,et al.  Utility Accrual Real-Time Scheduling Under the Unimodal Arbitrary Arrival Model with Energy Bounds , 2007, IEEE Transactions on Computers.

[9]  Binoy Ravindran,et al.  CPU scheduling for statistically-assured real-time performance and improved energy efficiency , 2004, CODES+ISSS '04.

[10]  Binoy Ravindran,et al.  On recent advances in time/utility function real-time scheduling and resource management , 2005, Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC'05).

[11]  D. Y. Barrer.  Queuing with Impatient Customers and Ordered Service , 1957 .

[12]  Binoy Ravindran,et al.  Energy-efficient, utility accrual scheduling under resource constraints for mobile embedded systems , 2004, EMSOFT '04.

[13]  Daniel Mossé,et al.  Value-density algorithms to handle transient overloads in scheduling , 1999, Proceedings of 11th Euromicro Conference on Real-Time Systems. Euromicro RTS'99.

[14]  Hyeonjoong Cho,et al.  Utility Accrual Real-Time Scheduling and Synchronization on Single and Multiprocessors: Models, Algorithms, and Tradeoffs , 2006 .

[15]  Binoy Ravindran,et al.  Energy-efficient, utility accrual real-time scheduling under the unimodal arbitrary arrival model , 2005, Design, Automation and Test in Europe.

[16]  Ali Movaghar-Rahimabadi,et al.  A stochastic DVS-based dynamic power management for soft real-time systems , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[17]  Dennis Shasha,et al.  D/sup over/; an optimal on-line scheduling algorithm for overloaded real-time systems , 1992, [1992] Proceedings Real-Time Systems Symposium.

[18]  Binoy Ravindran,et al.  Time-utility function-driven switched Ethernet: packet scheduling algorithm, implementation, and feasibility analysis , 2004, IEEE Transactions on Parallel and Distributed Systems.

[19]  Binoy Ravindran,et al.  Probabilistic, Real-Time Scheduling of Distributable Threads Under Dependencies in Mobile, Ad Hoc Networks , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[20]  Ali Movaghar.  On queueing with customer impatience until the end of service , 2000, Proceedings IEEE International Computer Performance and Dependability Symposium. IPDS 2000.

[21]  C. D. Locke,et al.  Best-effort decision-making for real-time scheduling , 1986 .

[22]  James W. Layland,et al.  Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment , 1989, JACM.

[23]  Binoy Ravindran,et al.  Utility accrual scheduling under joint utility and resource constraints , 2004, Seventh IEEE International Symposium onObject-Oriented Real-Time Distributed Computing, 2004. Proceedings..

[24]  Ali Movaghar-Rahimabadi,et al.  Non-preemptive earliest-deadline-first scheduling policy: a performance study , 2005, 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[25]  Paul Muhlethaler,et al.  Optimality and non-preemptive real-time scheduling revisited , 1995 .

[26]  Binoy Ravindran,et al.  Utility Accrual Scheduling under Arbitrary Time/Utility Functions and Multi-unit Resource Constraints , 2004 .

[27]  Niraj K. Jha,et al.  Joint dynamic voltage scaling and adaptive body biasing for heterogeneous distributed real-time embedded systems , 2003, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[28]  Rami G. Melhem,et al.  Power-aware scheduling for periodic real-time tasks , 2004, IEEE Transactions on Computers.

[29]  Ken Chen,et al.  A scheduling algorithm for tasks described by Time Value Function , 1996, Real-Time Systems.

[30]  Klara Nahrstedt,et al.  Energy-efficient soft real-time CPU scheduling for mobile multimedia systems , 2003, SOSP '03.

[31]  Rami G. Melhem,et al.  Dynamic and aggressive scheduling techniques for power-aware real-time systems , 2001, Proceedings 22nd IEEE Real-Time Systems Symposium (RTSS 2001) (Cat. No.01PR1420).

[32]  Raymond Keith Clark,et al.  Scheduling dependent real-time activities , 1990 .

[33]  Binoy Ravindran,et al.  A power-aware, best-effort real-time task scheduling algorithm , 2003, Proceedings IEEE Workshop on Software Technologies for Future Embedded Systems. WSTFES 2003.

[34]  Marco Spuri,et al.  Preemptive and Non-Preemptive Real-Time UniProcessor Scheduling , 1996 .

[35]  NahrstedtKlara,et al.  Energy-efficient soft real-time CPU scheduling for mobile multimedia systems , 2003 .

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

[37]  Don Towsley,et al.  Optimality of the Stochastic Earliest Deadline Policy for the G/M/c Queue Serving Customers with Deadlines , 1991 .

[38]  Aloysius Ka-Lau Mok,et al.  Fundamental design problems of distributed systems for the hard-real-time environment , 1983 .

[39]  Haisang Wu,et al.  Energy-Efficient, Utility Accrual Real-Time Scheduling , 2005 .

[40]  Alan Burns,et al.  Dynamic value-density for scheduling real-time systems , 1999, Proceedings of 11th Euromicro Conference on Real-Time Systems. Euromicro RTS'99.

[41]  Binoy Ravindran,et al.  Stochastic, utility accrual real-time scheduling with task-level and system-level timeliness assurances , 2005, Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC'05).