PARTOS-11: an efficient real-time operating system for low-cost microcontrollers

An efficient real-time operating system, PARTOS-11, has been developed for a low-speed and small-memory microcontroller, 68HC11. The size of the kernel is 2 Kbytes. Both hard real-time tasks and soft real-time tasks can be run in the system concurrently. The rate-monotonic policy is adopted for scheduling hard real time tasks, which guarantees that all tasks meet their deadline if the condition of Liu and Layland's theorem is met. A novel model, the Slack Sharing Server (SSS), was proposed and implemented. The SSS is a simple and efficient server for soft real time tasks running together with hard real time tasks in a small real-time embedded system.

[1]  Tei-Wei Kuo,et al.  A fixed-priority-driven open environment for real-time applications , 1999, Proceedings 20th IEEE Real-Time Systems Symposium (Cat. No.99CB37054).

[2]  Azer Bestavros,et al.  Statistical rate monotonic scheduling , 1998, Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279).

[3]  Kang G. Shin,et al.  EMERALDS: a microkernel for embedded real-time systems , 1996, Proceedings Real-Time Technology and Applications.

[4]  Parameswaran Ramanathan,et al.  Real-time computing: a new discipline of computer science and engineering , 1994, Proc. IEEE.

[5]  Kang G. Shin,et al.  On memory protection in real-time OS for small embedded systems , 1997, Proceedings Fourth International Workshop on Real-Time Computing Systems and Applications.

[6]  Miodrag Potkonjak,et al.  Real-time operating systems for embedded computing , 1997, Proceedings International Conference on Computer Design VLSI in Computers and Processors.

[7]  John P. Lehoczky,et al.  An optimal algorithm for scheduling soft-aperiodic tasks in fixed-priority preemptive systems , 1992, [1992] Proceedings Real-Time Systems Symposium.

[8]  Pam Binns.  Incremental rate monotonic scheduling for improved control system performance , 1997, Proceedings Third IEEE Real-Time Technology and Applications Symposium.

[9]  Jay K. Strosnider,et al.  The Deferrable Server Algorithm for Enhanced Aperiodic Responsiveness in Hard Real-Time Environments , 1987, IEEE Trans. Computers.

[10]  Kang G. Shin,et al.  An efficient semaphore implementation scheme for small-memory embedded systems , 1997, Proceedings Third IEEE Real-Time Technology and Applications Symposium.

[11]  Sanjoy K. Baruah,et al.  Efficient scheduling of real-time multi-task applications in dynamic systems , 2000, Proceedings Sixth IEEE Real-Time Technology and Applications Symposium. RTAS 2000.

[12]  Chung Laung Liu,et al.  Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment , 1989, JACM.

[13]  Alan Burns,et al.  New results on fixed priority aperiodic servers , 1999, Proceedings 20th IEEE Real-Time Systems Symposium (Cat. No.99CB37054).

[14]  Marco Spuri,et al.  Implications of Classical Scheduling Results for Real-Time Systems , 1995, Computer.