Adaptive real-time scheduling for legacy multimedia applications

Multimedia applications are often executed on standard personal computers. The absence of established standards has hindered the adoption of real-time scheduling solutions in this class of applications. Developers have adopted a wide range of heuristic approaches to achieve an acceptable timing behavior but the result is often unreliable. We propose a mechanism to extend the benefits of real-time scheduling to legacy applications based on the combination of two techniques: (1) a real-time monitor that observes and infers the activation period of the application, and (2) a feedback mechanism that adapts the scheduling parameters to improve its real-time performance.

[1]  Shuichi Oikawa,et al.  Resource kernels: a resource-centric approach to real-time and multimedia systems , 2001, Electronic Imaging.

[2]  Fabio Checconi,et al.  The wizard of OS: a heartbeat for Legacy multimedia applications , 2009, 2009 IEEE/ACM/IFIP 7th Workshop on Embedded Systems for Real-Time Multimedia.

[3]  Michael B. Jones,et al.  An overview of the Rialto real-time architecture , 1996, EW 7.

[4]  Iakovos S. Venieris,et al.  Supporting QoS for Legacy Applications , 2001, ICN.

[5]  Antonio Casimiro,et al.  Using the timely computing base for dependable QoS adaptation , 2001, Proceedings 20th IEEE Symposium on Reliable Distributed Systems.

[6]  Fabio Checconi,et al.  Self-tuning schedulers for legacy real-time applications , 2010, EuroSys '10.

[7]  John P. Lehoczky,et al.  The rate monotonic scheduling algorithm: exact characterization and average case behavior , 1989, [1989] Proceedings. Real-Time Systems Symposium.

[8]  C. Ieee.  IEEE Standard for Information Technology - Portable Operating System Interface (POSIX): System Application Program Interface (API), Amendment 1: Realtime Extension (C Language), IEEE Std 1003.1b-1993 , 1994 .

[9]  Eric Eide,et al.  Dynamic CPU management for real-time, middleware-based systems , 2004, Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium, 2004..

[10]  B. Galler,et al.  Predicting musical pitch from component frequency ratios , 1979 .

[11]  Klara Nahrstedt,et al.  A control theoretical model for quality of service adaptations , 1998, 1998 Sixth International Workshop on Quality of Service (IWQoS'98) (Cat. No.98EX136).

[12]  Luigi Palopoli,et al.  Adaptive real-time scheduling for legacy applications , 2008, 2008 IEEE International Conference on Emerging Technologies and Factory Automation.

[13]  Sang Hyuk Son,et al.  Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms* , 2001, Real-Time Systems.

[14]  Jonathan Walpole,et al.  Analysis of a reservation-based feedback scheduler , 2002, 23rd IEEE Real-Time Systems Symposium, 2002. RTSS 2002..

[15]  Corporate Ieee,et al.  Information Technology-Portable Operating System Interface , 1990 .

[16]  Douglas C. Schmidt,et al.  Integration of QoS-Enabled Distributed Object Computing Middleware for Developing Next-Generation Distributed Application , 2001 .

[17]  Ashvin Goel,et al.  Fair and timely scheduling via cooperative polling , 2009, EuroSys '09.

[18]  Hideyuki Tokuda,et al.  Applying Hard Real-Time Technology to Multimedia Systems , 1993 .

[19]  Giorgio C. Buttazzo,et al.  Adaptive bandwidth reservation for multimedia computing , 1999, Proceedings Sixth International Conference on Real-Time Computing Systems and Applications. RTCSA'99 (Cat. No.PR00306).

[20]  B. Kedem,et al.  Spectral analysis and discrimination by zero-crossings , 1986, Proceedings of the IEEE.

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

[22]  Douglas C. Schmidt,et al.  Integration of QoS-Enabled Distributed Object Computing Middleware for Developing Next-Generation Distributed Application , 2001, LCTES/OM.

[23]  Tommaso Cucinotta,et al.  QoS Management Through Adaptive Reservations , 2005, Real-Time Systems.

[24]  B. P. Bogert,et al.  The quefrency analysis of time series for echoes : cepstrum, pseudo-autocovariance, cross-cepstrum and saphe cracking , 1963 .

[25]  Aloysius K. Mok,et al.  Resource partition for real-time systems , 2001, Proceedings Seventh IEEE Real-Time Technology and Applications Symposium.

[26]  Tommaso Cucinotta,et al.  AQuoSA—adaptive quality of service architecture , 2009, Softw. Pract. Exp..

[27]  Giorgio C. Buttazzo,et al.  Integrating multimedia applications in hard real-time systems , 1998, Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279).

[28]  Reinder J. Bril,et al.  QoS Control Strategies for High-Quality Video Processing , 2004, Proceedings. 16th Euromicro Conference on Real-Time Systems, 2004. ECRTS 2004..

[29]  Emery D. Berger,et al.  Usenix Association 8th Usenix Symposium on Operating Systems Design and Implementation 73 Redline: First Class Support for Interactivity in Commodity Operating Systems , 2022 .

[30]  Robin Fairbairns,et al.  The Design and Implementation of an Operating System to Support Distributed Multimedia Applications , 1996, IEEE J. Sel. Areas Commun..

[31]  Tommaso Cucinotta,et al.  AQuoSA—adaptive quality of service architecture , 2009 .

[32]  Antonio Casimiro,et al.  The Timely Computing Base Model and Architecture , 2002, IEEE Trans. Computers.

[33]  Calton Pu,et al.  A feedback-driven proportion allocator for real-rate scheduling , 1999, OSDI '99.

[34]  Luigi Palopoli,et al.  Legacy Real-Time Applications in a Reservation-Based System , 2009, IEEE Transactions on Industrial Informatics.

[35]  Jonathan Walpole,et al.  Real-rate scheduling , 2004, Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium, 2004..