Capacity Sharing and Stealing in Server-based Real-Time Systems

In this paper we introduce an algorithm that supports the coexistence of guaranteed and best-effort bandwidth servers in a dynamic scheduling environment. In addition to being able to efficiently reclaim residual capacities, originated by early completions, an overloaded active server can also steal future capacities of inactive best-effort servers. The proposed dynamic budget accounting mechanism ensures that at a particular time, the currently executing server is using a residual capacity, its own capacity or is stealing some future capacity, eliminating the need of additional server states or unbounded queues. The server to which the budget accounting is going to be performed is dynamically determined at the time instant when a capacity is needed. The paper describes and evaluates the proposed scheduling algorithm, stating that it can efficiently reduce the mean tardiness of periodic jobs. The achieved results become even more significant when tasks’ computation times have a large variance. Capacity Sharing and Stealing in Dynamic Server-based Real-Time Systems Luis Nogueira, Luis Miguel Pinho IPP Hurray Research Group Polythecnic Institute of Porto, Portugal {luis,lpinho}@dei.isep.ipp.pt

[1]  Sanjoy K. Baruah,et al.  Greedy reclamation of unused bandwidth in constant-bandwidth servers , 2000, Proceedings 12th Euromicro Conference on Real-Time Systems. Euromicro RTS 2000.

[2]  Jane W.-S. Liu,et al.  Scheduling real-time applications in an open environment , 1997, Proceedings Real-Time Systems Symposium.

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

[4]  Harrick M. Vin,et al.  A hierarchial CPU scheduler for multimedia operating systems , 1996, OSDI '96.

[5]  Nuno Pereira,et al.  A few what-ifs on using statistical analysis of stochastic simulation runs to extract timeliness properties , 2004 .

[6]  Giuseppe Lipari,et al.  IRIS: a new reclaiming algorithm for server-based real-time systems , 2004, Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium, 2004..

[7]  Marco Spuri,et al.  Efficient aperiodic service under earliest deadline scheduling , 1994, 1994 Proceedings Real-Time Systems Symposium.

[8]  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.

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

[10]  Peter Csaba Ölveczky,et al.  Formal Simulation and Analysis of the CASH Scheduling Algorithm in Real-Time Maude , 2006, FASE.

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

[12]  Harrick M. Vin,et al.  A hierarchial CPU scheduler for multimedia operating systems , 1996, OSDI '96.

[13]  Alan Burns,et al.  Rewriting History to Exploit Gain Time , 2004, 25th IEEE International Real-Time Systems Symposium.

[14]  Luís Nogueira,et al.  Iterative Refinement Approach for QOS-Aware Service Configuration , 2006, DIPES.

[15]  Lui Sha,et al.  Capacity sharing for overrun control , 2000, Proceedings 21st IEEE Real-Time Systems Symposium.

[16]  Stefan M. Petters,et al.  Experimental evaluation of code properties for WCET analysis , 2003, RTSS 2003. 24th IEEE Real-Time Systems Symposium, 2003.

[17]  Theodore P. Baker,et al.  Aperiodic servers in a deadline scheduling environment , 2005, Real-Time Systems.

[18]  Alan Burns,et al.  Scheduling slack time in fixed priority pre-emptive systems , 1993, 1993 Proceedings Real-Time Systems Symposium.

[19]  Giorgio C. Buttazzo,et al.  Efficient reclaiming in reservation-based real-time systems with variable execution times , 2005, IEEE Transactions on Computers.

[20]  Luís Nogueira,et al.  Dynamic QoS-aware coalition formation , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[21]  Scott A. Brandt,et al.  Improving soft real-time performance through better slack reclaiming , 2005, 26th IEEE International Real-Time Systems Symposium (RTSS'05).

[22]  Krithi Ramamritham,et al.  Integrated scheduling of multimedia and hard real-time tasks , 1996, 17th IEEE Real-Time Systems Symposium.

[23]  Alan Burns,et al.  Multiple Servers and Capacity Sharing for Implementing Flexible Scheduling , 2004, Real-Time Systems.