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Fast, Best-Effort Real-Time Scheduling Algorithms
September 2004 (vol. 53 no. 9)
pp. 1159-1175
Peng Li, IEEE
This paper presents two fast, best-effort real-time scheduling algorithms called MDASA and MLBESA. MDASA and MLBESA are novel in the way that they heuristically, yet accurately, mimic the behavior of the DASA and LBESA scheduling algorithms, but are faster with O\left( n \right) and O \left( n \lg \left( n \right) \right) worst-case complexities, respectively. Experimental results show that the performance of MDASA and MLBESA, in general, is close to that of DASA and LBESA, respectively, for a broad range of realistic workloads. However, for a highly bursty workload, MLBESA is found to perform worse than LBESA. Furthermore, the task response times under MDASA and MLBESA are very close to the values under their counterpart scheduling algorithms. Thus, MDASA and MLBESA can substitute for DASA and LBESA algorithms, respectively, in adaptive resource allocation techniques for asynchronous real-time distributed systems where DASA and LBESA have previously been serious bottlenecks on computational costs.

[1] T. Abdelzaher, An Automated Profiling Subsystem for QoS-Aware Services Proc. IEEE EEE Real-Time Technology and Applications Symp. (RTAS), pp. 208-217, 2000.
[2] S. Aldarmi and A. Burns, Dynamic Value-Density for Scheduling Real-Time Systems Proc. Euromicro Conf. Real-Time Systems, pp. 270-277, June 1999.
[3] S.A. Aldarmi and A. Burns, Time-Cognizant Value Functions for Dynamic Real-Time Scheduling Technical Report YCS-306, Dept. of Computer Science, Univ. of York, U.K., 1998.
[4] A. Atlas and A. Bestavros, Statistical Rate Monotonic Scheduling Proc. 19th IEEE Real-Time Systems Symp., pp. 123-132, 1998.
[5] S. Baruah, G. Koren, D. Mao, B. Mishra, A. Raghunathan, L. Rosier, D. Shasha, and F. Wang, "On the Competitiveness of On-Line Real-Time Task Scheduling," Proc. 12th Real-Time Systems Symp.,San Antonio, Tex., Dec. 1991.
[6] S. Baruah, G. Koren, B. Mishra, A. Raghunathan, L. Rosier, and D. Shasha, "On-Line Scheduling in the Presence of Overload," Proc. 32nd Ann. IEEE Symp. Foundations of Computer Science,San Juan, Puerto Rico, Oct. 1991.
[7] S.K. Baruah, Overload Tolerance for Single-Processor Workloads Proc. IEEE EEE Real-Time Technology and Applications Symp. (RTAS), pp. 2-11, 1998.
[8] S.K. Baruah and J. Haritsa, Robust: A Hardware Solution to Real-Time Overload Proc. ACM SIGMETRICS Conf. Measurement and Modeling of Computer Systems, vol. 21, no. 1, pp. 207-216, 1993.
[9] S.K. Baruah, J.R. Haritsa, and N. Sharma, On-Line Scheduling to Maximize Task Completions J. Combinatorial Math. and Combinatorial Computing, vol. 39, pp. 65-78, 2001.
[10] A. Burns et al., The Meaning and Role of Value in Scheduling Flexible Real-Time Systems J. Systems Architecture, vol. 46, pp. 305-325, 2000.
[11] G. Buttazzo, M. Spuri, and F. Sensini, Value vs. Deadline Scheduling in Overload Conditions Proc. IEEE Real-Time Systems Symp. (RTSS), pp. 90-95. 1995.
[12] G.C. Buttazzo, Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications. Academic Publishers, 1997.
[13] G.C. Buttazzo and J. Stankovic, Adding Robustness in Dynamic Preemptive Scheduling Responsive Computer Systems, D. Fussel and M. Malek, eds., pp. 67-88, Kluwer Academic, Oct. 1995.
[14] K. Chen and P. Muhlethaler, A Scheduling Algorithm for Tasks Described by Time Value Function J. Real-Time Systems, vol. 10, no. 3, pp. 293-312, 1996.
[15] R. Clark et al., An Adaptive, Distributed Airborne Tracking System Proc. IEEE Int'l Workshop Parallel and Distributed Real-Time Systems, pp. 353-362, 1999.
[16] R.K. Clark, Scheduling Dependent Real-Time Activities PhD dissertation, Carnegie Mellon Univ., 1990.
[17] M.L. Dertouzos, Control Robotics: The Procedural Control of Physical Processes Proc. IFIP Congress, pp. 807-813, 1974.
[18] M.K. Gardner, Probabilistic Analysis and Scheduling of Critical Soft Real-Time Systems PhD dissertation, Univ. of Illinois at Urbana-Champaign, 1999.
[19] T. Hegazy and B. Ravindran, Using Application Benefit for Proactive Resource Allocation in Asynchronous Real-Time Distributed System IEEE Trans. Computers, vol. 51, no. 8, pp. 945-962, Aug. 2002.
[20] S.-I. Hwung, C.-M. Chen, and A.K. Agrawala, Scheduling an Overloaded Real-Time System Proc. IEEE Int'l Phoenix Conf. Computers and Comm., pp. 22-28, June 1996.
[21] E.D. Jensen and J.D. Northcutt, Alpha: A Non-Proprietary Operating System for Large, Complex, Distributed Real-Time Systems Proc. IEEE Workshop Experimental Distributed Systems, pp. 35-41, 1990.
[22] E.D. Jensen and B. Ravindran, Guest Editor's Introduction to Special Section on Asynchronous Real-Time Distributed Systems IEEE Trans. Computers, vol. 51, no. 8, pp. 881-882, Aug. 2002.
[23] E.D. Jensen, C.D. Locke, and H. Tokuda, A Time-Driven Scheduling Model for Real-Time Systems Proc. IEEE Real-Time Systems Symp. (RTSS), pp. 112-122, Dec. 1985.
[24] G. Koob, Quorum Proc. DARPA ITO General PI Meeting, pp. A-59-A-87, Oct. 1996.
[25] G. Koren and D. Shasha, “D-Over: An Optimal On-Line Scheduling Algorithm for Overloaded Real-Time Systems,” Proc. IEEE Real-Time Systems Symp., pp. 290-299, Dec. 1992.
[26] W. Leland et al., "On the Self-Similar Nature of Ethernet Traffic (Extended Version)," IEEE/ACM Trans. Networking, Vol. 2, No. 1, Feb. 1994, pp. 1-15.
[27] P. Li, B. Ravindran, J. Wang, and G. Konowicz, Choir: A Real-Time Middleware Architecture Supporting Benefit-Based Proactive Resource Allocation Proc. IEEE Int'l Symp. Object-Oriented Real-Time Distributed Computing (ISORC), pp. 292-299, 2003.
[28] J.W.S. Liu, W. Shih, K.J. Lin, R. Bettati, and J. Chung, “Imprecise Computations,” IEEE Proc., Jan. 1994.
[29] C.D. Locke, Best-Effort Decision Making for Real-Time Scheduling PhD dissertation, Carnegie Mellon Univ., 1986.
[30] C. Lu, J. Stakovic, G. Tao, and S. Son, Feedback Control Real-Time Scheduling: Framework, Modeling and Algorithms J. Real-Time Systems, vol. 23, nos. 1/2, pp. 85-126, July 2002.
[31] P. Mejia-Alvarez, R. Melhem, and D. Mosse, An Incremental Approach to Scheduling during Overloads in Real-Time Systems Proc. IEEE Real-Time Systems Symp. (RTSS), pp. 283-293, 2000.
[32] W. Mendenhall and T. Sincich, Statistics for the Engineering and Computer Sciences, third ed. 1991.
[33] D. Mosse, M.E. Pollack, and Y. Ronen, Value-Density Algorithm to Handle Transient Overloads in Scheduling Proc. Euromicro Conf. Real-Time Systems, pp. 278-286, 1999.
[34] D. Prasad and A. Burns, A Value-Based Scheduling Approach for Real-Time Autonomous Vehicle Control Robotica, vol. 31, pp. 273-279, 2000.
[35] P. Ramanathan, Overload Management in Real-Time Control Applications Using the (m, k) Firm Guarantee IEEE Trans. Parallel and Distributed Systems, vol. 10, no. 6, pp. 549-559, June 1999.
[36] B. Ravindran, Engineering Dynamic Real-Time Distributed Systems: Architecture, System Description Language, and Middleware IEEE Trans. Software Eng., vol. 28, no. 2, pp. 30-57, Jan. 2002.
[37] P. Richardson and S. Sarkar, Adaptive Scheduling: Overload Scheduling for Mission Critical Systems Proc. IEEE EEE Real-Time Technology and Applications Symp. (RTAS), pp. 14-23, 1999.
[38] B. Shirazi, L.R. Welch, B. Ravindran, C. Cavanaugh, and E. Huh, Dynbench: A Benchmark Suite for Dynamic Real-Time Systems J. Parallel and Distributed Computing Practices, vol. 3, no. 1, pp. 89-107, Mar. 2000.
[39] J.A. Stankovic and K. Ramamritham, “The Spring Kernel: A New Paradigm for Real-Time Systems,” IEEE Software, pp. 62-72, May 1991.
[40] D. Stewart and P. Khosla, Real-Time Scheduling of Sensor-Based Control Systems IFAC/IFIP Workshop Real-Time Programming, pp. 144-150, May 1991.
[41] The Open Group, MK7.3a Release Notes. Cambridge, Mass.: The Open Group Research Inst., 1998.
[42] T.-S. Tia et al., Probabilistic Performance Guarantee for Real-Time Tasks with Varying Computation Times Proc. IEEE EEE Real-Time Technology and Applications Symp. (RTAS), pp. 164-173, 1995.
[43] D. von Seggern, CRC Standard Curves and Surfaces. CRC Press, 1993.
[44] C.A. Waldspurger and W.E. Weihl, Lottery Scheduling: Flexible Proportional-Share Resource Management Operating Systems Design and Implementation, pp. 1-11, 1994.

Index Terms:
Best-effort real-time scheduling, overload scheduling, response time analysis, asynchronous real-time systems, distributed real-time systems.
Peng Li, Binoy Ravindran, "Fast, Best-Effort Real-Time Scheduling Algorithms," IEEE Transactions on Computers, vol. 53, no. 9, pp. 1159-1175, Sept. 2004, doi:10.1109/TC.2004.61
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