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An Exploration of the Effects of State Granularity through (m, k) Real-Time Streams
June 2009 (vol. 58 no. 6)
pp. 784-798
Yingxin Jiang, University of Notre Dame, Notre Dame
Aaron Striegel, University of Notre Dame, Notre Dame
Real-time media servers are becoming increasingly important as the Internet supports more and more multimedia applications. In order to meet these ever increasing demands, real-time media servers will be responsible for supporting a large number of clients with a wide range of QoS requirements. While techniques to aggregate state information for scalability have been proposed in the literature such as with Differentiated Services; the per-stream effects of such aggregation are poorly understood. Based on the (m,k)-firm model to schedule loss-tolerant streams, we explore the effects of aggregated state information in this paper and describe our scheme, called Granularity Aware (m,k) Queue Management (GAQM). GAQM improves control over the tradeoff between scalability and per-stream QoS performance. Specifically, we identify the necessity of balancing aggregation groups according to characteristics such as relative deadlines. Another key finding of this work is that with proper biasing, the inaccuracy of aggregate state lends itself to burst scheduling rather than simply extending traditional scheduling mechanisms. This finding is profound in that the result is counterintuitive: less frequent scheduling leads to increased per-stream performance. We present detailed examples of GAQM and evaluate our work through simulation studies and Markov chain analysis.

[1] Y. Jiang and A. Striegel, “Granularity-Aware (m,k) Queue Management for Real-Time Media Servers,” Proc. 12th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), pp.103-112, Apr. 2006.
[2] C.M. Aras, J.F. Kurose, D.S. Reeves, and H. Schulzrinne, “Real-Time Communication in Packet-Switched Networks,” Proc. IEEE, vol. 82, no. 1, pp.122-139, Jan. 1994.
[3] J.M. Peha and F.A. Tobagi, “A Cost-Based Scheduling Algorithm to Support Integrated Services,” Proc. IEEE INFOCOM '91, pp.741-753, 1991.
[4] J.M. Boyce and R.D. Gaglianello, “Packet Loss Effects on MPEG Video Sent Over the Public Internet,” Proc. Sixth ACM Int'l Conf. Multimedia, pp. 181-190, Sept. 1998.
[5] A. Koubaa and Y.-Q. Song, “Loss-Tolerant QoS Using Firm Constraints in Guaranteed Rate Networks,” Proc. 10th IEEE Real-Time and Embedded Technology and Applications Symp. (RTAS '04), pp. 526-533, May 2004.
[6] M. Hamdaoui and P. Ramanathan, “A Dynamic Priority Assignment Technique for Streams with (m,k)-Firm Guarantees,” IEEE Trans. Computers, vol. 44, no. 12, pp.1443-1451, Dec. 1995.
[7] A. Striegel and G. Manimaran, “Best-Effort Scheduling of (m, k)-Firm Real-Time Streams in Multihop Networks,” Computer Comm., vol. 23, no. 13, pp.1292-1300, July 2000.
[8] R. West, Y. Zhang, K. Schwan, and C. Poellabauer, “Dynamic Window-Constrained Scheduling of Real-Time Streams in Media Servers,” IEEE Trans. Computers, vol. 53, no. 6, pp.744-759, June 2004.
[9] A. Striegel and G. Manimaran, “Dynamic Class-Based Queue Management for Scalable Media Servers,” J. Systems and Software, vol. 66, no. 2, pp.119-128, May 2003.
[10] Y. Zhang, R. West, and X. Qi, “A Virtual Deadline Scheduler for Window-Constrained Service Guarantees,” Proc. 25th IEEE Real-Time Systems Symp. (RTSS), pp. 151-160, Dec. 2004.
[11] Y. Zhang and R. West, “End-to-end Window-Constrained Scheduling for Real-Time Communication,” Proc. 10th Int'l Conf. Real-Time and Embedded Computing Systems and Applications (RTCSA '04), Aug. 2004.
[12] A.B. Bondi, “Characteristics of Scalability and Their Impact on Performance,” Proc. Second Int'l Workshop Software and Performance, pp.195-203, 2000.
[13] K. Nichols, S. Blake, F. Baker, and D. Black, “Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers,” IETF RFC 2474, Dec. 1998.
[14] J. Heinanen, F. Baker, W. Weiss, and J. Wroclawski, “Assured Forwarding PHB Group,” IETF RFC 2597, June 1999.
[15] C. Dovrolis and P. Ramanathan, “A Case for Relative Differentiated Services and the Proportional Differentiation Model,” IEEE Network, pp.26-34, Sept./Oct. 1999.
[16] C. Dovrolis, D. Stiliadis, and P. Ramanathan, “Proportional Differentiated Services: Delay Differentiation and Packet Scheduling,” IEEE/ACM Trans. Networking, vol. 10, no. 1, pp.12-26, Feb. 2002.
[17] A.K. Parekh and R.G. Gallager, “A Generalized Processor Sharing Approach to Flow Control in Integrated Services Networks: The Single-Node Case,” IEEE/ACM Trans. Networking, vol. 1, no. 3, pp.344-357, June 1993.
[18] J. Nagle, “On Packet Switches with Infinite Storage,” IEEE Trans. Comm., vol. 35, no. 4, pp.435-438, Apr. 1987.
[19] A. Demers, S. Keshav, and S. Shenker, “Analysis and Simulation of a Fair Queueing Algorithm,” Proc. ACM SIGCOMM '89, pp.1-12, 1989.
[20] P. McKenney, “Stochastic Fairness Queueing,” Internetworking: Research and Experience, vol. 2, pp.113-131, Jan. 1991.
[21] M. Hamdaoui and P. Ramanathan, “Evaluating Dynamic Failure Probability for Streams with (m, k)-Firm Deadlines,” IEEE Trans. Computers, vol. 46, no. 12, pp.1325-1337, 1997.
[22] E. Poggi, Y. Song, A. Koubaa, and Z. Wang, “Matrix-DBP for $(m, k)$ -Firm Real-Time Guarantee,” Proc. Real-Time and Embedded System, pp.457-482, Apr. 2003.
[23] W. Lindsay and P. Ramanathan, “DBP-M: A Technique for Meeting End-to-End $(m, k)$ -Firm Guarantee Requirements in Point-to-Point Networks,” Proc. 22nd Ann. IEEE Conf. Local Computer Networks, pp.294-303, Nov. 1997.
[24] G. Quan and X. Hu, “Enhanced Fixed-Priority Scheduling with (m, k)-Firm Guarantee,” Proc. 21st IEEE Real-Time Systems Symp., pp. 79-88, Nov. 2000.
[25] A.K. Mok and W. Wang, “Window-Constrained Real-Time Periodic Task Scheduling,” Proc. IEEE Real-Time Systems Symp., pp.15-24, 2001.
[26] L. Jian and S. Ye-Qiong, “Relaxed (m, k)-Firm Constraint to Improve Real-Time Streams Admission Rate under Non Pre-Emptive Fixed Priority Scheduling,” Proc. IEEE Conf. Emerging Technologies and Factory Automation (ETFA '06), pp.1051-1060, 2006.
[27] J. Li and Y. Song, “Dlb: A Novel Real-Time QoS Control Mechanism for Multimedia Transmission,” Proc. Advanced Information Networking and Applications, pp.185-190, 2006.
[28] J. Lehoczky, L. Sha, and Y. Ding, “The Rate-Monotonic Scheduling Algorithm: Exact Characterization and Average Case Behaviour,” Proc. IEEE Real-Time Systems Symp., pp.166-171, 1989.
[29] A. Atlas and A. Bestavros, “Statistical Rate Monotonic Scheduling,” Proc. 19th IEEE Real-Time Systems Symp., pp.123-132, 1998.
[30] S. Floyd and V. Jacobson, “Link-Sharing and Resource Management Models for Packet Networks,” IEEE/ACM Trans. Networking, vol. 3, no. 4, pp.365-386, 1995.
[31] J. Mao, W.M. Moh, and B. Wei, “PQWRR Scheduling Algorithm in Supporting of DiffServ,” Proc. Int'l Conf. Comm. 2001, vol. 3, pp.679-684, 2001.
[32] V. Jacobson, K. Nichols, and K. Poduri, “An Expedited Forwarding PHB Group,” IETF RFC 2598, June 1999.
[33] M. Song and M. Alam, “Two Scheduling Algorithms for Input-Queued Switches Guaranteeing Voice QoS,” Proc. IEEE GLOBECOM 2001, pp. 92-96, 2001.
[34] Y. Jiang, X. Li, and A. Striegel, Experimental Studies of Granularity Aware (m,k) Scheduling for Real-Time Media Servers, Technical Report TR-2008-01, ND CSE, 2008.
[35] R. West and C. Poellabauer, “Analysis of a Window-Constrained Scheduler for Real-Time and Best-Effort Packet Streams,” Proc. 21st IEEE Real-Time Systems Symp. (RTSS), pp. 239-248, 2000.
[36] P. Ramanathan, “Overload Management in Real-Time Control Applications using m,k $(m, k)$ -Firm Guarantee,” IEEE Trans. Parallel and Distributed Systems, vol. 10, no. 6, pp.549-559, June 1999.
[37] , 2009.

Index Terms:
Real-time systems, dynamic failure, deadline-constraint scheduling, (m, k)-firm task scheduling, queue management.
Yingxin Jiang, Aaron Striegel, "An Exploration of the Effects of State Granularity through (m, k) Real-Time Streams," IEEE Transactions on Computers, vol. 58, no. 6, pp. 784-798, June 2009, doi:10.1109/TC.2008.225
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