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Issue No.05 - May (2013 vol.25)
pp: 974-986
Jisu Oh , SAMSUNG Electronics Co., Ltd., Suwon-si
Kyoung-Don Kang , State University of New York at Binghamton, Binghamton
ABSTRACT
Supporting timely data services using fresh data in data-intensive real-time applications, such as e-commerce and transportation management is desirable but challenging, since the workload may vary dynamically. To control the data service delay to be below the specified threshold, we develop a predictive as well as reactive method for database admission control. The predictive method derives the workload bound for admission control in a predictive manner, making no statistical or queuing-theoretic assumptions about workloads. Also, our reactive scheme based on formal feedback control theory continuously adjusts the database load bound to support the delay threshold. By adapting the load bound in a proactive fashion, we attempt to avoid severe overload conditions and excessive delays before they occur. Also, the feedback control scheme enhances the timeliness by compensating for potential prediction errors due to dynamic workloads. Hence, the predictive and reactive methods complement each other, enhancing the robustness of real-time data services as a whole. We implement the integrated approach and several baselines in an open-source database. Compared to the tested open-loop, feedback-only, and statistical prediction + feedback baselines representing the state of the art, our integrated method significantly improves the average/transient delay and real-time data service throughput.
INDEX TERMS
Delay, Databases, Portfolios, Real time systems, Feedback control, Admission control, Estimation, implementation and performance evaluation, Real-time data services, predictive and feedback control of data service delays
CITATION
Jisu Oh, Kyoung-Don Kang, "A Predictive-Reactive Method for Improving the Robustness of Real-Time Data Services", IEEE Transactions on Knowledge & Data Engineering, vol.25, no. 5, pp. 974-986, May 2013, doi:10.1109/TKDE.2012.44
REFERENCES
[1] K.-D. Kang, J. Oh, and Y. Zhou, "Backlog Estimation and Management for Real-Time Data Services," Proc. 20th Euromicro Conf. Real-Time Systems, pp. 289-298, 2008.
[2] Real-Time Database Systems, K.Y. Lam and T.W. Kuo, eds. Kluwer Academic Publishers, 2006.
[3] K. Ramamritham, S.H. Son, and L.C. Dipippo, "Real-Time Databases and Data Services," Real-Time Systems, vol. 28, pp. 179-215, 2004.
[4] N. Bhatti, A. Bouch, and A. Kuchinsky, "Integrating User-Perceived Quality into Web Server Design," Proc. Ninth Int'l World Wide Web Conf., pp. 1-16, 2000.
[5] "Microsoft SQL Server 2008 R2 - StreamInsight," http://www. microsoft.com/sqlserver/2008/ en/usr2-complex-event.aspx, 2012.
[6] "Exploratory Stream Processing Systems," http://domino. research.ibm.com/comm/research_projects.nsf/ pagesesps. index.html , 2012.
[7] "StreamBase," http:/www.streambase.com/, 2012.
[8] D.J. Abadi, Y. Ahmad, M. Balazinska, U. Cetintemel, M. Cherniack, J.-H. Hwang, W. Lindner, A.S. Maskey, A. Rasin, E. Ryvkina, N. Tatbul, Y. Xing, and S.B. Zdonik, "The Design of the Borealis Stream Processing Engine," Proc. Conf. Innovative Data Systems Research (CIDR), 2005.
[9] N. Tatbul, U. Cetintemel, S.B. Zdonik, M. Cherniack, and M. Stonebraker, "Load Shedding in a Data Stream Manager," Proc. Int'l Conf. Very Large Data Bases, 2003.
[10] B. Chandramouli, J. Goldstein, R. Barga, M. Riedewald, and I. Santos, "Accurate Latency Estimation in a Distributed Event Processing System," Proc. Int'l Conf. Data Eng., 2011.
[11] G.F. Franklin, J.D. Powell, and M.L. Workman, Digital Control of Dynamic Systems, third ed. Addison-Wesley, 1998.
[12] J.L. Hellerstein, Y. Diao, S. Parekh, and D.M. Tilbury, Feedback Control of Computing Systems. John Wiley & Sons, 2004.
[13] M. Amirijoo, N. Chaufette, J. Hansson, S.H. Son, and S. Gunnarsson, "Generalized Performance Management of Multi-Class Real-Time Imprecise Data Services," Proc. 26th IEEE Int'l Real-Time Systems Symp., pp. 38-49, 2005.
[14] K.D. Kang, S.H. Son, and J.A. Stankovic, "Managing Deadline Miss Ratio and Sensor Data Freshness in Real-Time Databases," IEEE Trans. Knowledge and Data Eng., vol. 16, no. 10, pp. 1200-1216, Oct. 2004.
[15] K.D. Kang, J. Oh, and S.H. Son, "Chronos: Feedback Control of a Real Database System Performance," Proc. 28th IEEE Real-Time Systems Symp., pp. 267-276, 2007.
[16] "Oracle Berkeley DB Product Family, High Performance, Embeddable Database Engines," http://www.oracle.com/database/ berkeley-db index.html, 2012.
[17] M. Amirijoo, J. Hansson, and S.H. Son, "Specification and Management of QoS in Real-Time Databases Supporting Imprecise Computations," IEEE Trans. Computers, vol. 55, no. 3, pp. 304-319, Mar. 2006.
[18] "E∗TRADE 2-Second Execution Guarantee," https://us.etrade. com/e/t/investapptemplate?gxml=exec_guarantee.html , 2012.
[19] Ameritrade, "Spot and Seize Potential Market Opportunities," http://www.tdameritrade.compowerfultools.html , 2012.
[20] N.Y. Times, "Stock Traders Find Speed Pays, in Milliseconds," http://www.nytimes.com/2009/07/24/business 24trading.html, 2012.
[21] D. Henriksson, Y. Lu, and T. Abdelzaher, "Improved Prediction for Web Server Delay Control," Proc. 16th Euromicro Conf. Real-Time Systems, pp. 61-68, 2004.
[22] "Transaction Processing Performance Council," http:/www.tpc.org/, 2012.
[23] Y. Zhou and K.-D. Kang, "Integrating Proactive and Reactive Approaches for Robust Real-Time Data Services," Proc. 30th IEEE Real-Time Systems Symp., pp. 105-114, 2009.
[24] "Yahoo! Finance," http:/finance.yahoo.com, 2012.
[25] R. Ramakrishnan and J. Gehrke, Database Management Systems, third ed. McGraw-Hill, 2003.
[26] D. Vrancic, "Design of Anti-Windup and Bumpless Transfer Protection," PhD dissertation, Univ. of Ljubljana, Slovenia, 1997.
[27] "TPC-DS," http://www.tpc.org/tpcdstpcds.asp, 2012.
[28] N.R. Draper and H. Smith, Applied Regression Analysis. Wiley, 1968.
[29] J.L. Devore, Probability and Statistics for Engineering and the Sciences, sixth ed. Thomson Learning, Inc., 2004.
[30] B. Babcock, M. Datar, and R. Motwani, "Load Shedding for Aggregation Queries over Data Streams," Proc. Int'l Conf. Data Eng., 2004.
[31] N. Tatbul, U. Çetintemel, and S. Zdonik, "Staying FIT: Efficient Load Shedding Techniques for Distributed Stream Processing" Proc. Int'l Conf. Very Large Data Bases, 2007.
[32] N. Tatbul, "Load Shedding," Encyclopedia of Database Systems, T. Özsu and L. Liu, eds., pp. 1632-1636, Springer, 2009.
[33] C. Lu, J.A. Stankovic, G. Tao, and S.H. Son, "Feedback Control Real-Time Scheduling: Framework, Modeling and Algorithms," Real-Time Systems, vol. 23, nos. 1/2, pp. 85-126, 2002.
[34] C. Lu, Y. Lu, T. Abdelzaher, J.A. Stankovic, and S. Son, "Feedback Control Architecture and Design Methodology for Service Delay Guarantees in Web Servers," IEEE Trans. Parallel and Distributed Systems, vol. 17, no. 9, pp. 1014-1027, Sept. 2006.
[35] Y. Lu, A. Saxena, and T.F. Abdelzaher, "Differentiated Caching Services; A Control-Theoretical Approach," Proc. 21st Int'l Conf. Distributed Computing Systems, pp. 615-624, 2001.
[36] S. Parekh, N. Gandhi, J. Hellerstein, D. Tilbury, T. Jayram, and J. Bigus, "Using Control Theory to Achieve Service Level Objectives in Performance Management," Real-Time Systems, vol. 23, nos. 1/2, pp. 127-141, 2002.
[37] W. Kang, S.H. Son, and J. Stankovic, "Design, Implementation, and Evaluation of a QoS-Aware Real-Time Embedded Database," IEEE Trans. Computers, vol. 61, no. 1, pp. 45-59, Jan. 2012.
[38] L. Sha, X. Liu, Y. Lu, and T. Abdelzaher, "Queueing Model Based Network Server Performance Control," Proc. 23rd IEEE Real-Time Systems Symp., p. 81, 2002.
[39] Y. Lu, T.F. Abdelzaher, C. Lu, L. Sha, and X. Liu, "Feedback Control with Queuing-Theoretic Prediction for Relative Delay Guarantees in Web Servers," Proc. Ninth IEEE Real-Time and Embedded Technology and Applications Symp., p. 208, 2003.
[40] B. Schroeder, M. Harchol-Balter, A. Iyengar, E. Nahum, and A. Wierman, "How to Determine a Good Multi-Programming Level for External Scheduling," Proc. 22nd Int'l Conf. Data Eng., p. 60, 2006.
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