WAIM 2004: Advances in Web-Age Information Management pp 268-279 | Cite as
Apply Feedback Control Theory to Design Soft Real-Time Search Engine System
Conference paper
Abstract
This paper proposes a design method for soft real-time search engine system, and provides proofs to its correctness and robustness both in control theory and by practical experiments. An analyzable mathematical model is set up to approximately describe the nonlinear and time-varying search engine system. The feedback control theory is adopted to prove the system’s stableness, zero steady state error and zero overshoot. The soft real-time guarantee is satisfied while the feedback system is in stable state. The experiment results further prove the effectiveness of our scheme.
Keywords
Steady State Error Performance Reference Search Speed Stochastic Schedule System Transfer Function
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Preview
Unable to display preview. Download preview PDF.
References
- 1.Buttazzo, G.: Hard Real-Time Computing System: Predictable Scheduling Algorithms and Applications. Kluwer Academic Publishers, Massachusetts (2000)Google Scholar
- 2.Thati, P., Chang, P.-H., Agha, G.A.: Crawlets: Agents for high performance web search engines. In: Picco, G.P. (ed.) MA 2001. LNCS, vol. 2240, pp. 119–134. Springer, Heidelberg (2001)CrossRefGoogle Scholar
- 3.Xiaohui, Z., Huayong, W., Guiran, C., Hong, Z.: An autonomous system- based distribution system for web search. In: Proceedings of IEEE International Conference on ystems, Man, and Cybernetics, vol. 1, pp. 435–440 (2001)Google Scholar
- 4.Sato, N., Uehara, M., Sakai, Y., Mori, H.: Distributed Information Retrieval by using Cooperative Meta Search Engines. In: Proceedings of the 21st IEEE International Conference on Distributed Computing Systems Workshops (Multimedia Network Systems, MNS 2001), pp. 345–350 (2001)Google Scholar
- 5.Sato, N., Uehara, M., Sakai, Y., Mori, H.: Fresh Information Retrieval using Cooperative Meta Search Engines. In: Proceedings of the 16th International Conference on Information Networking (ICOIN-16), vol. 2, pp. 7A-2-1-7 (2002)Google Scholar
- 6.Unger, H., Wulff, M.: Towards a Decentralized Search Engine for P2P-Network Communities. In: Proceedings of 11th Euromicro Conference on Parallel, Distributed and Network-Based Processing, pp. 429–499 (2003)Google Scholar
- 7.Gupta, V., Campbell, R.: Internet Search Engine Freshness by Web Server Help. In: Proceedings of 2001 Symposium on Applications and the Internet, pp. 113–119 (2001)Google Scholar
- 8.Chidi lkeji, A., Fotouhi, F.: An Adaptive Real-Time Web Search Engine. In: Proceedings of the second international workshop on Web information and data management (1999)Google Scholar
- 9.Talim, J., Liu, Z., Nain, P., Coffman, E.G.: Controlling the Robots of Web Search Engines. ACM SIGMETRICS Performance Evaluation Review 29(1) (June 2001)Google Scholar
- 10.Liu, C.L., Layland, J.W.: Scheduling Algorithms for Multiprogramming in a Hard Real Time Environment. Journal of the ACM 20(1), 46–61 (1973)MATHCrossRefMathSciNetGoogle Scholar
- 11.Tia, T.-S., Deng, Z., Shankar, M., Storch, M., Sun, J., Wu, L.-C., Liu, J.W.-S.: Probabilistic Performance Guarantee for Real-Time Tasks with Varying Computation Times. In: IEEE Real-Time Technology and Applications Symposium, pp. 164–173 (1995)Google Scholar
- 12.Diaz, J.L., Garcia, D.F., Kim, K., Lee, C.G., Lo Bello, L., Lopez, J.M., Min, S.L., Mirabella, O.: Stochastic Analysis of Periodic Real-Time Systems. In: IEEE 23rd Real-Time Systems Symposium, pp. 289–300 (2002)Google Scholar
- 13.Abdelzaher, T.F., Atkins, E.M., Shin, K.G.: Qos negotiation in real-time system and its application to automatic flight control. In: IEEE Real-Time Technology and Application Symposium (1997)Google Scholar
- 14.Buttazzo, G., Lipari, G., Abeni, L.: Elastic task model for adaptive rate control. In: IEEE Real-Time System Symposium, pp. 286–295 (1998)Google Scholar
- 15.Caccamo, M., Buttazzo, G., Sha, L.: Capacity sharing for overrun control. In: IEEE Real-Time Systems Symposium (2000)Google Scholar
- 16.Abdelzaher, T.F., Bhatti, N.: Web server Qos management by adaptive content delivery. In: International Workshop on Quality of Service (1999)Google Scholar
- 17.Lu, C., Abdelzaher, T.F., Stankovic, J.A., Son, S.H.: A feedback control approach for guaranteeing relative delays in web servers. In: IEEE Real-Time Technology and Application Symposium (2001)Google Scholar
- 18.Parekh, S., Gandhi, N., Hellerstein, J.L., Tilbury, D., Jayram, T.S., Bigus, J.: Using control theory to achieve service level objectives in performance management. In: IFIP/IEEE International Symposium on Integrated Network Management (2001)Google Scholar
- 19.Abeni, L., Palopoli, L., Lipari, G., Walpole, J.: Analysis of a Reservation-Based Feedback Scheduler. In: Proceedings of IEEE 23rd Real-Time Systems Symposium, pp. 71–80 (2002)Google Scholar
- 20.Sha, L., Liu, X., Lu, Y., Abdelzaher, T.: Queueing Model Based Network Server Performance Control. In: Proceedings of IEEE 23rd Real-Time Systems Symposium, pp. 71–80 (2002)Google Scholar
- 21.Cervin, A., Eker, J., Bernhardsson, B.: Feedback-Feedforward Scheduling of Control Tasks. Real-Time Systems 23(1/2), 25–53Google Scholar
- 22.Shengtan, C., Baolong, G., Xuewu, L., Zhongzhe, F.: Signal and System. Press of Xian Electronic Technology Univ., Xian, P.R.China (2001)Google Scholar
- 23.Zhengqi, S.: System analysis and control. Tsinghua univ. Press, Beijing (1994)Google Scholar
- 24.Franklin, G.F., Powell, J.D., Workman, M.L.: Digital Control of Dynamic Systems, 3rd edn. Addison-Wesley, Reading (1998)Google Scholar
Copyright information
© Springer-Verlag Berlin Heidelberg 2004