Journal of Computing Science and Engineering

Korean Institute of Information Scientists and Engineers (한국정보과학회)
권호 표지
DOI QR코드

DOI QR Code

Applying Formal Methods to Modeling and Analysis of Real-time Data Streams

  • Received : 2011.02.11
  • Accepted : 2011.03.03
  • Published : 2011.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Achieving situation awareness is especially challenging for real-time data stream applications because they i) operate on continuous unbounded streams of data, and ii) have inherent realtime requirements. In this paper we showed how formal data stream modeling and analysis can be used to better understand stream behavior, evaluate query costs, and improve application performance. We used MEDAL, a formal specification language based on Petri nets, to model the data stream queries and the quality-of-service management mechanisms of RT-STREAM, a prototype system for data stream management. MEDAL's ability to combine query logic and data admission control in one model allows us to design a single comprehensive model of the system. This model can be used to perform a large set of analyses to help improve the application's performance and quality of service.

Keywords

References

  1. ABADI, D., AHMAD, Y., BALAZINSKA, M., ÇETINTEMEL, U., CHERNIACK, M., HWANG, J., LINDNER, W., MASKEY, A., RASIN, A., RYVKINA, E., TATBUL, N., XING, Y., AND ZDONIK, S. 2005. The design of the Borealis stream processing engine. In The 2nd Biennial Conference on Innovative Data Systems Research.
  2. ABADI, D. J., CARNEY, D., ÇETINTEMEL, U., CHERNIACK, M., CONVEY, C., LEE, S., STONEBRAKER, M., TATBUL, N., AND ZDONIK, S. 2003. Aurora: a new model and architecture for data stream management. The VLDB Journal 12, 2, 120-139. https://doi.org/10.1007/s00778-003-0095-z
  3. BABCOCK, B., BABU, S., DATAR, M., MOTWANI, R., AND WIDOM, J. 2002. Models and issues in data stream systems. In Proceedings of the 21st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 1-16. https://doi.org/10.1145/543613.543615
  4. BARBARA, D., DUMOUCHEL, W., FALOUTSOS, C., HAAS, P. J., HELLERSTEIN, J. M., IOANNIDIS, Y., JAGADISH, H. V., JOHNSON, T., NG, R., POOSALA, V., ROSS, K. A., AND SEVCIK, K. C. 1997. The New Jersey data reduction report. Bulletin of the Technical Committee on Data Engineering 20, 4, 3-42.
  5. BLANDFORD, A. AND WONG, B. L. W. 2004. Situation awareness in emergency medical dispatch. International Journal of Human Computer Studies 61, 4, 421-452. https://doi.org/10.1016/j.ijhcs.2003.12.012
  6. CARNEY, D., CETINTEMEL, U., CHERNIACK, M., CONVEY, C., LEE, S., SEIDMAN, G., STONEBRAKER, M., TATBUL, N., AND ZDONIK, S. 2002. Monitoring streams: a new class of data management applications. In Proceedings of the 28th international conference on Very Large Data Bases, 215-226.
  7. CHAUDHURI, S., DAS, G., DATAR, M., MOTWANI, R., AND NARASAYYA, V. 2001.Overcoming limitations of sampling for aggregation queries. In 17th International Conference on Data Engineering, 534-542.
  8. COMER, D. 1979. The ubiquitous B-Tree. ACM Computing Surveys 11, 2, 121-137. https://doi.org/10.1145/356770.356776
  9. GIROD, L., MEI, Y., NEWTON, R., ROST, S., THIAGARAJAN, A., BALAKRISHNAN, H., AND MADDEN, S. 2007. The case for a signal-oriented data stream management system. In The 3rd Biennial Conference on Innovative Data Systems Research.
  10. GOLAB, L. AND OZSU, M. T. 2003. Issues in data stream management. SIGMOD Record 32, 2, 5-14. https://doi.org/10.1145/776985.776986
  11. GORMAN, J. C., COOKE, N. J., AND WINNER, J. L. 2006. Measuring team situation awareness in decentralized command and control environments. Ergonomics 49, 12-13, 1312-1325. https://doi.org/10.1080/00140130600612788
  12. HAAS, P. J., NAUGHTON, J. F., AND SWAMI, A. N. 1994. On the relative cost of sampling for join selectivity estimation. In Proceedings of the 13th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 14-24.
  13. HE, T., STANKOVIC, J. A., CHENYANG, L., AND ABDELZAHER, T. 2003. SPEED: a stateless protocol for real-time communication in sensor networks. In Proceedings of the 23rd International Conference on Distributed Computing Systems, 46-55. https://doi.org/10.1109/ICDCS.2003.1203451
  14. HELLERSTEIN, J. L., DIAO, Y., PAREKH, S., AND TILBURY, D. M. 2004. Feedback Control of Computing Systems. Wiley-IEEE Press, New York.
  15. HONG, W. AND STONEBRAKER, M. 1991. Optimization of parallel query execution plans in XPRS. In Proceedings of the First International Conference on Parallel and Distributed Information Systems, 218-225.
  16. KAPITANOVA, K. AND SON, S. H. 2009. MEDAL: a compact event description and analysis language for wireless sensor networks. In 6th International Conference on Networked Sensing Systems, 117-120.
  17. LEE, E. B. AND MARKUS, L. 1967. Foundations of Optimal Control Theory. Wiley, New York.
  18. LIN, S., ZHANG, J., ZHOU, G., GU, L., STANKOVIC, J. A., AND HE, T. 2006. ATPC: adaptive transmission power control for wireless sensor networks. In 4th International Conference on Embedded Networked Sensor Systems, 223-236. https://doi.org/10.1145/1182807.1182830
  19. LIU, B., ZHU, Y., JBANTOVA, M., MOMBERGER, B., AND RUNDENSTEINER, E. A. 2005. A dynamically adaptive distributed system for processing complex continuous queries. In 31st International Conference on Very Large Data Bases, 1338-1341.
  20. LJUNG, L. 1999. System Identification: Theory for the User. 2nd ed. Prentice Hall PTR, Upper Saddle River, NJ.
  21. LU, C., LU, Y., ABDELZAHER, T. F., STANKOVIC, J. A., AND SON, S. H. 2006. Feedback control architecture and design methodology for service delay guarantees in web servers. IEEE Transactions on Parallel and Distributed Systems 17, 9, 1014-1027. https://doi.org/10.1109/TPDS.2006.123
  22. LU, C., STANKOVIC, J. A., SON, S. H., AND TAO, G. 2002. Feedback control real-time scheduling: Framework, modeling, and algorithms. Real-Time Systems 23, 1-2, 85-126. https://doi.org/10.1023/A:1015398403337
  23. MOTWANI, R., WIDOM, J., ARASU, A., BABCOCK, B., BABU, S., DATAR, M., MANKU, G., OLSTON, C., ROSENSTEIN, J., AND VARMA, R. 2003. Query processing, resource management, and approximation in a data stream management system. In The 1st Biennial Conference on Innovative Data Systems Research.
  24. NULLMEYER, R. T., STELLA, D., MONTIJO, G. A., AND HARDEN, S. W. 2005. Human factors in air force flight mishaps: implications for change. In Proceedings of the 27th Annual Interservice/Industry Training, Simulation, and Education Conference.
  25. OLSTON, C., JIANG, J., AND WIDOM, J. 2003. Adaptive filters for continuous queries over distributed data streams. In Proceedings of ACM SIGMOD International Conference on Management of Data, 563-574.
  26. POOSALA, V. AND IOANNIDIS, Y. E. 1997. Selectivity estimation without the attribute value independence assumption. In Proceedings of the 23rd International Conference on Very Large Data Bases, 486-495.
  27. PRESS, W. H., FLANNERY, B. P., TEUKOLSKY, S. A., AND VETTERLING, W. T. 1992. Numerical Recipes in C: The Art of Scientific Computing. 2nd ed. Cambridge University Press, Cambridge.
  28. TU, Y. C., LIU, S., PRABHAKAR, S., AND YAO, B. 2006. Load shedding in stream databases: a control-based approach. In Proceedings of the 32nd International conference on Very Large Data Bases, 787-798.
  29. WEI, Y., PRASAD, V., AND SON, S. H. 2007. QoS management of real-time data stream queries in distributed environments. In 10th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing, 241-248. https://doi.org/10.1109/ISORC.2007.49
  30. WEI, Y., SON, S. H., AND STANKOVIC, J. A. 2006. RTSTREAM: real-time query processing for data streams. In Proceedings of the 9th IEEE International Symposium on Object-Oriented Real-Time Distributed Computing, 141-150. https://doi.org/10.1109/ISORC.2006.68
  31. WILSCHUT, A. N. AND APERS, P. M. G. 1991. Dataflow query execution in a parallel mainmemory environment. In Proceedings of the First International Conference on Parallel and Distributed Information Systems, 68-77.

Cited by

  1. Playback-Rate Based Streaming Services for Maximum Network Capacity in IP Multimedia Subsystem vol.5, pp.4, 2011, https://doi.org/10.1109/JSYST.2011.2165190