Abstract
In many of recent applications data are received as infinite, continuous, rapid and time varying data streams. Real-time processing of queries over such streams is essential in most of the applications. Single processor systems are not capable to provide the desired speed to be real-time. Parallelism over multiprocessors can be used to handle this deficit. In such a system, a multiprocessor real-time scheduling algorithm must be used. Generally, multiprocessor real-time scheduling algorithms fall into two approaches: Partitioning or Global. The partitioning approach has acceptable overhead but can NOT be optimal. The global approach can be but it has considerable overheads.
In this paper, a multiprocessor real-time scheduling algorithm for a DSMS is proposed that employs hybrid approach. It is shown that it is optimal while has minimum overheads. Also, simulation results illustrate that the proposed hybrid multiprocessor real-time scheduling algorithm outperforms algorithms that use either portioning approach or global approach.
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References
Holman, P., Anderson, J.: Group-based Pfair Scheduling. Real-Time Systems 32(1-2), 125–168 (2006)
Carpenter, J., et al.: A Categorization of Real-time Multiprocessor Scheduling Problems and Algorithms. In: Handbook on Scheduling: Algorithms, Models and Performance Analysis (2004)
Stankovic, J.A., et al.: Misconceptions About Real-Time Databases. Journal of Computer 32(6) (June 1999)
Sha, L., et al.: Real Time Scheduling Theory: A Historical Perspective. Real-Time Systems 28, 101–155 (2004)
Baruah, N., et al.: Proportionate progress: A notion of fairness in resource allocation. Algorithmica 15, 600–625 (1996)
Baruah, S., Gehrke, J., Plaxton, C.: Fast scheduling of periodic tasks on multiple resources. In: Proceedings of the 9th International Parallel Processing Symposium, pp. 280–288 (April 1995)
Anderson, J., Srinivasan, A.: Mixed Pfair/ERfair Scheduling of Asynchronous Periodic Tasks. Journal of Computer and System Sciences 68(1), 157–204 (2004)
Srinivasan, A.: Effcient and Flexible Fair Scheduling of Real-time Tasks on Multiprocessors., Ph. D. thesis, University of North Carolina at Chapel Hill (2003)
Lopez, J., Garcia, M., Diaz, J., Garcia, D.: Worst-case utilization bound for EDF scheduling on real-time multiprocessor systems. In: Proceedings of the 12th Euromicro Conference on Real-time Systems, pp. 25–33 (June 2000)
Srinivasan, A., Anderson, J.H.: Efficient Scheduling of Soft Real-time Applications on Multiprocessors. Journal of Embedded Computing 1(3) (June 2004)
Holman, P., Anderson, J.H.: Using Supertasks to Improve Processor Utilization in Multiprocessor Real-time Systems. In: 15th Euromicro Conference on Multiprocessor Real-Time Systems, ECRTS (2003)
Safaei, A., et al.: QRS: A Quick Real-Time Stream Management System. Submitted to Journal of Real-Time Systems (November 2010)
Alemi, M.: mplementation of a Real-Time DSMS prototype, M. Sc. Thesis, Iran University of Science and Technology (2010)
Safaei, A., Haghjoo, M.S.: Parallel Processing of Continuous Queries over Data Streams. Distributed and Parallel Databases 28(2-3), 93–118 (2010)
Safaei, A., Haghjoo, M.S.: Dispatching of Stream Operators in Parallel Execution of Continuous Queries. Submitted to the Journal of Supercomputing (July 2010)
Safaei, A., et al.: Hybrid Multiprocessor Real-Time Scheduling Approach. International Journal of Computer Science Issues, 8(2) (2011)
Ghalambor, M., Safaeei, A.A.: DSMS scheduling regarding complex QoS metrics. In: IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), May10-13 (2009)
Safaei, A., et al.: Using Finite State Machines in Processing Continuous Queries. International Review on Computers and Software 4(5) (September 2009)
Ramamritham, K., Son, S.H., DiPippo, L.C.: Real-Time Databases and Data Services. The Journal of Real-Time Systems 28(2-3), 179–215 (2004)
Haritsa, J., et al.: Data Access Scheduling in Firm Real-Time Database Systems. The Journal of Real-Time Systems 4, 203–241 (1992)
Schmidt, S., et al.: Real-time Scheduling for Data Stream Management Systems. In: Proceedings of the 17th Euromicro Conference on Real-Time Systems, ECRTS 2005 (2005)
Graham, M. H.: Issues In Real-Time Data Management, Technical Report, Software Engineering Institute, Carnegie Mellon University Pittsburgh, Pennsylvania (July 1991)
Kang, K.D., Son, S., Stankovic, J.: Specifying and Managing Quality of Real-Time Data Services. IEEE TKDE, University of Virginia (2004)
Aldarmi, S.A.: Real-time database systems: concepts and design. Department of Computer Science, University of York (1998)
Garcia-Molina, H., Salem, K.: Main Memory Database Systems: An Overview. IEEE Transactions on Knowledge and Data Engineering 4(6) (December 1992)
Adelberg, B.S.: Strip: A Soft Real-Time Main Memory Database for Open Systems, PhD. Thesis, Stanford university (1997)
Gruenwald, L., Liu, S.: A performance study of concurrency control in a real-time main memory database system. ACM SIGMOD Record 22(4) (December 1993)
Babcock, B., et al.: Models and issues in data stream systems. In: Proceedings of the Twenty-first ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (2003)
Stonebraker, M., et al.: The 8 Requirements of Real-Time Stream Processing. SIGMOD Records 34(4) (December 2005)
Johnson, T., et al.: Query-Aware Partitioning for Monitoring Massive Network Data Streams. In: Proc. Of SIGMOD (2008)
Kang, K.D., Son, S., Stankovic, J.: Specifying and Managing Quality of Real-Time Data Services. IEEE TKDE, University of Virginia (2004)
Aldarmi, S.A.: Real-time database systems: concepts and design. Department of Computer Science, University of York (1998)
The internet traffic archive, http://ita.ee.lbl.gov/html/contrib/DEC-PKT.html (last accessed on January 2011)
Babcock, B., et al.: Models and Issues in Data Stream Systems. In: Invited paper in Proc. Of PODS (June 2002)
The STREAM Group. STREAM: The Stanford Stream Data Manager. IEEE Data Engineering Bulletin (March 2003)
Abadi, et al.: Aurora: A New Model and Architecture for Data Stream Management. VLDB Journal 2(12), 120–139 (2003)
Ou, Z., Yu, G., Yu, Y., Wu, S., Yang, X., Deng, Q.: Tick Scheduling: A Deadline Based Optimal Task Scheduling Approach for Real-Time Data Stream Systems. In: Fan, W., Wu, Z., Yang, J. (eds.) WAIM 2005. LNCS, vol. 3739, pp. 725–730. Springer, Heidelberg (2005)
Nehme, R.V., et al.: Tagging Stream Data for Rich Real-Time Services. In: Proc. of VLDB (2009)
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Safaei, A.A., Haghjoo, M.S., Abdi, F. (2011). PFGN: A Hybrid Multiprocessor Real-Time Scheduling Algorithm for Data Stream Management Systems. In: Cherifi, H., Zain, J.M., El-Qawasmeh, E. (eds) Digital Information and Communication Technology and Its Applications. DICTAP 2011. Communications in Computer and Information Science, vol 167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22027-2_16
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DOI: https://doi.org/10.1007/978-3-642-22027-2_16
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