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Wireless Personal Communications
Published in: Wireless Personal Communications 2/2021

23-11-2020

Prediction Based QoS Management in Replicated DRTDBS

Authors: Pratik Shrivastava, Udai Shanker

Published in: Wireless Personal Communications | Issue 2/2021

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Abstract

In a distributed real time database system (DRTDBS), replication technique is used to easily meet the timeliness demand of real time transactions. The features of replication technique depend on the Replication Protocols (RPLs). Existing RPLs are kernel-based which is tightly linked with the concurrency control protocol and confined to a vendor-specific database. Middleware is the evolution of the kernel-based RPL that shifts the load of maintaining mutual consistency from the database kernel to the middleware server. Middleware based RPLs suffer from the issue of QoS, security-constraint, and dependency relationship. Here, our objective is to maintain the QoS during overload occurrence in the replicated DRTDBS (RDRTDBS). The proposed framework in this paper consists of a system model for expressing QoS requirements, a middleware extended with the prediction technique to predict the RTT processing time, and a set of policies to guarantee QoS. The performance of our proposed algorithms is compared with other baseline approaches and simulation results show that it outperforms a set of existing algorithms that use feedback control to overcome overload.
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Literature
1.
Alhalabi, F., Narkoy, B., Aubry, R., Maranzana, M., Morel, L., & Sourrouille, J. L. (2008). Centralized vs. decentralized QoS management policy. In 2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications, (pp. 1–6).
2.
Amirijoo, M., Hansson, J., & Son, S. H. (2003). Error-driven QoS management in imprecise real-time databases. In Proceedings of the 15th Euromicro Conference on Real-Time Systems, 2003, (pp. 63–72).
3.
Baccouche, L. (2006). An overview of MOA, a multi-class overload architecture for real-time database systems: framework and algorithms. In IEEE International Conference on Computer Systems and Applications, (pp. 756–763).
4.
Bishop, T. A., & Karne, R. K. (2003). A Survey of Middleware. Computers and Their Applications, (pp. 254–258).
5.
Chauhan, N., & Tripathi, S. P. (2019). QoS aware replica control strategies for distributed real time database management system. Wireless Personal Communications, 104(2), 739–752.CrossRef
6.
Datta, A., Mukherjee, S., Konana, P., Viguier, I. R., & Bajaj, A. (1996). Multiclass transaction scheduling and overload management in firm real-time database systems. Information Systems, 21(1), 29–54.CrossRef
7.
Gustavsson, S., & Andler, S. F. (2004). Real-time conflict management in replicated databases. In Proceedings of the Fourth Conference for the Promotion of Research in IT at New Universities and University Colleges in Sweden (PROMOTE IT 2004), Karlstad, Sweden, 2, (pp. 504–513).
8.
Gustavsson, S., & Andler, S. R. (2005). Continuous consistency management in distributed real-time databases with multiple writers of replicated data. In 19th IEEE International Parallel and Distributed Processing Symposium, (p. 8).
9.
Hansson, J., Son, S. H., Stankovic, J. A., & Andler, S. F. (1998). Dynamic transaction scheduling and reallocation in overloaded real-time database systems. In Proceedings Fifth International Conference on Real-Time Computing Systems and Applications (Cat. No. 98EX236), (pp. 293–302).
10.
Haritsa, J. R., Livny, M., & Carey, M. J. (1991). Earliest deadline scheduling for real-time database systems. In [1991] Proceedings Twelfth Real-Time Systems Symposium, (pp. 232–242).
11.
Kang, K. D., Son, S. H., Stankovic, J. A., & Abdelzaher, T. F. (2002). A QoS-sensitive approach for timeliness and freshness guarantees in real-time databases. In Proceedings 14th Euromicro Conference on Real-Time Systems. Euromicro RTS 2002, (pp. 203–212).
12.
Kang, K. D., Son, S. H., & Stankovic, J. A. (2002). Service differentiation in real-time main memory databases. In Proceedings Fifth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing. ISIRC, (pp. 119–128), (2002).
13.
Kang, K. D. (2018). Enhancing timeliness and saving power in real-time databases. Real-Time Systems, 54(2), 484–513.CrossRef
14.
Kim, Y. K., & Son, S. H. (1993). An approach towards predictable real-time transaction processing. Citeseer, (pp. 70–75).
15.
Kim, Y. K. (1996). Towards real-time performance in a scalable, continuously available telecom DBMS, Citeseer
16.
M’barek, S., Baccouche, L., & Ghezala, H. B. (2008) An evaluation of QoS management approaches in real-time databases. In Third International Conference on Systems (icons 2008), (pp. 41–46).
17.
M’barek, S., Baccouche, L., & Ghezala, H. B. (2008). Feedback control based model of QoS management approaches in Real-Time databases. In 2008 Second International Conference on Research Challenges in Information Science, (pp. 409–414).
18.
Mathiason, G., Andler, S. F., & Son, S. H. (2007). Virtual full replication by adaptive segmentation. In13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2007), (pp. 327–336).
19.
O’Neil, P. E., Ramamritham, K., & Pu, C. (1996). A two-phase approach to predictably scheduling real-time transactions.
20.
Peddi, P., & DiPippo, L. C. (2002). A replication strategy for distributed real-time object-oriented databases. In Proceedings Fifth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing. ISIRC, (pp. 129–136) (2002).
21.
Saad-Bouzefrane, S., & Kaiser, C. (2003). How to manage replicated real-time databases in an overloaded distributed system, Citeseer.
22.
Said, A. H., Sadeg, B., Amanton, L., & el Ayeb, B. (2008). A protocol to control replication in distributed real-time database systems. ICEIS, 1, 501–504.
23.
24.
Shanker, U., Misra, M., & Sarje, A. K. (2008). Distributed real time database systems: Background and literature review. Distributed and Parallel Databases, 23, 127–149.CrossRef
25.
Shanker, U. (2006). Some performance issues in distributed real time database systems. In Proceedings of the VLDB PhD Workshop.
26.
Shrivastava P. & Shanker U. (2018). Replica update technique in RDRTDBS: issues & challenges. In Proceedings of the 24th International Conference on Advanced Computing and Communications (ADCOM-2018), IIIT Bangalore.
27.
28.
Shrivastava, P., & Shanker, U. (2019). Supporting transaction predictability in replicated DRTDBS. In Fahrnberger G., Gopinathan S., Parida L. (Eds.), Distributed Computing and Internet Technology, ICDCIT 2019. Lecture Notes in Computer Science, vol 11319. Springer, Cham. https://​doi.​org/​10.​1007/​978-3-030-05366-6_​10.
29.
Shrivastava, P., & Shanker, U. (2018). Replication protocol based on dynamic versioning of data object for replicated DRTDBS. International Journal of Computational Intelligence & IoT, 1(2), 154–159.
30.
Shrivastava, P., & Shanker, U. (2019). Real time transaction management in replicated DRTDBS. In Australasian Database Conference, pp. 91–103.
31.
Shrivastava P. & Shanker U. (2020). Survey on Data Replication in DRTDBS: Taxonomy and State of the Art. Journal of Advanced Research in Dynamical and Control Systems - JARDCS, 12(01-special issue) pp. 925–943.
32.
Shrivastava P. & Shanker U., Middleware Based Fault Recovery Technique for Replicated DRTDBS , International Journal of Intelligent Information and Database Systems (In Press).
33.
Son, S. H., & Kouloumbis, S. (1993). A token-based synchronization scheme for distributed real-time databases. Information Systems, 18(6), 375–389.CrossRef
34.
Son, S. H., & Zhang, F. (1995). Real-time replication control for distributed database systems: Algorithms and their performance. DASFAA, 11, 214–221.
35.
Son, S. H., Zhang, F., & Hwang, B. (1996). Concurrency control for replicated data in distributed real-time systems. Journal of Database Management (JDM), 7(2), 12–23.CrossRef
36.
Syberfeldt, S. (2007) Optimistic replication with forward conflict resolution in distributed real-time databases. Institutionen för datavetenskap.
37.
Ulusoy, O., & Belford, G. G. (1993). Real-time transaction scheduling in database systems. Information Systems, 18(8), 559–580.CrossRef
38.
Ulusoy, O. (1994). Processing real-time transactions in a replicated database system. Distributed and Parallel Databases, 2(4), 405–436.CrossRef
39.
Vienne, P., & Sourrouille, J. L. (2005). A middleware for autonomic QoS management based on learning. In Proceedings of the 5th international workshop on Software engineering and middleware, (vol. 23, pp. 1–8).
40.
Wang, N., Schmidt, D. C., Gokhale, A., Rodrigues, C., Natarajan, B., Loyall, J. P., et al. (2003). QoS-enabled middleware, Middleware for. Communications, 20, 131–162.
41.
Wang, F., Yao, L. W., & Yang, Y. L. (2011). Efficient verification of distributed real-time systems with broadcasting behaviors. Real-Time Systems, 47(4), 285.CrossRef
42.
Wei, Y., Son, S. H., Stankovic, J. A., & Kang, K. D. (2003). Qos management in replicated real-time databases, RTSS 2003. 24th IEEE Real-Time Systems Symposium, (pp. 86–97).
43.
Xiong, M., Ramamritham, K., Haritsa, J. R., & Stankovic, J. A. (2002). MIRROR: A state-conscious concurrency control protocol for replicated real-time databases. Information Systems, 27(4), 277–297.CrossRef
Metadata
Title
Prediction Based QoS Management in Replicated DRTDBS
Authors
Pratik Shrivastava
Udai Shanker
Publication date
23-11-2020
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 2/2021
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07923-w

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