The International Arab Journal of Information Technology (IAJIT)

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Intelligent Replication for Distributed Active Real- Time Databases Systems

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Recently, the demand for real-time database is increasing. Most real-time systems are inherently distributed in nature and need to handle data in a timely fashion. Obtaining data from remote sites may take long time making the temporal data invalid. This results in a large number of tardy transactions with their catastrophic effect. Replication is one solution of this problem, as it allows transactions to access temporal data locally. This helps transactions to meet their time requirements which require predictable resource usage. To improve predictability, Distributed Active Real-time Database System (DeeDS) prototype is introduced to avoid the delay which results from disk access, network communications and distributed commit processing. DeeDS advises to use In-memory database, fully replication and local transaction committing, but full replication consumes the system resources causing a scalability problem. In this work, we introduce Intelligent Replic


[1] Adelberg B., Molina H., and Kao B., Applying Update Streams in a Soft Real-Time Database System, in Proceedings of the ACM SIGMOD International Conference on Management of Data, San Jose, pp. 245-256, 1995.

[2] Andler S., Hansson J., Eriksson J., Mellin J., Berndtsson M., and Eftring B., DeeDS Towards A Distributed and Active Real-Time Database System, SIGMOD Record, vol. 25, no. 1, pp. 38-51, 1996.

[3] Aslinger A. and Son S., Efficient Replication Control in Distributed Real-Time Databases, in Proceedings of the 3rd ACS/IEEE International Conference on Computer Systems and Applications, Cairo, pp. 34, 2005.

[4] Chen T., Bahsoon R., and Tawil A., Scalable Service-Oriented Replication with Flexible Consistency Guarantee in the Cloud, Information Sciences, vol. 264, pp. 349-370, 2014.

[5] Galeana D., Pacheco H., and Magadan A., Analysis of Clustering Algorithms for Image Segmentation and Numerical Databases, in Proceedings of the Electronics, Robotics and Automotive Mechanics Conference, Morelos, pp. 288-292, 2008.

[6] Hababeh I., Improving Network Systems Performance by Clustering Distributed Database Sites, The Journal of Supercomputing, vol. 59, no. 1, pp. 249-267, 2012.

[7] Hamdi S., Salem M., Bouazizi R., and Bouazizi E., Management of Real-Time Data in Distributed Real Time DBMS Using Semi-Total Replication Data, in Proceedings of the International Conference on Computer Systems and Applications, Ifrane, pp. 1-4, 2013.

[8] Hauglid H., Ryeng N., and Norvag K., DYFRAM: Dynamic Fragmentation and Replica Management in Distributed Database Systems, Distrib Parallel Databases, vol. 28, no. 2-3, pp. 157-185, 2010.

[9] Jaing X., Li J., Xi H., and Hongsheng X., Distributed Algorithms for a Replication Problem of Popular Network Data, Journal of Network and Systems Management, vol. 24, no. 1, pp. 34-56, 2014.

[10] Jannu S. and Jana P., Energy Efficient Grid Based Clustering and Routing Algorithms for Wireless Sensor Networks, in Proceeding of the 4th International Conference on Communication Systems and Network Technologies, Bhopal, pp. 63-68, 2014.

[11] Laarabi M., Boulmakoul A., Sacile R., and Garbolino E., A Scalable Communication Middleware for Real-Time Data Collection of Dangerous Goods Vehicle Activities, Transportation Research Part C: Emerging Technologies, vol. 48, pp. 404-417, 2014.

[12] Lin W. and Veeravalli B., A Dynamic Object Allocation and Replication Algorithm for Distributed Systems with Centralized Control, International Journal of Computers and Applications, vol. 28, no. 1, pp. 26-34, 2006.

[13] Malliaros F. and Vazirgiannis M., Clustering and Community Detection in Directed Networks: A Survey, Physics Reports, vol. 533, no. 4, pp. 95-142, 2013.

[14] Mathiason G., Andler S., and Jagszent D., Virtual Full Replication by Static Segmentation for Multiple Properties of Data Objects, in Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Replication by Static Segmentation for Multiple Properties of Data Objects, Sweden, pp. 1-8, 2005.

[15] Mathiason G., Andler S., and Son S., Virtual Full Replication by Adaptive Segmentation, in Proceedings of the 13th International Conference on Embedded and Real-Time Computing Systems and Applications, Daegu, pp. 327-336, 2007.

[16] Rajaretnam K., Rajkumar M., and Venkatesan R., RPLB: A Replica Placement Algorithm in Data Grid with Load Balancing, The International Arab Journal of Information Technology, vol. 13, no. 6, pp. 635-643, 2016.

[17] Said A., Sadeg B., Ayeb B., and Amanton L., The DLR-ORECOP Real-Time Replication Control Protocol, in Proceedings of the IEEE Conference on Emerging Technologies and Factory Automation, Mallorca, pp. 1-8, 2009.

[18] Santos R., Bernardino J., and Vieira M., Leveraging Availability and Performance for Distributed Real Time Data Warehouse, in Proceedings of the IEEE 36th Annual Computer 513 Intelligent Replication for Distributed Active Real-Time Databases Systems Software and Applications Conference, Izmir, pp. 654-659, 2012.

[19] Sultan T., El-Bakry H., and Hameed H., Design of Efficient Dynamic Replica Control Algorithm for Periodic/Aperiodic Transactions in Distributed Real-Time Databases, International Journal of Computer Science Issues, vol. 9, no. 2, pp. 72-80, 2012.

[20] Sun Q., Qiu Y., Shao Y., and Yan W., Implementation of Massive Real-Time Database System Using Network Sensors and Sector Operation, Sensors and Transducers, vol. 174, no. 7, pp. 123-128, 2014.

[21] Tiwari S., Sharma A., and Swaroop V., Distributed Real Time Replicated Database: Concept And Design, International Journal of Engineering Science and Technology, vol. 3, no. 6, pp. 4839-4848, 2011.

[22] Wang J., Han S., Lam K., and Mok A., Maintaining Data Temporal Consistency in Distributed Real-Time Systems, Real-Time System, vol. 48, no. 4, pp. 387-429, 2012.

[23] Wang W. and Fan S., Application of Data Mining Technique in Customer Segmentation of Shipping Enterprises, in Proceedings of the 2nd International Workshop on Database Technology and Applications, Wuhan, pp.1-4, 2010.

[24] Xu Ch., Sharaf M., Zhou X., and Zhou A., Quality-Aware Schedulers for Weak Consistency Key-Value Data Stores, Distrib Parallel Databases, vol. 32, no. 4, pp. 535-581, 2014.

[25] Zaki M. and Meira W., Data Mining and Analysis: Fundamental Concepts and Algorithms, Cambridge University Press, 2014. Rashed Salem He received his PhD degree in computer science from the University of Lyon 2, France in 2012. He has been a member of Complex Data Warehousing and On-Line Analysis research group within the ERIC laboratory. He is a lecturer at Faculty of Computers and Information, Menoufia University, Egypt. His current research interests mainly relate to database, business intelligence (BI), data warehousing and Big Data. Safa a Saleh Currently, she is a Lecturer in Information systems department, Taibah University. She received B.Sc. from Alexandria University. She awarded High Diploma, M.Sc. (by research) in information systems -College of Computing and Information Technology, Arab Academy for Science, Alexandria, 2005 and 2008 respectively. Ph.D. degree in Information System, Menoufia University, Egypt. She has contributed papers in the areas of Data mining, Distributed DB applications and bioinformatics. Hattem Abdul-Kader He obtained his B.S. and M.SC. (by research) in Electrical Engineering from the Alexandria University, Faculty of Engineering, Egypt in 1990 and 1995 respectively. He obtained his Ph.D. degree in Electrical Engineering also from Alexandria University, Faculty of Engineering, and Egypt in 2001 specializing in neural networks and applications. He is currently a Lecturer in Information systems department, Faculty of Computers and Information, Menoufia University, Egypt since 2004. He has contributed more than 30+ technical papers in areas of Neural networks, DB applications,Information security and Internet applications.