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The database system (DBS) (Garcia-Molina H., & Salem, K.,1992; Ramakrishnan, R., & Gehrke, J., 2000; Ullman, J. D., 1984) is a set of data items that can be accessed concurrently by multiple people in the network. It can be classified into two categories: (i) centralized DBS, and (ii) distributed DBS. A centralized DBS is limited to only one location and is comprised of a single processor with its associated hardware. A centralized database system provides greater reliability, lesser overhead, and a centralized control point while a distributed database system (DDBS) is an advanced variant of a centralized DBS. A DDBS (Garcia-Molina et al., 1990; Bernstein et al., 1987) is a set of sites that are connected through the communication network offering additional benefits such as fault tolerance, stability, etc.
The RTDBS is the evolution of DDBS that offers the predefined functionality of traditional DDBS along with real time property such as timeliness (Wei Y., 2004). This database system is widely used in the system where programs have the primary requirement to meet the deadline and secondary to satisfy the strict consistency. As the demand for such a database system grows, reliable processing of large quantities of temporal and non-temporal data items is needed (Wei Y., 2004). The distributed real-time database system (DRTDBS) is thus designed to manage temporal and non-temporal data objects effectively. To further improve the performance of DRTDBS, several researchers have researched Concurrency Control Protocol (Ulusoy O., 1998), Commit Protocol (Shanker U., 2006), and other relevant issues (Shanker U., 2008).
The replication technique (Son S. H., 1987; Son S. H. and Spiros Kouloumbis, 1993; Son S. H. et al., 1995; Xiong M. et al., 2002; Kim Y. K., 1996; Peddi P., 2002; Gustavsson S. et al., 2004; Gustavsson S. et al., 2005; Syberfeldt S., 2007, Haj S. A. et al., 2008; El-Bakry et al., 2012; Mathiason G., 2007; Shrivastava, P., & Shanker, U. 2018, August; Shrivastava P. & Shanker U., 2018a; Shrivastava P. & Shanker U., 2018b; Shrivastava P. & Shanker U., 2019a; Shrivastava P. & Shanker U., 2019b; Shrivastava P. & Shanker U., 2019c; Shrivastava P. & Shanker U., 2020a; Shrivastava P. & Shanker U., 2020b; Shrivastava P., 2020; Shrivastava P. & Shanker U., 2020c; Shrivastava P. & Shanker U., 2020d; Shrivastava P. & Shanker U., 2021; Srivastava A. et al. 2012) is one of the most focused subareas for research in the DRTDBS. This technique enhances the performance of the system in terms of availability, scalability, efficiency, and fault tolerance. In this technique, data copies are redundantly positioned at various locations so that admitted real-time operations from the user executed locally. The data copies are either fully replicated, partly replicated, or not replicated, (i.e., the decision to replicate the data replica on the client site will depend on the demand from the application and client). The primary requirement for realizing the benefits of the replication technique is the design of effective and efficient RPCL, and conflict detection/resolution strategy. Hence, the majority of researchers have researched on designing conflict detection/resolution strategy and RPCL. An RPCL processes on the database kernel and manages the mutual consistency between different data replicas. The mutual consistency between different data replicas is achieved by scheduling the local and global RTT correctly (i.e., all replica sites should receive the updates gradually or immediately). Existing RPCLs (Son S. H., 1987; Son S. H. and Spiros Kouloumbis, 1993; Son S. H. et al., 1995; Xiong M. et al., 2002; Kim Y. K., 1996; Peddi P., 2002; Gustavsson S. et al., 2004; Gustavsson S. et al., 2005; Syberfeldt S., 2007, Haj S. A. et al., 2008; El-Bakry et al., 2012; Mathiason G., 2007; Shrivastava, P., & Shanker, U. 2018, August; Shrivastava P. & Shanker U., 2018a; Shrivastava P. & Shanker U., 2018b; Shrivastava P. & Shanker U., 2019a; Shrivastava P. & Shanker U., 2019b; Shrivastava P. & Shanker U., 2019c; Shrivastava P. & Shanker U., 2020a; Shrivastava P. & Shanker U., 2020b; Shrivastava P., 2020; Shrivastava P. & Shanker U., 2020c; Shrivastava P. & Shanker U., 2020d; Shrivastava P. & Shanker U., 2021; Srivastava A. et al. 2012) cause improper resource utilization and suffer from large communication costs, which create a hard challenge in meeting the demand for timeliness and mutual consistency. Hence, it is necessary to design a solution that efficiently utilizes the system resource and decreases the communication cost. To solve this problem, in the current paper we have opted for the concept of data sequence mining.