A Hybrid Fragmentation Method for Multimedia Databases Considering Dynamic Access Patterns

The volume of multimedia data generated by various applications is increasing constantly. These data are complex to process, hindering efficient information retrieval because database operations require analyzing an entire database during their execution, augmenting the query execution costs and response times. In a distributed environment, fragmentation is an effective technique that aims to improve query performance and increase the availability of information. Most methods address horizontal or vertical partitioning and are static because they cannot adapt the fragmentation scheme to new changes in database access patterns or elements (attributes and/or tuples). This work presents a dynamic hybrid fragmentation method for multimedia databases that includes an observer–fragmenter developed in the Java programming language and uses the NoSQL (Not only SQL) MongoDB database. To implement the proposed method, it is first necessary to carry out static hybrid fragmentation through the XAMANA Web application. Then, the observer–fragmenter is executed, which is capable of analyzing the fragment costs and monitoring the operation and performance thresholds without the intervention of the Database Administrator (DBA). When the cost of a fragment exceeds the thresholds, a new hybrid fragmentation is automatically triggered, and new fragments are allocated to the corresponding sites. Finally, to validate our proposed method, we conduct a case study using the HITO (History of the Technological Institute of Orizaba) database and compare our method with three state-of-the-art approaches. The results show that it is possible to reduce the execution cost of 77% of queries by accessing less remote data and requiring fewer joins.