Fragmentation is a design technique widely used in multimedia databases, because it produces substantial benefits in reducing response times, causing lower execution costs in each operation performed. Multimedia databases include data whose main characteristic is their large size, therefore, database administrators face a challenge of great importance, since they must contemplate the different qualities of non-trivial data. These databases over time undergo changes in their access patterns. Different fragmentation techniques presented in related studies show adequate workflows, however, some do not contemplate changes in access patterns. This paper aims to provide an in-depth review of the literature related to dynamic fragmentation of multimedia databases, to identify the main challenges, technologies employed, types of fragmentation used, and characteristics of the cost model. This review provides valuable information for database administrators by showing essential characteristics to perform proper fragmentation and to improve the performance of fragmentation schemes. The reduction of costs in fragmentation methods is one of the most desired main properties. To fulfill this objective, the works include cost models, covering different qualities. In this analysis, a set of characteristics used in the cost models of each work is presented to facilitate the creation of a new cost model including the most used qualities. In addition, different data sets or reference points used in the testing stage of each work analyzed are presented.

Data fragmentation and replication are an essential issue in cloud databases, since information demands are huge and improving performance through distributed database design techniques is a necessity. This paper aims to provide a review of the literature about data fragmentation and replication methods applied in a cloud environment in the last eight years, to determine if the methods take into account both techniques (fragmentation and replication) together, consider a cloud database, are easy to implement, are focused on improving the performance of the database, are complete (i.e., the paper includes all the necessary information to implement the method), and if they provide a cost model. To meet this objective we analyzed and classified 83 papers concerning data fragmentation and replication techniques. Finally, we selected the best method of our comparative analysis and presented an architecture of a web application for data fragmentation and replication in the cloud based on such method.

At present, the demand for information in distributed database systems is large and growing day by day. While this is happening, new challenges arise to improve the performance of the databases. Data fragmentation and replication methods have a leading role in distributed systems over the cloud, which is why this paper presents the design of a horizontal fragmentation, allocation and replication method in the cloud. This research proposes an algorithm for solving the problem of overlapping horizontal fragments in a data fragmentation and replication method in the cloud. The design of a Web application using the aforementioned method is also presented, this allows the fragmentation, assignment and replication scheme proposed by the method to be directly applied on a distributed database.

Multimedia databases store high-volume data, which causes problems in efficient information retrieval, and increases execution costs and response times of the queries. To solve this problem, data fragmentation techniques exist to improve query performance, increase information availability, and efficiently execute more operations accessing less irrelevant data. This article presents a comprehensive review of 34 methods related to hybrid fragmentation and subsequently proposes the design of a hybrid fragmentation method that adapts the scheme according to workload changes to maintain efficient retrieval of multimedia data. The proposed technologies are Java as a programming language, Java Server Faces (JSF) as a framework, MySQL and MongoDB database management systems, and NetBeans as an Integrated Development Environment (IDE), following the UWE methodology (Unified Modeling Language-based Web Engineering).

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.