Nonreplicated Static Data Allocation in Distributed Databases Using Biogeography-Based Optimization

Allocation of data is one of the key design issues of distributed database. A major cost of query execution in a distributed database system is the data transfer cost from one site to another site. The allocation of fragments among the different sites over the network plays an important role in performance of the distributed database system. The main objective of a data allocation in distributed database is to place the data fragments at different sites in such a way, so that the total data transfer cost can be minimized while executing a set of queries. In this paper, a new biogeography-based optimization (BBO) algorithm has been used to allocate the fragments during the design of distributed database system. The goal of this paper is to design a fragments allocation algorithm, so that the total data transmission cost can be minimized. To show the performance of proposed algorithm, results of biogeography-based optimization algorithm for data allocation are compared with genetic algorithm.

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Distributed database system of the New Atlas of Amphibians and Reptiles in Europe: the NA2RE project

Amphibia-Reptilia ◽

10.1163/15685381-00002936 ◽

2014 ◽

Vol 35 (1) ◽

pp. 33-39 ◽

Cited By ~ 10

Author(s):

Neftalí Sillero ◽

Marco Amaro Oliveira ◽

Pedro Sousa ◽

Fátima Sousa ◽

Luís Gonçalves-Seco

Keyword(s):

Spatial Data ◽

Distributed Databases ◽

Species Conservation ◽

Distributed Database ◽

Database System ◽

Data Systems ◽

Web Interface ◽

Data Infrastructure ◽

Societas Europaea ◽

Distributed Database System

The Societas Europaea Herpetologica (SEH) decided in 2006 through its Mapping Committee to implement the New Atlas of Amphibians and Reptiles of Europe (NA2RE: http://na2re.ismai.pt) as a chorological database system. Initially designed to be a system of distributed databases, NA2RE quickly evolved to a Spatial Data Infrastructure, a system of geographically distributed systems. Each individual system has a national focus and is implemented in an online network, accessible through standard interfaces, thus allowing for interoperable communication and sharing of spatial-temporal data amongst one another. A Web interface facilitates the access of the user to all participating data systems as if it were one single virtual integrated data-source. Upon user request, the Web interface searches all distributed data-sources for the requested data, integrating the answers in an always updated and interactive map. This infrastructure implements methods for fast actualisation of national observation records, as well as for the use of a common taxonomy and systematics. Using this approach, data duplication is avoided, national systems are maintained in their own countries, and national organisations are responsible for their own data curation and management. The database could be built with different representation levels and resolution levels of data, and filtered according to species conservation matters. We present the first prototype of NA2RE, composed of the last data compilation performed by the SEH (Sillero et al., 2014). This system is implemented using only open source software: PostgreSQL database with PostGIS extension, Geoserver, and OpenLayers.

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Subquery Allocation Problem and Heuristics for Secret Sharing Distributed Database System

Journal of Computer Systems Networks and Communications ◽

10.1155/2010/984059 ◽

2010 ◽

Vol 2010 ◽

pp. 1-6

Author(s):

Toshiyuki Miyamoto ◽

Takeshi Ikemura

Keyword(s):

Secret Sharing ◽

Data Transfer ◽

Optimal Solution ◽

Distributed Database ◽

Database System ◽

Allocation Problem ◽

Shared Data ◽

Distributed Database System ◽

Feasible Solutions

We discuss query optimization in a secure distributed database system, called the Secret Sharing Distributed DataBase System (SSDDBS). We have to consider not only subquery allocations to distributed servers and data transfer on the network but also decoding distributed shared data. At first, we formulated the subquery allocation problem as a constraints satisfaction problem. Since the subquery allocation problem is NP-complete in general, it is not easy to obtain the optimal solution in practical time. Secondly, we proposed aheuristic evaluationfunction for the best-first search. We constructed an optimization model on an available optimization software, and evaluated the proposed method. The results showed that feasible solutions could be obtained by using the proposed method in practical time, and that quality of the obtained solutions was good.

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Implementasi Sistem Interkoneksi Basis Data Terdistribusi Menggunakan Socket API

Jurnal Komtika ◽

10.31603/komtika.v1i1.1680 ◽

2017 ◽

Vol 1 (1) ◽

pp. 1-4

Author(s):

Ary Yulianto

Keyword(s):

Information System ◽

Big Data ◽

Human Resources ◽

Distributed Databases ◽

Distributed Database ◽

Database System ◽

Master Data ◽

Distributed Database System ◽

The Moment ◽

Asset Data

Majelis Pendidikan Dasar dan Menengah Pimpinan Daerah Kabupaten Magelang needs information about the development of the school. The necessary data include data on human resources, asset data and data of their students. At the moment the data is obtained manually by looking to the schools. With the development of information technology is now expected to have a school information system that can provide information quickly and accurately. Data on each school if put into one large server or big data can be used to analyze the data. The purpose of this research is to implement the interconnection of distributed database system using the socket API. It is used to provide master data of all schools under Persyarikatan Muhammadiyah. To support the analysis of the data interconnection of distributed databases, socket API technology is used. With a system like this then the communications database can be connected so that the school's data will be sent directly through the socket API and the data will automatically be processed by the webservice in the server middleware and will be utilized in the next process.

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Algorithm Development, Simulation Analysis and Parametric Studies for Data Allocation in Distributed Database Systems

Advanced Topics in Database Research, Volume 1 ◽

10.4018/978-1-930708-41-9.ch009 ◽

2002 ◽

pp. 157-189

Author(s):

Amita Goyal Chin

Keyword(s):

Simulation Analysis ◽

Database Systems ◽

Distributed Database ◽

Database System ◽

Data Allocation ◽

Distributed Database Systems ◽

Data Reorganization ◽

Incremental Growth ◽

Efficient Data ◽

Distributed Database System

In a distributed database system, an increase in workload typically necessitates the installation of additional database servers followed by the implementation of expensive data reorganization strategies. We present the Partial REALLOCATE and Full REALLOCATE heuristics for efficient data reallocation. Complexity is controlled and cost minimized by allowing only incremental introduction of servers into the distributed database system. Using first simple examples and then, a simulator, our framework for incremental growth and data reallocation in distributed database systems is shown to produce near optimal solutions when compared with exhaustive methods.

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Incremental Data Allocation and Reallocation in Distributed Database Systems

Data Warehousing and Web Engineering ◽

10.4018/978-1-931777-02-5.ch007 ◽

2011 ◽

pp. 137-160 ◽

Cited By ~ 9

Author(s):

Amita Goyal Chin

Keyword(s):

Database Systems ◽

Distributed Database ◽

Database System ◽

Data Allocation ◽

Distributed Database Systems ◽

Data Reorganization ◽

Incremental Growth ◽

Efficient Data ◽

Distributed Database System ◽

Database Servers

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A Data Allocation Strategy Algorithm for Large Databases Based on Genetic Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.268-270.898 ◽

2011 ◽

Vol 268-270 ◽

pp. 898-903

Author(s):

Xiao Feng Li ◽

Yuan Xin Tang ◽

Cui Cui Gong

Keyword(s):

Computer Network ◽

Great Influence ◽

Distributed Database ◽

Database System ◽

Data Availability ◽

Data Allocation ◽

Large Databases ◽

System Improvement ◽

Distributed Database System ◽

Allocation Strategies

The distributed database system is the product that the database system combines with the computer network system. The data distribution problem has great influence on distributed database application system improvement, data availability, the efficiency and reliability of the distributed database. The allocation strategies in this paper have used some excellent properties in genetic algorithms, including higher parallelism and robustness, the realization of standard way, and to maintain good balance between the depth prior search and breadth prior search, etc, so the allocation strategies in this article's have high execution efficiency, with stronger ability in seeking the best global solution and easy to realize.

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