Incremental Data Allocation and Reallocation in Distributed Database Systems

2011 ◽  
pp. 137-160 ◽  
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

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.

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

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.

Performance Evaluation of Distributed Database Systems

2014 ◽  
Vol 13 (9) ◽  
pp. 4859-4867
Author(s):  
Khaled Saleh Maabreh
Keyword(s):  
Performance Evaluation ◽  
System Performance ◽  
Operation Mode ◽  
Database Systems ◽  
Distributed Database ◽  
Evaluation Study ◽  
Distributed Database Systems ◽  
Different Types ◽  
Distributed Database System ◽  
Distributed Database Management

Distributed database management systems manage a huge amount of data as well as large and increasingly growing number of users through different types of queries. Therefore, efficient methods for accessing these data volumes will be required to provide a high and an acceptable level of system performance.  Data in these systems are varying in terms of types from texts to images, audios and videos that must be available through an optimized level of replication. Distributed database systems have many parameters like data distribution degree, operation mode and the number of sites and replication. These parameters have played a major role in any performance evaluation study. This paper investigates the main parameters that may affect the system performance, which may help with configuring the distributed database system for enhancing the overall system performance.

MULTI-KEY INDEX FOR DISTRIBUTED DATABASE SYSTEM

2005 ◽  
Vol 15 (02) ◽  
pp. 433-438
Author(s):  
MD. SHAZZAD HOSAIN ◽  
MUHAMMAD ABDUL HAKIM NEWTON
Keyword(s):  
Distributed Databases ◽  
Database Systems ◽  
Distributed Database ◽  
Index Model ◽  
Network Bandwidth ◽  
Distributed Database Systems ◽  
Efficient Access ◽  
Distributed Database System ◽  
Bit Vector ◽  
Centralized Database

In this paper we present a multi-key index model that enables us to search a record with more than one attribute values in distributed database systems. Indices provide fast and efficient access of data and so become a major aspect in centralized database systems. Most of the centralized database systems use B + tree or other types of index structures such as bit vector, graph structure, grid file etc. But in distributed database systems no index model is found in the literature. Therefore efficient access is a major problem in distributed databases. Our proposed index model avoids the query-flooding problem of existing system and thus optimizes network bandwidth.

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

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Arjan Singh ◽  
Karanjeet Singh Kahlon ◽  
Rajinder Singh Virk
Keyword(s):  
Data Transfer ◽  
Distributed Databases ◽  
Distributed Database ◽  
Database System ◽  
Data Allocation ◽  
Transmission Cost ◽  
Static Data ◽  
Total Data ◽  
Transfer Cost ◽  
Distributed Database System

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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