A high-performance computing method for data allocation in distributed database systems

2007 ◽  
Vol 39 (1) ◽  
pp. 3-18 ◽  
Author(s):  
Ismail Omar Hababeh ◽  
Muthu Ramachandran ◽  
Nicholas Bowring
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Database Systems ◽  
Distributed Database ◽  
Data Allocation ◽  
Distributed Database Systems ◽  
Computing Method ◽  
Performance Computing

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.

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.

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