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.

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.

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.

AN OPTIMAL STATIC PESSIMISTIC SCHEME FOR FAULT TOLERANT DISTRIBUTED DATABASE SYSTEMS

1994 ◽  
Vol 01 (03) ◽  
pp. 365-378
Author(s):  
HOANG PHAM ◽  
DAVID POTOSKI
Keyword(s):  
Fault Tolerant ◽  
Database Systems ◽  
Distributed Database ◽  
Optimal Number ◽  
Data Consistency ◽  
Total System ◽  
Distributed Database Systems ◽  
Replication Control ◽  
Distributed Database System ◽  
Quorum Consensus

A distributed database system often replicates data across its servers to provide a fault-resistant application, which maximizes server availability. Various replication control protocols have been developed to ensure data consistency. In this paper, we develop optimal design methods for the quorum-consensus replication protocol, which (1) maximizes availability of the distributed database systems and (2) minimizes the total system cost by calculating the optimal read quorum and the optimal number of system servers. Several numerical examples and applications are provided to illustrate the results.

scholarly journals From Classical to Fuzzy Databases in a Production Enterprise

2020 ◽  
Vol 26 (11) ◽  
pp. 1382-1401
Author(s):  
Izabela Rojek ◽  
Dariusz Mikołajewski ◽  
Piotr Kotlarz ◽  
Alžbeta Sapietová
Keyword(s):  
Business Intelligence ◽  
Relational Databases ◽  
Distributed Databases ◽  
Database Systems ◽  
Distributed Database ◽  
Data Warehouses ◽  
Distributed Database Systems ◽  
Fuzzy Database ◽  
The One ◽  
Global World

This article presents the evolution of databases from classical relational databases to distributed databases and data warehouses to fuzzy databases used in a production enterprise. This paper discusses characteristics of this kind of enterprise. The authors precisely define centralized and distributed databases, data warehouses and fuzzy databases. In the modern global world, many companies change their management strategy from the one based on a centralized database to an approach based on distributed database systems. Growing expectations regarding business intelligence encourage companies to deploy data warehouses. New solutions are sought as the demand for engineers' expertise continues to rise. The requested knowledge can be certain or uncertain. Certain knowledge does not any problems and is easy to obtain. However, uncertain knowledge requires new ways of obtaining, including the use of fuzzy logic. It is from where the fuzzy database approach takes its beginning. The above-mentioned strategies of a production enterprise were described herein as a case of special interest.

scholarly journals A Survey On Fragmentation In Distributed Database Systems

2021 ◽  
Author(s):  
Mohsen Taki ◽  
Mohammadreza Mollahoseini Ardakani
Keyword(s):  
Computer Network ◽  
Database Systems ◽  
Distributed Database ◽  
Primary Concern ◽  
Design And Optimization ◽  
Distributed Database Systems ◽  
Placement Decisions ◽  
Use Of Data ◽  
File Design ◽  
Distributed Database System

Abstract One of the most critical aspects of distributed database design and management is fragmentation. If the fragmentation is done properly, we can expect to achieve better throughput from such systems. The primary concern of DBMS design is the fragmentation and allocation of the underlying database. The distribution of data across various sites of computer networks involves making proper fragmentation and placement decisions. The first phase in the process of distributing a database is fragmentation which clusters information into fragments. This process is followed by the allocation phase which distributes, and if necessary, replicates the generated fragments among the nodes of a computer network. The use of data fragmentation to improve performance is not new and commonly appears in file design and optimization literature. An efficient functionality of any distributed database system is highly dependent on its proper design in terms of adopted fragmentation and allocation methods. Fragmentations of large, global databases are performed by dividing the database horizontally, vertically or combination of both. In order to enable the distributed database systems to work efficiently, the fragments have to be allocated across the available sites in such a way that reduces communication cost of data.In this article, we have tried to describe the existing methods of database fragmentation and have an overview of the existing methods. Finally, we conclude with suggestions for using machine learning to solve the overlap problem in fragments.

scholarly journals A Survey on Efficient Concurrency Control Algorithm in Distributed Database Systems

2019 ◽  
pp. 1176-1185
Author(s):  
Rebecca Nyasuguta Arika ◽  
W. Cheruiyot
Keyword(s):  
Concurrency Control ◽  
Control Algorithm ◽  
Distributed Databases ◽  
Database Systems ◽  
Distributed Database ◽  
Communication Overhead ◽  
Distributed Database Systems ◽  
Commit Protocols ◽  
Message Exchange ◽  
Transaction Commit

Transaction commit protocols help in reaching an agreement among the participating nodes when a transaction has to be committed or aborted. To initiate an agreement each participating node is asked to vote its decision on the operations on its transactional fragment. The participating nodes can decide to either commit or abort an ongoing transaction. In case of a node failure, the active participants take essential steps such as running the termination protocol to preserve database correctness. This paper sought to investigate the current distributed databases commit protocols such as 2PC and 3PC in order to pin-point their shortcomings. For instance, 2PC suffers from blocking of participant site in case of coordinator failure and increased latency due to forced writes of logs. On its part, 3PC suffers more communication overhead due to extra pre-commit phase. Based on these setbacks, an efficient protocol is suggested towards the end of this paper that it believed to address some of the challenges such as blocking and extra message exchange between communicating nodes.

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