scholarly journals Building a Retail Sysem Based on Distributed Databases Model

2019 ◽  
Vol 8 (10) ◽  
pp. 826-829
Keyword(s):  
Distributed System ◽  
Distributed Databases ◽  
Distributed Database ◽  
Database Management System ◽  
Entire System ◽  
Point Of Sale ◽  
Client Server ◽  
Processing Information ◽  
Important Field ◽  
Distributed Database Management

In recent years, distributed databases have become an important field of processing information, overcoming some limitations of centralized database such as overloading, bottlenecking while accessing, availability/ reliability of low fault tolerance. Our article proposes to build a distributed system (functions and databases) for POS (point of sale) retailers, data will be distributed across different locations but can still be linked together when required. At each location retailers can sell directly on the system (online or offline) so they can administer local databases and execute their local applications (business). Here we deploy the system on the distributed database management system based on Client-Server model. Therefore, aside from local management of data at clients (POS), there is also a server (manager) that stores data, manages and controls the entire system.

Trends in Improving Performances in Distributed Database Management Systems

2010 ◽  
pp. 396-422
Author(s):  
Ismail Omar Hababeh ◽  
Muthu Ramachandran
Keyword(s):  
Database Management ◽  
Real Life ◽  
Distributed Database ◽  
Database Management Systems ◽  
Database Management System ◽  
Management Systems ◽  
Data Allocation ◽  
Performance Improvements ◽  
Integrated Method ◽  
Distributed Database Management

Database technology has been a significant field to work in for developing real life applications in network information systems. An enterprise’s reliance on its network and database applications in Distributed Database Management systems (DDBMS) environment is likely to continue growing exponentially. In such a system the estimation and prediction of Quality of Service (QoS) performance improvements are crucial since it increases understanding the issues that affect the distributed database networking system behaviour; like database fragmentation, clustering database network sites, and data allocation and replication that would reduce the amount of irrelevant data and speed up the transactions response time. This chapter introduces the trends of database management systems DBMS and presents an integrated method for designing Distributed Relational networking Database Management System DRDBMS that efficiently and effectively achieves the objectives of database fragmentation, clustering database network sites, and fragments allocation and replication. It is based on high speed partitioning, clustering, and data allocation techniques that minimize the data fragments accessed and data transferred through the network sites, maximize the overall system throughput by increasing the degree of concurrent transactions processing of multiple fragments located in different sites, and result in better QoS design and decision support.

scholarly journals A better way for finding the optimal number of nodes in a distributed database management system

2010 ◽  
Vol 4 (2) ◽  
pp. 19-22
Author(s):  
Rashed Mustafa ◽  
Md Javed Hossain ◽  
Thomas Chowdhury
Keyword(s):  
Management System ◽  
Database Management ◽  
Database Systems ◽  
Distributed Database ◽  
Optimal Number ◽  
Database Management System ◽  
Data Fragmentation ◽  
Large Databases ◽  
Very Large Databases ◽  
Distributed Database Management

Distributed Database Management System (DDBMS) is one of the prime concerns in distributed computing. The driving force of development of DDBMS is the demand of the applications that need to query very large databases (order of terabytes). Traditional Client- Server database systems are too slower to handle such applications. This paper presents a better way to find the optimal number of nodes in a distributed database management systems. Keywords: DDBMS, Data Fragmentation, Linear Search, RMI.   DOI: 10.3329/diujst.v4i2.4362 Daffodil International University Journal of Science and Technology Vol.4(2) 2009 pp.19-22

scholarly journals Null Values Treatment in Distributed Databases

2002 ◽  
Vol 40 (1) ◽  
pp. 55-64
Author(s):  
Saran Akram Abd Al-Majeed
Keyword(s):  
Programming Languages ◽  
Relational Databases ◽  
Distributed Databases ◽  
Distributed Database ◽  
Database Management System ◽  
Data Sources ◽  
Relational Model ◽  
A Value ◽  
Null Values ◽  
Distributed Database System

There has been a great deal of discussion about null values in relational databases. The relational model was defined in 1969, and Nulls Was died in 1979. Unfortunately, there is not a generally agreeable solution for rull values problem. Null is a special marker which stands for a value undefined or unknown, which means thut ne entry has been made, a missing valuc mark is not a value and not of a date type and cannot be treated as a value by Database Management System (DBMS). As we know, distributed database users are more than a single database and data will be distributed among several data sources or sites, it must be precise data, the replication is allowed there, so complex problems will appear, then there will be need for perfect practical general approaches for treatment of Nulls. A distributed database system is designed, that is "Hotel reservation control system, based on different data sources at four site, each site is represented as a Hotel, for more heterogeneity different application programming languages there are five practical approaches, designed with their rules and algorithms for Null values treatment through the distributed database sites. (1), (2), (3). 14). 15), (9).

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