scholarly journals Advanced consistency management of highly-distributed transactional database in a hybrid cloud environment using novel R-TBC/RTA approach

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jasmina Dizdarevic ◽  
Zikrija Avdagic ◽  
Fahrudin Orucevic ◽  
Samir Omanovic
Keyword(s):  
Distributed Database ◽  
Database Management System ◽  
Multidimensional Data ◽  
Hybrid Cloud ◽  
Cloud Environment ◽  
Bayesian Hierarchical ◽  
Consistency Management ◽  
Model Research ◽  
Sufficient Degree ◽  
Novel Strategy

AbstractThis paper examines possibilities for improving the existing strategies of consistency management for highly-distributed transactional database in a hybrid cloud environment. With a detailed analysis of the existing consistency models for distributed database and standard strategies including Classic, Quorum and Tree Based Consistency (TBC), it is concluded that an improved advanced model of so-called visible adaptive consistency needs to be applied in a highly-distributed cloud environment, as necessary and sufficient degree of synchronization of all replicas. Along with the proposed model, research and development of an advanced novel strategy for consistency management Rose TBC (R-TBC) approach has been conducted, by improving standard TBC approach. Regarding implementation, a specific agglomerative Rose Tree Algorithm (RTA) has been developed, based on Bayesian hierarchical clustering and Graph Partitioning Algorithm - Multidimensional Data Clustering (GPA-MDC) intelligent partitioning of transactional Cloud Database Management System (CDBMS). The final result is constructed R-TBC model that changes in accordance with dynamic changes of entire heterogeneous CDBMS environment.

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 How to Achieve Compliance with GDPR Article 17 in a Hybrid Cloud Environment

Sci ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 22
Author(s):  
Miriam Kelly ◽  
Eoghan Furey ◽  
Kevin Curran
Keyword(s):  
Ad Hoc ◽  
Data Repository ◽  
Hybrid Cloud ◽  
Cloud Environment ◽  
Cloud Infrastructure ◽  
General Data Protection Regulation ◽  
Right To Be Forgotten ◽  
Personally Identifiable Information ◽  
General Data ◽  
The Right

On 25 May 2018, the General Data Protection Regulation (GDPR)Article 17, the Right to Erasure (‘Right to be Forgotten’) came into force making it vital for organisations to identify, locate and delete all Personally Identifiable Information (PII) where a valid request is received from a data subject to erase their PII and the contractual period has expired. This must be done without undue delay and the organisation must be able to demonstrate reasonable measures were taken. Failure to comply may incur significant fines, not to mention impact to reputation. Many organisations do not understand their data, and the complexity of a hybrid cloud infrastructure means they do not have the resources to undertake this task. The variety of available tools are quite often unsuitable as they involve restructuring so there is one centralised data repository. This research aims to demonstrate compliance with GDPR’s Article 17 Right to Erasure (‘Right to be Forgotten’) is achievable in a Hybrid cloud environment by following a list of recommendations. However, 100% retrieval, 100% of time will not be possible, but we show that small organisations running an ad-hoc Hybrid cloud environment can demonstrate that reasonable measures were taken to be Right to Erasure (‘Right to be Forgotten’) compliant.

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