scholarly journals GLOBAL CONVERGENCE IN PARTIALLY FULLY CONNECTED NETWORKS (PFCN) WITH LIMITED RELAYS

2003 ◽  
Vol 02 (02) ◽  
pp. 265-285 ◽  
Author(s):  
AZAD AZADMANESH ◽  
AXEL W. KRINGS ◽  
BAHADOR GHAHRAMANI
Keyword(s):  
Distributed System ◽  
Failure Modes ◽  
Database Systems ◽  
Distributed Database ◽  
Malicious Behavior ◽  
Commit Protocols ◽  
Fully Connected ◽  
Fully Connected Networks ◽  
Selection Of ◽  
Distributed Agreement

In a distributed system, it is often necessary for nodes to agree on a particular event or to coordinate their activities. Applications of distributed agreement are many, such as Commit Protocols in distributed database systems, selection of a monitor node in a distributed system, detecting an intruder, or agreeing on the malicious behavior of a node. Among many forms of Distributed Agreement, one form is called Approximate Agreement (AA), in which the nodes, by exchanging their local values with other nodes, need to agree on values which are approximately equal to each other. Research on AA for fully connected networks is relatively mature. In contrast, the study of AA in partially connected networks has been very limited. More specifically, no general solution to the AA problem exists for such networks. This research solves the AA problem for a specific, scalable, partially connected network with limited relays. The research considers the worst failure mode of nodes, called Byzantine, and hybrid failure modes. The results show low communication cost in comparison to fully connected networks. The network is designed to take advantage of the results available for fully connected networks. Thus, the analysis for obtaining the expressions for Convergence Rate and Fault Tolerance becomes relatively easy.

An Agent-Based Approach to Inference Prevention in Distributed Database Systems

2003 ◽  
Vol 12 (03) ◽  
pp. 297-313 ◽  
Author(s):  
James Tracy ◽  
Liwu Chang ◽  
Ira S. Moskowitz
Keyword(s):  
Distributed System ◽  
Database Systems ◽  
Distributed Database ◽  
Sensitive Data ◽  
Agent Based ◽  
Distributed Database Systems

We propose an inference prevention agent as a tool that enables each of the databases in a distributed system to keep track of probabilistic dependencies with other databases and then use that information to help preserve the confidentiality of sensitive data. This is accomplished with minimal sacrifice of the performance and survivability gains that are associated with distributed database systems.

AI-Assisted Dynamic Modeling for Data Management in a Distributed System

2021 ◽  
Author(s):  
Yihao Tian
Keyword(s):  
Data Management ◽  
Dynamic Modeling ◽  
Distributed System ◽  
Distributed Processing ◽  
Database Systems ◽  
Distributed Database ◽  
Initial Stage ◽  
Complex Decision Making ◽  
Distributed Database Design ◽  
Efficient Information

Data management is an administrative mechanism that involves the acquisitions, validations, storage, protection, and processing of data needed by its users to ensure that data are accessible, reliable, and timely. It is a challenging task to manage protections for information properties. With the emphasis on distributed systems and Internet-accessible systems, the need for efficient information security management is increasingly important. In the paper, artificial intelligence-assisted dynamic modeling (AI-DM) is used for data management in a distributed system. Distributed processing is an effective way to enhance the efficiency of database systems. Therefore, each distributed database structure’s functionality depends significantly on its proper architecture in implementing fragmentation, allocation, and replication processes. The proposed model is a dynamically distributed internet database architecture. This suggested model enables complex decision-making on fragmentation, distribution, and duplication. It provides users with links from anywhere to the distributed database. AI-DM has an improved allocation and replication strategy where no query performance information is accessible at the initial stage of the distributed database design. AI-DM findings show that the proposed database model leads to the reliability and efficiency of the enhanced system. The final results are obtained by analyzing the dynamic modeling ratio is 87.6%, increasing decision support ratio is 88.7%, the logistic regression ratio is 84.5%, the data reliability ratio is 82.2%, and the system ratio is 93.8%.

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.

Selection of the Rational Variant for Construction of a Specialized Distributed Database in a Fuzzy Multicriterion Environment

2006 ◽  
Vol 65 (3) ◽  
pp. 261-269
Author(s):  
A. A. Burushkin ◽  
V. G. Gerasimenko ◽  
S. A. Golovin ◽  
S. V. Zhilinskii
Keyword(s):  
Distributed Database ◽  
Selection Of

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.

scholarly journals Benchmarking scalability and elasticity of distributed database systems

2014 ◽  
Vol 7 (12) ◽  
pp. 1219-1230 ◽  
Author(s):  
Jörn Kuhlenkamp ◽  
Markus Klems ◽  
Oliver Röss
Keyword(s):  
Database Systems ◽  
Distributed Database ◽  
Distributed Database Systems
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