A Dynamic Priority Scheduling Rule with Optimization for Transaction Processing Systems.

1979 ◽  
Author(s):  
Daniel K. Wood
Keyword(s):  
Transaction Processing ◽  
Priority Scheduling ◽  
Dynamic Priority ◽  
Transaction Processing Systems

scholarly journals Graph Computing for Financial Crime and Fraud Detection: Trends, Challenges and Outlook

2020 ◽  
Vol 14 (04) ◽  
pp. 565-589
Author(s):  
Eren Kurshan ◽  
Hongda Shen
Keyword(s):  
Fraud Detection ◽  
Transaction Processing ◽  
Financial Crime ◽  
Numerous Application ◽  
Detection Techniques ◽  
Significant Interest ◽  
Crime Detection ◽  
Digital Payments ◽  
Graph Computing ◽  
Transaction Processing Systems

The rise of digital payments has caused consequential changes in the financial crime landscape. As a result, traditional fraud detection approaches such as rule-based systems have largely become ineffective. Artificial intelligence (AI) and machine learning solutions using graph computing principles have gained significant interest in recent years. Graph-based techniques provide unique solution opportunities for financial crime detection. However, implementing such solutions at industrial-scale in real-time financial transaction processing systems has brought numerous application challenges to light. In this paper, we discuss the implementation difficulties current and next-generation graph solutions face. Furthermore, financial crime and digital payments trends indicate emerging challenges in the continued effectiveness of the detection techniques. We analyze the threat landscape and argue that it provides key insights for developing graph-based solutions.

Mobile Transaction Processing System

2017 ◽  
pp. 64-112
Keyword(s):  
Mobile Computing ◽  
Resource Constraints ◽  
Processing System ◽  
Database Systems ◽  
Transaction Processing ◽  
Distributed Environments ◽  
Mobile Transaction ◽  
Basic Concepts ◽  
Database Transactions ◽  
Transaction Processing Systems

In this chapter, we first revisit the basic concepts of database transactions, and discuss how these concepts are achieved in practical systems. Next, we briefly go through the architecture of transaction processing systems in the centralized and the distributed environments. This chapter we have reviewed the basic concepts of database systems and database transactions, and discussed the architecture of transaction processing systems in distributed environments. We will shift our focus to transactions and transaction processing in mobile environments, which possess some unique characteristics such as the mobility of mobile computing hosts, the limitations of wireless communications and the resource constraints of mobile computing devices.

Security Issues in Distributed Transaction Processing Systems

2008 ◽  
pp. 3572-3576
Author(s):  
R. A. Haraty
Keyword(s):  
Computer Network ◽  
Processing System ◽  
Data Replication ◽  
Transaction Processing ◽  
Substantial Effect ◽  
Security Issues ◽  
Distributed Transaction Processing ◽  
Distributed Transaction ◽  
Research Stage ◽  
Transaction Processing Systems

Transaction-processing systems (TPS) are becoming increasingly more available as commercial products. However, the approaches to the issues associated with using TPS in multilevel secure environments are still in the research stage. In this article, we address the issues of multilevel security in distributed transaction-processing systems. A distributed transaction-processing system (DTPS) is a collection of a finite number of centralized transaction-processing systems connected by a computer network. Each of these transaction-processing systems is controlled by a software layer and can be accessed both remotely and locally. Properties of a DTPS, such as data replication, may have a substantial effect on the security of the system. The security policies and integrity constraints adopted at each site may result in global security having inconsistent states. We address the issues of achieving a multilevel secure DTPS, and discuss the security constraints and data replication.

Design and Application of a Containerized Hybrid Transaction Processing and Data Analysis Framework

2018 ◽  
Vol 10 (3) ◽  
pp. 76-90
Author(s):  
Ye Tao ◽  
Xiaodong Wang ◽  
Xiaowei Xu
Keyword(s):  
Data Analysis ◽  
Data Processing ◽  
User Interfaces ◽  
Relational Databases ◽  
Transaction Processing ◽  
Data Sets ◽  
Healthcare Data ◽  
Development Framework ◽  
Hybrid Development ◽  
Transaction Processing Systems

This article describes how rapidly growing data volumes require systems that have the ability to handle massive heterogeneous unstructured data sets. However, most existing mature transaction processing systems are built upon relational databases with structured data. In this article, the authors design a hybrid development framework, to offer greater scalability and flexibility of data analysis and reporting, while keeping maximum compatibility and links to the legacy platforms on which transaction business logics run. Data, service and user interfaces are implemented as a toolset stack, for developing applications with functionalities of information retrieval, data processing, analyzing and visualizing. A use case of healthcare data integration is presented as an example, where information is collected and aggregated from diverse sources. The workflow and simulation of data processing and visualization are also discussed, to validate the effectiveness of the proposed framework.

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