A performance anomaly in clustered on-line transaction processing systems

2004 ◽  
Vol 27 (12) ◽  
pp. 1166-1173 ◽  
Author(s):  
Hong Cai ◽  
Hisao Kameda ◽  
Jie Li
Keyword(s):  
Transaction Processing ◽  
Performance Anomaly ◽  
On Line ◽  
Transaction Processing Systems ◽  
A Performance

scholarly journals Voting And Lottery Technologies: A Potential Jackpot? An Economic Analysis

2011 ◽  
Vol 1 (5) ◽  
Author(s):  
Maria Cornachione Kula
Keyword(s):  
Cost Effective ◽  
Transaction Processing ◽  
First Century ◽  
Economic Welfare ◽  
Public And Private ◽  
The Public ◽  
Voting System ◽  
On Line ◽  
High Level ◽  
Transaction Processing Systems

Voting irregularities and recount mechanisms used in Florida during the 2000 U.S. Presidential election have brought calls for re-vamped voting technologies and procedures. Many in both the public and private sectors have focused on the Internet as a possible underlying technology that could provide the ease, accuracy, and reliability a twenty-first century voting system should possess. Apart from the difficulties inherent in building an Internet based system from scratch, this solution ignores existing, proven technology, already in use by a majority of states, which could be adapted to provide a cost effective voting system with many desirable characteristics. The technology: computerized, on-line lottery systems. Inherently, these lotteries are transaction processing systems, which is what a voting system, at its base, is. Lottery systems are state based, handle vast quantities of transactions reliably, operate under an extremely high level of scrutiny, and are familiar to millions of Americans. This paper examines a lottery technology based voting system from several perspectives and develops an economic welfare analysis of a lottery technology based voting system.

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.

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