Performance comparison of concurrency control protocols for transaction processing systems with regional locality

Author(s):  
B. Ciciani ◽  
D.M. Dias ◽  
P.S. Yu
2020 ◽  
Vol 14 (04) ◽  
pp. 565-589
Author(s):  
Eren Kurshan ◽  
Hongda Shen

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.


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.


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