• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.533-544
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• 2004

Reports have a significant meaning in time-constrained large transaction environments, such as airplane control systems or wargame simulations. This is due to the necessity of generating reports within a given time limit without restraining the operation performance of large transaction environments. In order to generate reports in large transaction environments while satisfying time-constrained requirements, this paper proposes a model which combines the incremental operation mechanism and materialized view mechanism using triggers and stored procedures. Further, the implementation and evaluation of the proposed model provides the Identification of the characteristics of the proposed model.

• 한국컴퓨터산업교육학회:학술대회논문집
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• 2003.11a
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• pp.33-38
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• 2003

Reports have a significant meaning in time-constrained large transaction environments, such as airplane control systems or wargame simulations. This is due to the necessity of generating reports within a limited scope of time without restraining the operation performance of large transaction environments. In order to generate reports in large transaction environments while satisfying time - constrained requirements, this paper propose a model which combines the incremental operation mechanism and materialized view mechanism using triggers and stored procedures. Further, the implementation and evaluation of the preposed model provides analysis for model characteristics.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.973-986
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• 2004

Reports have a significant meaning In large transaction environments, such as advanced the information technology and online environment. This is due to the necessity of generating reports within a giventime limit without restraining the operation performance of large transaction environments. In order to generate reports in large transaction environments while sa!isfying time-constrained requirements, this paper proposes a model which combines the incremental operation mechanism and materialized view mechanism using triggers and stored procedures. Further, the implementation and evaluation of the proposed model provides the identification of the characteristics of the proposed model.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.499-502
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• 1999

This paper presents a PCI (Peripheral Component Interconnect) controller embedded in a multimedia processor, called FLOVA (FLOating point VLIW Architecture), targeting for 3D graphics applications. Fast I/O interfaces are essential for multimedia processors which usually handle large amount of multimedia data. Therefore, in FLOVA, PCI bus is adopted for I/O interface due to fast burst transaction. However, there are several problems in implementation and verification to use burst transaction of PCI. It is difficult to handle data transaction between two units which have two different operating frequency. FLOVA has more higher operating frequency about 100MHz than that of PCI local bus and it makes lower utilization of FLOVA bus. Also, traditional simulation is not sufficient for verification of PCI functionality. In this paper, we propose buffering schemes to implement the PCI controller with wide bandwidth and high bus utilization. Also, this paper shows how to verify the PCI controller using real PCI bus environments before its fabrication.

• The KIPS Transactions:PartD
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• v.11D no.2
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• pp.339-350
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• 2004

A broadcast method in mobile computing environments which have very large client populations solves the problem of low bandwidth. But most of previous proposed concurrency control protocols are restricted to read-only transactions from mobile client. In this paper, we propose the UTSM-ARM method which uses caching and broadcast method, and allows update transactions in mobile client. The UTSM-ARM decides the validation of cache data consistency with the dynamic update pattern ratio of accessed cached data. Also, the timestamps of accessed cached data and transaction in mobile client guarantee the serializable execution of mobile transactions. As a result, UTSM-ARM makes efficiently use of the asymmetric bandwidth of broadcast environment and can Increase the transaction throughput.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.153-169
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• 2018

Previous e-financial anomalies analysis and detection technology collects large amounts of electronic financial transaction logs generated from electronic financial business systems into big-data-based storage space. And it detects abnormal transactions in real time using detection rules that analyze transaction pattern profiling of existing customers and various accident transactions. However, deep analysis such as attempts to access e-finance by insiders of financial institutions with large scale of damages and social ripple effects and stealing important information from e-financial users through bypass of internal control environments is not conducted. This paper analyzes the management status of e-financial security programs of financial companies and draws the possibility that they are allies in security control of insiders who exploit vulnerability in management. In order to efficiently respond to this problem, it will present a comprehensive e-financial security management environment linked to insider threat monitoring as well as the existing e-financial transaction detection system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5B
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• pp.317-323
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• 2005

Broadcast disks are suited for disseminating information to a large number of clients in mobile computing environments. In broadcast disks, the server continuously and repeatedly broadcasts all data items in the database to clients without specific requests. The clients monitor the broadcast channel and retrieve data items as they arrive on the broadcast channel. The broadcast channel then becomes a disk from which clients can retrieve data items. This paper proposes a Timestamp based Concurrency Control (TCC) scheme to preserve the consistency of read-only client transactions, when the values of broadcast data items are updated at the server. Previous schemes tried to reduce transaction aborts by consuming considerable amount of downlink communication from the server to clients for transferring control information. On the other hand, the TCC uses a timestamp field of each data item to describe execution order of server transactions. Clients can allow more transaction executions by checking consistency of their read-only transactions with timestamps of data items. As a result, the TCC can reduce the abort ratio of client transactions with minimal control information to be broadcast from the server.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.69-85
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• 2006

Broadcast has been often used to disseminate the frequently requested data efficiently to a large volume of mobile clients over a single or multiple channels. Conventional concurrency control protocols for mobile transactions are not suitable for the wireless broadcast environments due to the limited bandwidth of the up-link communication channel. In wireless broadcast environments, the server often broadcast different data items with different frequency to incorporate the data access patterns of mobile transactions. The previously proposed concurrency control protocols for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. However, these protocols perform poorly when the data access pattern of update mobile transaction are not uniform but skewed. The update mobile transactions with skewed data access patterns will be frequently aborted and restarted due 4o the update conflict of the same data items with a high access frequency. In this paper, we propose an energy-efficient concurrence control protocol for mobile transactions with skewed data access as well as uniform data access patterns. Our protocol use a random back-off technique to avoid the frequent abort and restart of update mobile transactions. We present in-depth experimental analysis of our method by comparing it with existing concurrency control protocols. Our performance analysis show that it significantly decrease the average response time, the amount of upstream and downstream bandwidth usage over existing protocols.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1095-1101
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• 2012

As the amount of data increases explosively, a large scale database system is emerged to store, retrieve and manipulate it. There are several issues in this environments such as, consistency, availability and fault tolerance. In this paper, we address a efficient range-query method where data management services are separated from transaction management services in large-scale database systems. A study had been proposed using partitions to protect independence of two modules and to resolve the phantom problem, but this method was efficient only when range-query is specified by a key. So, we present a new method that can improve the efficiency when range-query is specified by a key attribute as well as other attributes. The presented method can guarantee the independence of separated modules and alleviate overheads for range-query using partial index.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.