• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.84-90
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• 2010

DBMS is used for a range of applications from data warehousing through on-line transaction processing. As a result of this demand, DBMS has continued to grow in terms of its size. This growth invokes the most important issue of manually tuning the performance of DBMS. The DBMS tuning should be adaptive to the type of the workload put upon it. But, identifying workloads in mixed database applications might be quite difficult. Therefore, a method is necessary for identifying workloads in the mixed database environment. In this paper, we propose a SVM workload classifier to automatically identify a DBMS workload. Database workloads are collected in TPC-C and TPC-W benchmark while changing the resource parameters. Parameters for SVM workload classifier, C and kernel parameter, were chosen experimentally. The experiments revealed that the accuracy of the proposed SVM workload classifier is about 9% higher than that of Decision tree, Naive Bayes, Multilayer perceptron and K-NN classifier.

• IE interfaces
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• v.9 no.3
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• pp.257-268
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• 1996

This paper illustrates the process of developing and configuring the prototype Computer Analysis System for Controlling Occupational WORKload (CAS-COWORK). The software interface between the database and expert system was attempted. The database is used for storing and retrieving series of data entered by general users and the expert system is used for identifying and solving occupational problem areas. Two theories were applied in developing the algorithm base of CAS-COWORK that were used to calculate overall workload stress level. The fuzzy set theory was introduced to capture the subject‘s workload stress perception. The Analytic Hierarchy Process (AHP) was introduced to estimate the importance of the task and workplace variables. The purpose of the system development is for future prediction and problem solving which would be highly valuable to the industrial engineer.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1427-1434
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• 2004

Database system benchmarks, which are usually evaluated to use the maximized resource in order to get the best results, arc not likely to simulate the real environment. We propose a workload generator that helps benchmarks be executed in the environment similar to a real world. The workload generator can create memory-bound, CPU-bound, and I/O-bound workloads. The workload generator allows users to create an integrated workload. which is similar to a real workload users run across in practice. Finally, we conducted the experiments that the Wisconsin benchmark was performed with the TPC-C and with the workload generation tool, and showed the feasibility of the proposed workload gen-eration tool comparing with two experimental results.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.5
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• pp.97-104
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• 2010

In this paper, mesh network structure is applied to solve the load balancing problems in the Grid database. Data of the Grid database is replicated to several node for enhanced performance. Therefore, load balancing for user's query is selected node that evaluated workload in it. Existing researches are using passive load balancing method that selected another node after then node overflowed workload. It is inefficient to be applied to Gird database that has a number of node and user's queries almost changes dynamically. The proposed method connected each node which includes the same data through mesh network structure. When user's query occurs, it select node that has the lowest workload. The performance evaluation shows that proposed method performs better than the existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1693-1713
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• 2018

An important technique used by database administrators (DBAs) is to improve performance in decision-support workloads associated with a Star schema is multi-level partitioning. Queries will then benefit from performance improvements via partition elimination, due to constraints on queries expressed on the dimension tables. As the task of multi-level partitioning can be overwhelming for a DBA we are proposing a wizard that facilitates the task by calculating a partitioning scheme for a particular workload. The system resides completely on a client and interacts with the costing estimation subsystem of the query optimizer via an API over the network, thereby eliminating any need to make changes to the optimizer. In addition, since only cost estimates are needed the wizard overhead is very low. By using a greedy algorithm for search space enumeration over the query predicates in the workload the wizard is efficient with worst-case polynomial complexity. The technology proposed can be applied to any clustering or partitioning scheme in any database management system that provides an interface to the query optimizer. Applied to the Teradata database the technology provides recommendations that outperform a human expert's solution as measured by the total execution time of the workload. We also demonstrate the scalability of our approach when the fact table (and workload) size increases.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.271-282
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• 2008

Database administrators are demanded to acquire much knowledges and take great efforts for keeping consistent performance in system. Various principles, methods, and tools have been proposed in many studies and commercial products in order to alleviate such burdens on database administrators, and it has resulted to the automation of DBMS which reduces the intervention of database administrator. This paper suggests a resource selection method that estimates the status of the database system based on the workload characteristics and that recommends tuneable resources. Our method tries to simplify selection information on DBMS status using data-mining techniques, enhance the accuracy of the selection model, and recommend tuneable resource. For evaluating the performance of our method, instances are collected in TPC-C and TPC-W workloads, and accuracy are calculated using 10 cross validation method, comparisons are made between our scheme and the method which uses only the classification procedure without any simplification of informations. It is shown that our method has over 90% accuracy and can perform tuneable resource selection.

• Journal of Information Technology Applications and Management
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• v.9 no.1
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• pp.27-44
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• 2002

Performance evaluations of database algorithms are usually conducted on a set of queries for a given test database. For more detailed evaluation results, it is often necessary to use different query workloads several times. Each query workload should reflect the querying patterns of the application domain in real world, which are non-uniform in the usage frequencies of attributes in queries of the workload for a given database. It is not trivial to generate many different query workloads manually, while considering non-uniform distributions of attributes'usage frequencies. In this paper we propose a technique to generate non-uniform distributions, which will help construct query workloads more efficiently. The proposed algorithm generates a query-attribute usage distribution based on given constraints on usage frequencies of attributes and qreries. The algorithm first allocates as many attributes to queries as Possible. Then it corrects the distribution by considering attributes and queries which are not within the given frequency constraints. We have implemented and tested the performance of the proposed algorithm, and found that the algorithm works well for various input constraints. The result of this work could be extended to help automatically generate SQL queries for various database performance benchmarking.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3533-3549
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• 2019

A big database utilizes the establishing network technology, and it became an emerging trend in the computing field. Therefore, there is a necessity for an optimal and effective data distribution approach to deal with this trend. This research presents the practical perspective of designing and implementing distributed database features. The proposed system has been establishing the satisfying, reliable, scalable, and standardized use of information. Furthermore, the proposed scheme reduces the vast and recurring efforts for designing an individual system for each university, as well as it is effectively participating in solving the course equivalence problem. The empirical finding in this study shows the superiority of the distributed system performance based on the average response time and the average waiting time than the centralized system. The system throughput also overcomes the centralized system because of data distribution and replication. Therefore, the analyzed data shows that the centralized system thrashes when the workload exceeds 60%, while the distributed system becomes thrashes after 81% workload.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.47-55
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• 1996

This study developed a comprehensive and easily applicable nuclear reactor control system evaluation method using reactor operators behavioral and mental workload database. A proposed control panel design cycle consists of the 5 steps: (1) finding out inconvenient, erroneous, and mentally stressful factors for the proposed design through evaluative experiments, (2) drafting improved design alternatives considering detective factors found out in the step (1), (3) comparative experiements for the design alternatives, (4) selecting a best design alternative, (5) returning to the step (1) and repeating the design cycle. Reactor operators behavioral and mental workload database collected from evaluative experiments in the step (1) and comparative experiments in the step (3) of the design cycle have a key roll in finding out defective factors and yielding the criteria for selection of the proposed reactor control systems. The behavioral database was designed to include the major informations about reactor operators' control behaviors: beginning time of operations, involved displays, classification of observational behaviors, dehaviors, decisions, involved control devices, classification of control behaviors, communications, emotional status, opinions for man-machine interface, and system event log. The database for mental workload scored from various physiological variables-EEG, EOG, ECG, and respir- ation pattern-was developed to indicate the most stressful situation during reactor control operations and to give hints for defective design factors. An experimental test for the evaluation method applied to the Compact Nuclear Simulator (CNS) installed in Korea Atomic Energy Research Institute (KAERI) suggested that some defective design factors of analog indicators should be improved and that automatization of power control to a target level would give relaxation to the subject operators in stressful situation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.64
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• pp.1-20
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• 2001

In distributed databases, file replication and workload allocation are important design issues. This paper solves these two issues simultaneously, The primary objective is to minimize the system response time that consists of local processing and communication overhead on a local area network. Workload (query transactions) is assigned among any sites in proportion to the remaining file request service rate of the each server The problem is presented in the form of a nonlinear integer programming model. The problem is proved to be NP-complete and thus an efficient heuristic is developed by employing its special structure. To illustrate its effectiveness, it is shown that the proposed heuristic is based on the heuristic of a non-redundant allocation that was provided to be effective. The model and heuristics are likely to provide more effective distributed database designs.