• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1081-1090
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• 2015

This work proposes a theoretic framework for the performance assessment of an access point in the IP network that accommodates MD (Machine Data) and HD (Human Data). First, we investigate typical resource allocation methods in LTE for MD and HD. After that we carry out a Max-Min analysis about the surplus and deficiency of network resource seen from MD and HD. Finally, we evaluate the performance via numerical experiment.

• Journal of the Korea Society for Simulation
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• v.12 no.3
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• pp.69-81
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• 2003

To manage a cluster of distributed server systems, a number of management aspects should be considered in terms of configuration management, fault management, performance management, and user management. System performance monitoring and reporting take an important role for performance and fault management. In this paper, we present distributed system architecture modeling of a performance monitoring and reporting tool. Modeling architecture of four subsystems are introduced: node agent, data collection, performance management & report, and DB schema. The performance-related information collected from distributed servers are categorized into performance counters, event data for system status changes, service quality, and system configuration data. In order to analyze those performance information, we use a number of ways to evaluate data corelation. By using some results from a real site of a company and from simulation of artificial workload, we show the example of performance collection and analysis. Since our report tool detects system fault or node component failure and analyzes performances through resource usage and service quality, we are able to provide information for server load balancing, in short term view, and the cause of system faults and decision for system scale-out and scale-up, in long term view.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.233-244
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• 2023

Although artificial intelligence and machine learning technologies have been used in various fields, problems with personal information protection have arisen based on centralized data collection and processing. Federated learning has been proposed to solve this problem. Federated learning is a process in which clients who own data in a distributed data environment learn a model using their own data and collectively create an artificial intelligence model by centrally collecting learning results. Unlike the centralized method, Federated learning has the advantage of not having to send the client's data to the central server. In this paper, we quantitatively present the performance improvement when federated learning is applied using the building change detection learning data. As a result, it has been confirmed that the performance when federated learning was applied was about 29% higher on average than the performance when it was not applied. As a future work, we plan to propose a method that can effectively reduce the number of federated learning rounds to improve the convergence time of federated learning.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.142-148
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• 2023

In this paper, we identify performance issues in executing compute kernels from PolyBench, which includes compute kernels that are the core computational units of various data-intensive workloads, such as deep learning and data-intensive applications, on Processing-in-Memory (PIM) devices. Therefore, using our in-house simulator, we measured and compared the various performance metrics of workloads based on traditional out-of-order and in-order processors with Processing-in-Memory-based systems. As a result, the PIM-based system improves performance compared to other computing models due to the short-term data reuse characteristic of computational kernels from PolyBench. However, some kernels perform poorly in PIM-based systems without a multi-layer cache hierarchy due to some kernel's long-term data reuse characteristics. Hence, our evaluation and analysis results suggest that further research should consider dynamic and workload pattern adaptive approaches to overcome performance degradation from computational kernels with long-term data reuse characteristics and hidden data locality.

• Journal of the Korean Solar Energy Society
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• v.29 no.6
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• pp.69-74
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• 2009

Monitoring system is an absolutely-required system for assessing a performance and fatigue load of the wind turbine in an on-shore wind energy experimental research complex. It was implemented for the purpose of monitoring the wind information measured from a meteorological tower at the monitoring house, and of utilizing the measured data(fatigue data and electric analyzing data of wind turbine)for the performance assessment, by using the LabVIEW program. Then, by adding the performance assessment-related data acquired from the wind turbine during the performance assessment and the data recorder for synchronizing the data of meteorological tower, the system(BusDAQ) was implemented. Because it transmitted the data by converting the output 'RS-232' of data logger which measures the wind condition into CAN protocol, the data error rate was minimized. Also, This paper is introduced to make the best use of the developed monitoring system and to explain about construct of the system and detailed data communication of its system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2682-2700
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• 2023

To cope with the risks of climate change and promote the realization of carbon peaking and carbon neutrality, this paper first comprehensively considers the policy background, technical trends and carbon reduction paths of energy conservation and emission reduction in data center server industry. Second, we propose a computing power carbon efficiency of data center server, and constructs the carbon emission per performance of server (CEPS) model. According to the model, this paper selects the mainstream data center servers for testing. The result shows that with the improvement of server performance, the total carbon emissions are rising. However, the speed of performance improvement is faster than that of carbon emission, hence the relative carbon emission per unit computing power shows a continuous decreasing trend. Moreover, there are some differences between different products, and it is calculated that the carbon emission per unit performance is 20-60KG when the service life of the server is five years.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.150-162
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• 2022

This study investigated the impact of the latest developments in big data analytics capabilities (BDAC) on firm performance. The BDAC have the power to innovate existing management practices. Nevertheless, their impact on firm performance has not been fully is not yet fully elucidated. The BDAC relates to the flexibility of infrastructure as well as the skills of management and firm's personnel. Most studies have explored the phenomena from a theoretical perspective or based on factors such as organizational characteristics. However, this study extends the flow of previous research by proposing and testing a model which examines whether organizational exploration, exploitation and market agility mediate the relationship between the BDAC and firm performance. The proposed model was tested using survey data collected from the long-term employees over 10 years in 250 companies. The results analyzed through structural equation modeling show that a strong BDAC can help improve firm performance. An organization's ability to analyze big data affects its exploration and exploitation thereby affecting market agility, and, consequently, firm performance. These results also confirm the powerful mediating role of exploration, exploitation, and market agility in improving insights into big data utilization and improving firm performance.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.401-409
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• 2007

This paper addresses a performance evaluation model for ERP system's implementation using Analytic Network Process (ANP) technique. In this study, the performance variables are identified as the perspectives of cost, business process, systems operation, and change management, respectively. The empirical study also investigated factors that affect the performance variables to find out the causal relationship between them using the ANP approach. The data for the empirical analysis were collected from manufacturing companies that have implemented ERP systems. The research findings indicate the proposed model is powerful in proposing that the indirect relationship between influencing factors and managerial effectiveness, mediated by employee satisfaction, is an important one.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.1-11
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• 2010

Many applications of DSMS(Data Stream Management System) require not only to process real-time stream data efficiently but also to provide high quality services such as data mining and data warehouse combining with DBMS(Database Management System) to users. In this paper we execute the performance benchmark of the combined system of DSMS and DBMS that is developed for high quality services. We use the stream data of network monitoring application system and combine the traditional representative DSMSs and DBMSs in a single system for the performance testing. We develop the total performance benchmark tool implementing JAVA language for the our testing. For our performance testing, we combine DSMS such as STREAM and Coral8 and DBMS such MySQL and Oracle10g respectively.

• KEPCO Journal on Electric Power and Energy
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• v.3 no.1
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• pp.9-16
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• 2017

The performance test is conducted for the purpose of determining the accurate thermal performance of the power generation facility or deriving the factors of thermal efficiency degradation. Compared to the acquisition method of power plant thermal performance test data by compensating cable or transmission cable, performance test using wireless instrument can acquire digital data in order to shorten the period due to installation and demolition of instrument and enhance safety of workers and relatively accurate data can be acquired thereby improving work efficiency. Wireless instruments have already been introduced to the market a long time ago, and some of them are used in industry such as petrochemical industry. However, there is no example which has been conducted for performance test of power generation facilities. In order to apply power generation facilities, a reliable system capable of acquiring performance data smoothly without affecting the control system is required. The wireless measurement system can eliminate the measurement defects and errors such as the damage due to the movement of the connecting cable, the extension due to the extension of the shield wire, the contact failure at the contact point between the measuring sensor and the connecting wire, This method has the advantage of collecting relatively accurate performance test data.