• The KIPS Transactions:PartC
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• 제10C권7호
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• pp.879-884
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• 2003

Generally we use web cache in order to increase performance of web base system, and a replacement technique has a great influence on performance of web cache. A web cache replacement technique is different from a replacement technique of memory scope, and a unit substituted for is web object Also, as for the web object, a variation of user reference characteristics is very great. Therefore, a web cache replacement technique can reflect enough characteristics of this web object. But the existing web caching techniques were not able to reflect enough these object reference characteristics. A principal viewpoint of this study is reference characteristic analysis, an elevation of an object hit rate, an improvement of response time. First of all we analyzed a reference characteristics of an web object by log analysis. And we divide web cache storage scope using the result of reference characteristics analysis. In the experiment result, we can confirm that performance of an object-hit ratio and a response speed was improved than a conventional technique about a proposal technique.

• Journal of the Korea Computer Graphics Society
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• 제30권1호
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• pp.1-10
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• 2024

In immersive virtual environments including mixed reality (MR) and virtual reality (VR), avatars or agents, which are virtual humans, are being studied and applied in various ways as factors that increase users' social presence. Recently, studies are being conducted to apply generative AI as an agent to improve user learning effects or suggest a collaborative environment in an immersive virtual environment. This study proposes a novel method for interface application of a virtual assistant agent (VAA) using OpenAI's ChatGPT in an immersive virtual environment including VR and MR. The proposed method consists of an information agent that responds to user queries and a control agent that controls virtual objects and environments according to user needs. We set up a development environment that integrates the Unity 3D engine, OpenAI, and packages and development tools for user participation in MR and VR. Additionally, we set up a workflow that leads from voice input to the creation of a question query to an answer query, or a control request query to a control script. Based on this, MR and VR experience environments were produced, and experiments to confirm the performance of VAA were divided into response time of information agent and accuracy of control agent. It was confirmed that the interface application of the proposed VAA can increase efficiency in simple and repetitive tasks along with user-friendly features. We present a novel direction for the interface application of an immersive virtual environment through the proposed VAA and clarify the discovered problems and limitations so far.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제18권10호
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• pp.117-124
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• 2017

A Smart Grid is a system that can efficiently use energy by exchanging real-time information in both directions between a consumer and a power supplier using ICT technology on an existing power network. DR(Demand response) is an arrangement in which electricity users can sell the electricity they save to the electricity market when the price of electricity is high or the power system is crisis. In this study, we developed a power meter data transmission device and power IT system that measure the demand information in real-time using a smart meter and transmit it to a cloud server. The power meter data transmission device developed in this study uses alight sensor connected to a Raspberry Pi 3 to measure the number of blinking lamps on the KEPCO meter per unit of power, in order to provide reliable data without any measurement errors with respect to the KEPCO power data. The power measurement data transmission device uses the standard communication protocol, OpenADR 2.0b. The measured data is transmitted to the power IT system, which consists of the VEN, VTN, and calculation program, via the LTE WiFi communication network and stored in its MySQL DB. The developed power measurement data transmission device issues a power supply instruction and performs a peak reduction DR when a power system crisis occurs. The developed power meter data transmission device has the advantage of allowing the user to adjust it every 1 minute, where as the existing smart metering time is fixed at once every 15 minutes.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제25권6호
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• pp.766-773
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• 2021

This paper presents an implementation result and performance evaluation of pavilion management services that does not only provide real-time status of the pavilion in the forest but also prediction services through machine learning. The developed hardware prototype detects whether the pavilion is occupied using a motion detection sensor and then sends it to a cloud database along with location information, date and time, temperature, and humidity data. The real-time usage status of the collected data is provided to the user's mobile application. The performance evaluation confirms that the average response time from the hardware module to the applications was 1.9 seconds. The accuracy was 99%. In addition, we implemented a pavilion availability prediction service that applied a machine learning-based SVM (Support Vector Model) model to collected data and provided it through mobile and web applications.

• Journal of KIISE:Computer Systems and Theory
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• 제35권11호
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• pp.497-508
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• 2008

Mobile Multimedia File System, MNFS, is a file system which extensively exploits NAND FLASH Memory, Since general Flash file systems does not precisely meet the criteria of mobile devices such as MP3 Player, PMP, Digital Camcorder, MNFS is designed to guarantee the optimal performance of FLASH Memory file system. Among many features MNFS provides, there are three distinguishable characteristics. MNFS guarantees, first, constant response time in sequential write requests of the file system, second, fast file system mounting time, and lastly least memory footprint. MNFS implements four schemes to provide such features, Hybrid mapping scheme to map file system metadata and user data, manipulation of user data allocation to fit allocation unit of file data into allocation unit of NAND FLASH Memory, iBAT (in core only Block Allocation Table) to minimize the metadata, and bottom-up representation of directory. Prototype implementation of MNFS was tested and measured its performance on ARM9 processor and 1Gbit NAND FLASH Memory environment. Its performance was compared with YAFFS, NAND FLASH File system, and FAT file system which use FTL. This enables to observe constant request time for sequential write request. It shows 30 times faster mounting time to YAFFS, and reduces 95% of HEAP memory consumption compared to YAFFS.

• The Journal of Bigdata
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• 제8권1호
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• pp.23-34
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• 2023

Nowadays, the Designated Driver Services employ dynamic pricing, which adapts in real-time based on nearby driver availability, service user volume, and current weather conditions during the user's request. The uncertain volatility is the main cause of price increases, leading to customer attrition and service refusal from driver. To make a good Designated Driver Services, development of a demand forecasting model is required. In this study, we propose developing a demand forecasting model using data from the Designated Driver Service by considering normal and peak periods, such as rush hour and rush day, as prior knowledge to enhance the model performance. We propose a new methodology called Time-Series with Conditional Probability(TSCP), which combines conditional probability and time-series models to enhance performance. Extensive experiments have been conducted with real Designated Driver Service data, and the result demonstrated that our method outperforms the existing time-series models such as SARIMA, Prophet. Therefore, our study can be considered for decision-making to facilitate proactive response in Designated Driver Services.

• KIPS Transactions on Computer and Communication Systems
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• 제4권11호
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.137-142
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• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

• Journal of Korean Society of Industrial and Systems Engineering
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• 제43권4호
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• pp.133-141
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• 2020

Up to date cosmetic OEM/ODM (original equipment manufacturing/original development manufacturing) industry receives attention as a future growth engine due to steady growth. However, because of limited research and development capability, many companies have employed commercial management platforms specialized for large-sized companies; thus, overall system effectiveness and efficiency is low. Especially, MRP (material requirement planning) system introduced originally in 1970s is employed to calculate the requirement of the parts. However, dynamic nature of production lead time usually results in incorrect requirements. In addition, its algorithm does not consider the capability of the production resources. Also, because the commercial MRP system calculates all subcomponent for fixed period, the more goods have subcomponent, the slower calculation is. Therefore, conventional MRP system cannot respond complicated situation in time. In this study, we will suggest a new method that can respond to complicated situations resulting from short lead time and urgent production order in Korean cosmetic market. In particular, a distributed MRP system is proposed, that consists of multi-functional and operational modules, based on the characteristic of the BOM (bill of material). The distributed MRP system divides components (i.e. products and parts) into several fields and decrease the problem size; thus, we can respond to dynamically changed data any time. Through this solution, we can order components quickly, adjust schedules and planned quantity, and manage stocks reasonably. In addition, a prototype of the distributed MRP system is presented in this paper, in which ERP (enterprise resource planning) sever data is associated with an excel spreadsheet via MSsql. System user interface is implemented by a VBA (visual basic for applications) tool. According to a case study, response rate for delivery and planning achievement rate were enhanced about 20%, and inventory turnover was also decreased. Consequently, the proposed system improves overall profit.

• The KIPS Transactions:PartA
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• 제18A권6호
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• pp.255-264
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• 2011

A sensor network is a special network that makes physical data sensed by sensor nodes and manages the data. The sensor network is a technology that can apply to many parts of field. It is very important to transmit the data to a user at real-time. The core of the sensor network is a sensor node and small operating system that works in the node. TinyOS developed by UC Berkeley is a sensor network operating system that used many parts of field. It is event-driven and component-based operating system. Basically, it uses non-preemptive scheduler. If an urgent task needs to be executed right away while another task is running, the urgent one must wait until another one is finished. Because of that property, it is hard to guarantee real-time requirement in TinyOS. According to recent study, Priority Level Scheduler, which can let one task preempt another task, was proposed in order to have fast response in TinyOS. It has restrictively 5 priorities, so a higher priority task can preempt a lower priority task. Therefore, this paper suggests Preemptive EDF(Earliest Deadline First) Scheduler that guarantees a real-time requirement and reduces average respond time of user tasks in TinyOS.