• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.594-598
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• 2008

In this paper we propose a fast booting technique based on Improved snapshot boot in embedded Linux, widely adopted in personal devices such as PDA and mobile phones. The existing Snapshot boot technique tries to create a snapshot image at the time of suspend, and later load the entire snapshot image into the system memory at the predefined location with the help of a bootloader at the time of resume. Since a bootloader has to copy the entire snapshot image into the predefined memory to resume the previous suspended computing state, a little bit long time is required to resume. Improved snapshot boot does not create a snapshot image consisting of whole memory pages at the time of suspend, thus resulting in smaller snapshot image than the existing snapshot boot. The remaining pages are in the swap area. The resulting smaller sized snapshot image enables much faster booting latency. Through the experiment, we can see the booting latency is reduced almost 30% with suspend image of 2982 pages. This result depends on the amount of swap-out pages.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3B
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• pp.254-259
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• 2011

This paper attempts to propose a method to improve the snapshot boot method, one of the methods to enhance the booting speed of the embedded Linux based system and to increase its efficiency. Snapshot boot is a method of using suspend/resume that is a method of saving and restoring the entire information of the current tasks, and it enhances the booting speed by processing a restoration of previous tasks from the bootloader instead of processing the Linux booting. The facing problem of snapshot boot is that it takes a long time to create images and save them to the storage device during the suspend process since it targets every pages. Additionally, if the switch is turned off while creating an image by some extraordinary circumstances, then the image is not created and thus, the resume process of snapshot boot cannot be executed. The suggest method in this paper creates the snapshot image for once only and utilize the image to enhance the speed and stability on booting.

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.3
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• pp.194-201
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• 2007

As the performance of the mobile terminal becomes higher, the power consumption gradually increases. As a result, power management is one of the most important issues in mobile system with battery. In this paper, we describe an DPM(Dynamic Power Management) using DVS(Dynamic Power Management) as a power management mechanism in Qplus operating system. DVS generally considers a specific device such as CPU, whereas we consider the relations with other hardware components as well as each component. We specially focus on the relation between CPU, memory and LCD devices. We also designs a kernel monitor to collect information to decide the policy for power management. According to the experimental results, the proposed method enables to save much power.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.66-71
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• 2019

In digital pathology, an electronic system in the biomedical domain storage of the files is a big constrain and because all the analysis and annotation takes place at every user-end manually, it becomes even harder to manage the data that is being shared inside an enterprise. Therefore, we need such a storage system which is not only big enough to store all the data but also manage it and making communication of that data much easier without losing its true from. A virtual server setup is one of those techniques which can solve this issue. We set a main server which is the main storage for all the virtual machines(that are being used at user-end) and that main server is controlled through a hypervisor so that if we want to make changes in storage overall or the main server in itself, it could be reached remotely from anywhere by just using the server's IP address. The server in our case includes XML-RPC based API which are transmitted between computers using HTTP protocol. JAVA API connects to HTTP/HTTPS protocol through JAVA Runtime Environment and exists on top of other SDK web services for the productivity boost of the running application. To manage the server easily, we use Tkinter library to develop the GUI and pmw magawidgets library which is also utilized through Tkinter. For managing, monitoring and performing operations on virtual machines, we use Python binding to XML-RPC based API. After all these settings, we approach to make the system user friendly by making GUI of the main server. Using that GUI, user can perform administrative functions like restart, suspend or resume a virtual machine. They can also logon to the slave host of the pool in case of emergency and if needed, they can also filter virtual machine by the host. Network monitoring can be performed on multiple virtual machines at same time in order to detect any loss of network connectivity.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.25-28
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• 2011

최근 사이언스 컴퓨팅 분야에서 대용량 데이터가 발생하고 있고 컴퓨팅 자원들의 수요도 급증하고 있다. 이로 인해 클라우드 컴퓨팅 기술의 필요성이 중요시되고 있고 전 세계적으로 급속히 발전하고 있다. 천문 연구 분야에서 관측기기의 발전으로 대용량의 천문 데이터가 생산되고 있다. 이를 처리하기 위하여 다양한 클라우드 컴퓨팅 기술을 이용한 데이터 분석 환경이 요구되고 있다. 이러한 환경을 구축하기 위해서는 가상 인프라 자원을 효율적으로 관리할 수 있어야 한다. 현재 가상 인프라 자원을 관리하기 위해 오픈 소스를 개발하는 프로젝트들이 활발히 진행되고 있다. 본 논문에서는 오픈 소스인 Eucalyptus와 OpenNebula의 기능적인 측면을 크게 10가지로 분류하여 장단점을 비교 분석하였고 OpenNebula의 세 가지 특징인 중앙 집중화된 구조, live migration과 suspend/resume 기능, 커스터마이징 기능이 대용량 천문 응용 수행을 위한 환경을 구축하는데 반드시 필요하기 때문에 OpenNebula를 채택하였다. OpenNebula를 사용해 구축한 사이언스 클라우드 테스트베드는 NFS 서버의 별도 구성을 통한 성능 개선, 하이브리드 클라우드 컴퓨팅 환경 구축, B클래스 사설 네트워크 구성, GUI 기반 사이언스 클라우드 테스트베드 관리 및 모니터링 기능의 4가지 특징을 가지고 있다. 앞으로도 천문 연구자들에게 안정적인 서비스를 제공하기 위하여 관련 연구를 계속할 것이다.

• Journal of KIISE
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• v.42 no.3
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• pp.281-288
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• 2015

A volcano disaster damage prediction system supports decision making for counteracting volcanic disasters by simulating meteorological condition and volcanic eruptions. In this system, a program called Fall3D generates predicted results for the diffusion of ash after a volcanic eruption on the basis of meteorological information. The relevant meteorological information is generated by a weather numerical prediction model known as Weather Research & Forecasting (WRF). In order to reduce the entire processing time without modifying these two simulation programs, pipelining can be used by partly executing Fall3D whenever the hourly (partial) results of WRF are generated. To reduce the processing time, successor programs such as Fall3D require that certain features be suspended until the part of the results that is based on prior calculation is generated by a predecessor. Even though Fall3D does not have a suspend or resume feature, pipelining effect can be produced by using the program's restart feature, which resumes simulation from the previous session. In this study, we suggest a workflow that can control the execution type.

• Journal of Intelligence and Information Systems
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• v.14 no.3
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• pp.59-76
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• 2008

In this paper, we propose an agent architecture called L-CAA that is quite effective in real-time dynamic environments. L-CAA is an extension of CAA, the behavior-based agent architecture which was also developed by our research group. In order to improve adaptability to the changing environment, it is extended by adding reinforcement learning capability. To obtain stable performance, however, behavior selection and execution in the L-CAA architecture do not entirely rely on learning. In L-CAA, learning is utilized merely as a complimentary means for behavior selection and execution. Behavior selection mechanism in this architecture consists of two phases. In the first phase, the behaviors are extracted from the behavior library by checking the user-defined applicable conditions and utility of each behavior. If multiple behaviors are extracted in the first phase, the single behavior is selected to execute in the help of reinforcement learning in the second phase. That is, the behavior with the highest expected reward is selected by comparing Q values of individual behaviors updated through reinforcement learning. L-CAA can monitor the maintainable conditions of the executing behavior and stop immediately the behavior when some of the conditions fail due to dynamic change of the environment. Additionally, L-CAA can suspend and then resume the current behavior whenever it encounters a higher utility behavior. In order to analyze effectiveness of the L-CAA architecture, we implement an L-CAA-enabled agent autonomously playing in an Unreal Tournament game that is a well-known dynamic virtual environment, and then conduct several experiments using it.