• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.3
• /
• pp.140-148
• /
• 2009

Recent advances in communication and multimedia technologies make it possible to provide video-on-demand(VOD) services and people can access video servers over the Internet at any time using their electronic devices, such as PDA, mobile phone and digital TV. Each device has different processing capabilities, energy budgets, display sizes and network connectivities. To support such diverse devices, multiple versions of videos are needed to meet users' requests. In general cases, VOD servers cannot store all the versions of videos due to the storage limitation. When a device requests a stored version, the server can send the appropriate version immediately, but when the requested version is not stored, the server first converts some stored version to the requested version, and then sends it to the client. We call this conversion process transcoding. If transcoding occurs frequently in a VOD server, the CPU resource of the server becomes insufficient to response to clients. Thus, to admit as many requests as possible, we need to maximize the CPU availability. In this paper, we propose a new algorithm to select versions from those stored on disk using a branch and bound technique to maximize the CPU availability. We also explore the impact of these storage management policies on streaming to heterogeneous users.

• Proceedings of the Korean Information Science Society Conference
• /
• 2006.10a
• /
• pp.189-192
• /
• 2006

본 논문은 그래픽 가속기를 포함한 모바일 시스템에서 멀티미디어 응용을 위한 통합전력관리 기법을 제안한다. 가속기가 포함된 시스템이 멀티미디어 프로세스를 실행할 때 QoS를 유지하면서 에너지 절약을 하기 위해서는 가속기의 특징을 고려한 DVS 알고리즘이 필요하다. 그러나 기존 DVS 알고리즘은 CPU 위주로 연구된 알고리즘이여서 가속기가 포함된 시스템에 적용하는 것은 문제가 있기 때문에 CPU와 가속기의 특징을 고려한 통합전력관리 DVS 방법이 필요하다. 제안된 DVS 스케줄링은 리눅스 운영체제 상에 구현하였으며 Intel 2700G 그래픽 가속기가 포함된 Xscale 장치에서 실험을 하였다. 따라서 제안된 DVS 기법이 범용적인 프로세스의 QoS를 보장하면서 에너지 소비를 CPU위주로 연구된 알고리즘보다 평균 12.5% 줄일 수 있음을 밝혔다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.11a
• /
• pp.553-555
• /
• 2007

클러스터 시스템은 가격대 성능비의 효율성 때문에 다양한 분야에서 활용되고 있으며, 구축 규모도 급속히 증가하고 있다. 특히, 인터넷을 통한 정보 검색 및 공유가 활발하게 이루어지면서, 정보를 수집, 가공 및 제공하는 대형 포털들의 규모가 급속히 증가하고 있다. 포털들은 대량의 정보를 서비스하기 위해서 대규모의 클러스터 시스템을 운영하고 있으며, 이러한 시스템을 유지 관리하는 것은 커다란 문제점중의 하나이다. 대규모 클러스터 시스템의 운영 비용중에서 전력비용이 상당히 큰 부분을 차지하고 있으며, 이를 감소시키려는 다양한 시도가 진행되고 있다. 본 논문에서는 클러스터 시스템의 전력사용량을 감소시키기 위해서 CPU 의 전력을 효율적으로 관리하는 있는 관리 메커니즘을 제안한다.

• Journal of Computing Science and Engineering
• /
• v.5 no.2
• /
• pp.111-120
• /
• 2011

Data mining algorithms should exploit new hardware technologies to accelerate computations. Such goal is difficult to achieve in database management system (DBMS) due to its complex internal subsystems and because data mining numeric computations of large data sets are difficult to optimize. This paper explores taking advantage of existing multithreaded capabilities of multicore CPUs as well as caching in RAM memory to efficiently compute summaries of a large data set, a fundamental data mining problem. We introduce parallel algorithms working on multiple threads, which overcome the row aggregation processing bottleneck of accessing secondary storage, while maintaining linear time complexity with respect to data set size. Our proposal is based on a combination of table scans and parallel multithreaded processing among multiple cores in the CPU. We introduce several database-style and hardware-level optimizations: caching row blocks of the input table, managing available RAM memory, interleaving I/O and CPU processing, as well as tuning the number of working threads. We experimentally benchmark our algorithms with large data sets on a DBMS running on a computer with a multicore CPU. We show that our algorithms outperform existing DBMS mechanisms in computing aggregations of multidimensional data summaries, especially as dimensionality grows. Furthermore, we show that local memory allocation (RAM block size) does not have a significant impact when the thread management algorithm distributes the workload among a fixed number of threads. Our proposal is unique in the sense that we do not modify or require access to the DBMS source code, but instead, we extend the DBMS with analytic functionality by developing User-Defined Functions.

• Journal of KIISE
• /
• v.42 no.12
• /
• pp.1623-1628
• /
• 2015

As the performance of mobile devices has increased, high-end multicore CPUs have become the norm in smartphones. However, such high performance devices are exposed to the problem of battery depletion due to the energy consumption caused by software performance, and despite increases in battery capacity. The required resources are dynamic and varied, and further user interaction is highly random; thus, Linux-based power management such as DVFS is needed to fulfill requirements. In order to reduce power consumption, we propose a method to restrict the CPU frequency of data download while maintaining user reactivity. This can supplement the weakness of existing Linux-based power management techniques like DVFS in relation to webpage loading. Through the implementation of our method at the application level, we confirm that energy consumption from webpage loading is reduced.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.6
• /
• pp.809-814
• /
• 2011

The major resource problem in sensor networks is energy efficiency. There are two major access methods to efficiently use energy. The first is to use dynamic power management (DPM). The second is to use energy efficient protocols. In DPM methods, the OS, the power manager, is responsible for managing the proper power state of CPU and each I/O with respect to the events, but the OS is not largely concerned about the internal operation of each network protocols. Also, energy efficient protocols are mainly focused on the power saving operation of the radio PHY. In addition, in wireless sensor network most of tasks are connected to communication. In such a situation, traditional power managers can waste unpredicted power. In this paper, we introduce an efficient power manger that can reduce a lot of unwanted power consumption through cooperative power management (CPM) in communication-related tasks between each units, such as radio, sensing unit, and CPU, for ad hoc wireless sensor nodes.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.28B no.5
• /
• pp.404-410
• /
• 1991

In this paper,a network interface unit of token-passing bus network and its driving software are implemented based on Mini-MAP. This network interface unit performs the function of MAC layer which is responsible for transmission and reception of frames as well as the management of logical ring. The driving software performs the management of data buffer and the report of errors, if ocoured, to the higher layer. Motorola MC68824 of is used as a TBC(Token Bus Controller) and Intel80186 as a CPU for network interface unit. The operation of network interface unit is verified by self-test which checks the functioning of TBC and CPU. In addition each module of driving software is tested to check the functions regarding transmission and reception of frames.

• Journal of Computing Science and Engineering
• /
• v.6 no.2
• /
• pp.79-88
• /
• 2012

Power continues to be a driving force in central processing units (CPU) design. Most of the advanced breakthroughs in power have been in a realm that is applicable to workstation CPUs. Advanced power management systems will manage temperature, dynamic voltage scaling and dynamic frequency scaling in a CPU. The use of power management systems for microcontrollers and embedded CPUs has been modest, and mostly focuses on very large scale integration (VLSI) level optimizations compared to system level optimizations. In this paper, a dynamic frequency controlling (DFC) technique is introduced, to lay the foundation of a system level power management system for commercial microcontrollers. The DFC technique allows a commercial microcontroller to have minor modifications on both the hardware and software side, to allow the clock frequency to change to save power; results in this study show a 10% savings. By adding an additional layer of software abstraction at the interrupt level, the microcontroller can operate without having knowledge of the current clock frequency, and this can be accomplished without having to use an embedded operating system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.493-496
• /
• 2007

As the ubiquitous society period has set in recently, which resulted from both mass distribution of portable devices such as PDA, PMP, Smart Phones, the demand for more optional features of system and multimedia functions has been increasing. In compliance with thoses needs, the amount of information increased in a system and greater power capacities are needed more than ever. Therefore, in portable device which uses battery as a limited source of power, the power management has become a key factor in the system. This paper concentrates on the Power management solution for Smart device for the prevention of missing child. And ARM9 Core was used as CPU and Windows CE 5.0 was ported to the smart device.

• Journal of the Korea Computer Graphics Society
• /
• v.22 no.4
• /
• pp.21-30
• /
• 2016

Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.