• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.6
• /
• pp.61-67
• /
• 2023

The rise of 5G and the proliferation of smart devices have underscored the significance of multi-access edge computing (MEC). Amidst this trend, interest in effectively processing computation-intensive and latency-sensitive applications has increased. This study investigated a novel task offloading strategy considering the probabilistic MEC environment to address these challenges. Initially, we considered the frequency of dynamic task requests and the unstable conditions of wireless channels to propose a method for minimizing vehicle power consumption and latency. Subsequently, our research delved into a deep reinforcement learning (DRL) based offloading technique, offering a way to achieve equilibrium between local computation and offloading transmission power. We analyzed the power consumption and queuing latency of vehicles using the deep deterministic policy gradient (DDPG) and deep Q-network (DQN) techniques. Finally, we derived and validated the optimal performance enhancement strategy in a vehicle based MEC environment.

• The Journal of the Convergence on Culture Technology
• /
• v.7 no.1
• /
• pp.615-619
• /
• 2021

This study focuses on memory systems that are optimized to increase performance and energy efficiency in many embedded systems such as IoT, cloud computing, and edge computing, and proposes a performance improvement technique. The proposed technique improves memory system performance based on machine learning algorithms that are widely used in many applications. The machine learning technique can be used for various applications through supervised learning, and can be applied to a data classification task used in improving memory system performance. Data classification based on highly accurate machine learning techniques enables data to be appropriately arranged according to data usage patterns, thereby improving overall system performance.

• Journal of KIISE:Computer Systems and Theory
• /
• v.36 no.5
• /
• pp.351-359
• /
• 2009

Recently with increase of data in the Internet, platform technologies that can process huge data effectively such as Google platform and Hadoop are regarded as worthy of notice. In this kind of platform, there exist network I/O overheads to send task outputs due to the MapReduce operation which is a programming model to support parallel computation in the large cluster system. In this paper, we suggest applying of TIPC (Transparent Inter-Process Communication) protocol for reducing network I/O overheads and increasing network performance in the distributed computing environments. TIPC has a lightweight protocol stack and it spends relatively less CPU time than TCP because of its simple connection establishment and logical addressing. In this paper, we analyze main features of the Hadoop-based distributed computing system, and we build an experimental model which can be used for experiments to compare the performance of various protocols. In the experimental result, TIPC has a higher bandwidth and lower CPU overheads than other protocols.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.5B
• /
• pp.899-912
• /
• 2000

PVM provides users with a single image of high performance parallel computing machine by collecting machines distributed over a network. Low communication overhead is essential to effectively run applications on PVM based platforms. In the original PVM, three times of memory copies are required for a PVM task to send a message to a remote task, which results in performance degradation. We propose a zero-copy model using global shared memory that can be accessed by PVM tasks, PVM daemon, and network interface card(NIC). In the scheme, a task packs data into global shared memory, and notify daemon that the data is ready to be sent, then daemon routes the data to a remote task to which it is sent with no virtual data copy overhead. Experimental result reveals that the message round trip time between two machines is reduced significantly in the proposed zero-copy scheme.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.05a
• /
• pp.52-55
• /
• 2022

5G 시대에 스마트 모바일 기기가 기하급수적으로 증가하면서 멀티 액세스 엣지 컴퓨팅(MEC)이 유망한 기술로 부상했다. 낮은 지연시간 안에 계산 집약적인 서비스를 제공하기 위해 MEC 서버로 오프로딩하는 특히, 태스크 도착률과 무선 채널의 상태가 확률적인 MEC 시스템 환경에서의 오프로딩 연구가 주목받고 있다. 본 논문에서는 차량의 전력과 지연시간을 최소화하기 위해 로컬 실행을 위한 연산 자원과 오프로딩을 위한 전송 전력을 할당하는 심층 강화학습 기반의 오프로딩 기법을 제안하였다. Deep Deterministic Policy Gradient (DDPG) 기반 기법과 Deep Q-network (DQN) 기반 기법을 차량의 전력 소비량과 큐잉 지연시간 측면에서 성능을 비교 분석하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.33 no.9
• /
• pp.113-119
• /
• 2005

The methods that are used for receiving data from attached devices under real-time preemptive multi-task operating system (OS) by general processors can be categorized as polling and interrupt driven. The technical approach to these methods may be different due to the application specific scheduling policy of the OS and the programming architecture of the flight software. It is one of the most important requirements on the development of the flight software to process the data received from satellite subsystems or components with the exact timeliness and accuracy. This paper presents the analysis of the I/O method of device related scheduling mechanism and the reliable data I/O methods between processor and devices.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.3
• /
• pp.116-126
• /
• 2015

In a distributed heterogeneous computing system, the performance of a parallel application greatly depends on its task scheduling algorithm. Therefore, in order to improve the performance, it is essential to consider some factors that can have effect on the performance of the parallel application in a given environment. One of the most important factors that affects the total execution time is a critical path. In this paper, we propose the CLTS algorithm for a task scheduling. The CLTS sets the priorities of all nodes to improve overall performance by applying leveling method to improve parallelism of task execution and by reducing the delay caused by waiting for execution of critical nodes in priority phase. After that, it conditionally uses insertion based policy or duplication based policy in processor allocation phase to reduce total schedule time. To evaluate the performance of the CLTS, we compared the CLTS with the DCPD and the HCPFD in our simulation. The results of the simulations show that the CLTS is better than the HCPFD by 7.29% and the DCPD by 8.93%. with respect to the average SLR, and also better than the HCPFD by 9.21% and the DCPD by 7.66% with respect to the average speedup.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.7
• /
• pp.759-767
• /
• 2010

RT-eCos 3.0 is a micro-sized embedded real-time kernel that has been developed based on the open source eCos 3.0 to support the basic task model of the well-known distributed real-time object model, TMO(Time-Triggered Message-triggered Object). In this paper, the design and implementation techniques of the RMMC(Real-time Multicast & Memory replication Channel) that is a standard distributed IPC model of the TMO is described based on the RT-eCos 3.0. And the support technique of the global time for using the same time in a distributed environment using the RMMC is also described. The developed global time based RMMC supports highly abstracted distributed IPC environment in a wide area distributed computing environment with the RT-eCos 3.0.

• The Journal of Korean Association of Computer Education
• /
• v.10 no.3
• /
• pp.49-56
• /
• 2007

Grid provides a platform for the efficient execution of large-scale computing in science and engineering. In this environment, resource management and task scheduling are complex undertaking. We designed and implemented a web-based scheduling toolkit(GridTool), which can model a system and simulate scheduling scheme in Grid computing. The GridTool used GridSim, a toolkit in java-environment, as a tool for simulation. The GridTool is able to perform resource modeling, task modeling, algorithm compiling, simulation, and performance evaluation efficiently in web environment. The GridTool can be applied as a platform for Grid research and can be used to analyze the efficiency of scheduling algorithm.

• 한국HCI학회:학술대회논문집
• /
• 2007.02a
• /
• pp.567-572
• /
• 2007

빠른 인터넷의 보급과 빈번하게 발생하는 원격지 구성원간의 협업으로 인해서 쉽고 편리하게 이용 가능한 다자간 협업 환경의 필요성이 대두되었으며 현재 이와 관련한 연구가 활발히 진행되고 있다. 커뮤니티 컴퓨팅 환경에서의 원격 협업을 지원하기 위한 구성 기술로는 먼저 지능형 원격협업을 지원할 수 있는 시스템 및 네트워킹 구조를 설계하는 기술, 다양한 종류의 입력 채널의 내용을 동시에 보여줄 수 있는 디스플레이를 제공하는 기술, 협업 구성원 간의 자연스러운 데이터 및 태스크 마이그레이션 기반 기술, 그리고 다양한 사용자 인터랙션을 제공하는 기술 등이 있다. 그러나 무엇보다도 사용자 편의성 면에서는 위치적인 이질감을 극복하고 현장감 있는 공동 작업을 지원할 수 있는 사용자 인터랙션 기술이 매우 중요하다고 할 수 있다. 본 논문에서는 이러한 인터랙션을 지원하기 위한 다양한 인터랙션 기술을 소개하며 사용자의 인터랙션이 발생했을 경우 사용자의 의도에 따라 변경된 협업 환경, 특히 공통 디스플레이 화면의 변경 정보를 사용자 컨트롤 머신에도 Graphic User Interface(GUI) 기술을 통해 제공하는 방안이 논의되어 진다.