• 터널과지하공간
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• 제29권4호
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• pp.262-279
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• 2019

고준위방사성폐기물처분장의 공학적 방벽에서는 다양한 원인으로 인해 기체가 발생한다. 만약 기체 생성 속도가 기체 확산 속도보다 빠를 경우 기체의 압력이 증가하게 되고, 기체 유입 압력(gas entry pressure)을 넘어서게 되면 기체가 급격히 벤토나이트 완충재를 통과하는 기체 이동 현상(gas migration)이 발생하게 되며 이는 사람과 주변 환경을 방사능에 노출시킬 수 있기 때문에, 공학적 방벽의 장기 건전성 확보 측면에서 기체 이동 현상을 명확히 규명하는 것이 매우 중요하다. 특히 벤토나이트 완충재와 같이 점토 물질을 다량 함유한 매질에서만 나타나는 매우 중요한 기체 흐름 현상인 팽창 흐름에 대한 수리-역학적 메커니즘을 규명하고, 기체 이동 현상의 정량적 평가를 위한 새로운 수치 해석 기법 개발 및 검증이 필수적이다. 따라서 본 연구에서는 공학적 방벽에서의 기체 이동 현상을 모사하고자 역학 손상 모델 및 손상도를 고려한 2상 유동 모델을 개발하였으며, 일정 체적 경계 조건 하에서의 1차원 기체 주입 시험 모사를 통해 개발된 모델의 적용성을 검토하였다. 수치 해석 결과 공극 수압 및 응력, 기체 유출량이 팽창 흐름 발생 시 급격히 증가하는 현상을 모사할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4103-4121
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• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

• 인터넷정보학회논문지
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• 제24권2호
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• pp.1-10
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• 2023

The Multi-access Edge Computing (MEC) paradigm equips network edge telecommunication infrastructure with cloud computing resources. It seeks to transform the edge into an IT services platform for hosting resource-intensive and delay-stringent services for mobile users, thereby significantly enhancing perceived service quality of experience. However, erratic user mobility impedes seamless service continuity as well as satisfying delay-stringent service requirements, especially as users roam farther away from the serving MEC resource, which deteriorates quality of experience. This work proposes a deep reinforcement learning based service mobility management approach for ensuring seamless migration of service instances along user mobility. The proposed approach focuses on the problem of selecting the optimal MEC resource to host services for high mobility users, thereby reducing service migration rejection rate and enhancing service availability. Efficacy of the proposed approach is confirmed through simulation experiments, where results show that on average, the proposed scheme reduces service delay by 8%, task computing time by 36%, and migration rejection rate by more than 90%, when comparing to a baseline scheme.

• Physical Therapy Rehabilitation Science
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• 제5권4호
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• pp.193-197
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• 2016

Objective: In the present study, the effects of visual restriction and unstable base dual-task training (VUDT), stable base dual-task training (SDT), and on stroke patients' balance and concentration abilities were examined. Design: Two-group pretest-posttest design. Methods: Dual-task training was conducted for thirty persons with chronic stroke who were hospitalized or receiving physical therapy and were randomly assigned to either the VUDT group (n=15) or the SDT group (n=15). The subjects were divided into two groups of 15 participants each, the VUDT group and the SDT group. Dual-task training was administered for 30 minutes per session, three times a week for 8 weeks. The participants' balance was measured via the center of pressure migration distances, functional reach test (FRT), Berg Balance Scale (BBS), and attention was measured using the trail-making test and the Stroop test. Results: In comparisons within each group, the two groups showed significant differences before and after the training (p<0.05). In the comparisons between the groups, the VUDT group showed significant improvements in center of pressure (COP), FRT, and BBS, and TMT compared to the SDT group (p<0.05). Conclusions: It would be more effective to conduct dual-task training as a rehabilitation training program under vision restriction and unstable supporting surface conditions than to conduct the test under unstable supporting plane conditions to improve balance and attention in chronic stroke patients.

• ETRI Journal
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• 제20권4호
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• pp.346-360
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• 1998

It is challenging to parallelize problems with irregular computation and communication. In this paper, we propose an asynchronous algorithm for balancing unpredictable workload on distributed-memory machines. By using an initial workload estimate, we first partition the computations such that the workload is distributed evenly across the processors. In addition, we perform task migrations dynamically for adapting to the evolving workload. To demonstrate the usefulness of our load balancing strategy, we conducted experiments on an IBM SP2 and a Cray T3D. Experimental results show that our task migration strategy can balance unpredictable workload with little overhead. Our code using C and MPI is portable onto other distributed-memory machines.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.176-179
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• 2002

In recent years, an increasing amount of computer network research has focused on the problem of cluster system in order to achieve higher performance and lower cost. The load unbalance is the major defect that reduces performance of a cluster system that uses parallel program in a form of SPMD (Single Program Multiple Data). Also, the load unbalance is a problem of MPP (Massive Parallel Processors), and distributed system. The cluster system is a loosely-coupled distributed system, therefore, it has higher communication overhead than MPP. Dynamic load balancing can solve the load unbalance problem of cluster system and reduce its communication cost. The cluster systems considered in this paper consist of P heterogeneous nodes connected by a switch-based network. The master node can predict the average execution time of tasks for each slave node based on the information from the corresponding slave node. Then, the master node redistributes remaining tasks to each node considering the predicted execution time and the communication overhead for task migration. The proposed dynamic load balancing uses execution time prediction to optimize the task redistribution. The various performance factors such as node number, task number, and communication cost are considered to improve the performance of cluster system. From the simulation results, we verified the effectiveness of the proposed dynamic load balancing algorithm.

• 대한치과의사협회지
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• 제48권10호
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• pp.738-753
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• 2010

Objectives: To deter job migration and to facilitate a more efficient personnel management system, a personality type analysis tool, such as MBTI and Enneagram, may be considered. These tools can facilitate better recognition of talent among prospective employees, as well as more efficient allocation of tasks for greater job satisfaction. Methods: This study conducted direct interviews with dental hygienists currently employed at two major dental organizations, which operate the largest networks of clinics across the greater metropolitan area. Results : First, in terms of number of turnover experiences, the Head Type showed lower task satisfaction, whereas the Body Type exhibited greater task satisfaction. Second, the Head Type showed greater job satisfaction compared to the other types. Third, the SJ Type, often considered the traditionalist in terms of long-term employments, exhibited greater tendencies toward long-term commitment with one employer. Fourth, dental hygienists, in terms of long-term employment, are negatively affected by task satisfaction, and positively affected by job satisfaction. Conclusions: It is thought to be considerable to use personality type analysis tools in clinical human resource management.

• 한국컴퓨터정보학회논문지
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• 제12권3호
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• pp.165-175
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• 2007

이동 에이전트는 에이전트 코드 자체가 서버로 이동하여 주어진 작업을 수행한다. 이 때 노드 이주 방법은 분산 시스템의 전체 성능에 큰 영향을 줄 수 있는 요소가 된다. 따라서 본 논문에서는 네이밍 에이전트의 메타데이터를 이용한 이동 에이전트의 적응적 이주 경로 기법을 제안한다. 제안 기법에서 노드 이주의 선택은 참조된 메타데이터의 정보에 의존하며, 이주 정보의 신뢰성은 멀티 에이전트의 각 에이전트 시스템들의 상호 협력 및 메타데이터 갱신 방법에 의해 결정된다. 이를 위해 적중 문건 수 적중률, 노드 처리 및 네트워크 지연 시간 등의 정보로 메타데이터를 설계하고 이를 이용하여 각 에이전트의 상호 관계와 적중 문건의 수에 따라 이동 에이전트의 적응적 이주 경로를 결정하기 위한 메타데이터의 생성, 이용 및 갱신하는 방법을 기술한다. 그리고 제안 이주 기법을 실험 및 분석을 통해 성능을 평가한 결과 메타데이터를 적용한 경우는 13개 노드만을 순회하면 될 뿐 아니라, 수집된 문건에 대한 적중률(72%) 또한 높기 때문에 높은 유효정보 확보율을 얻을 수 있다. 하지만 메타데이터를 적용하지 않은 경우는 26개의 노드를 순회하여 수집된 문건에 대한 적중률이 46%이며 사용자가 원하는 유효정보를 포함하고 있을 유효정보 확보율은 36.8% 이다.

• International Journal of Control, Automation, and Systems
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• 제2권3호
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• pp.333-342
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• 2004

This paper presents a framework for the self-organization of swarm systems based on coupled nonlinear oscillators (CNOs). In this scheme, multiple agents in a swarm self-organize to flock and arrange themselves as a group using CNOs, which are able to keep a certain distance by the attractive and repulsive forces among different agents. A theoretical approach of flocking behavior by CNOs and a design guideline of CNO parameters are proposed. Finally, the formation scenario for cooperative multi-agent groups is investigated to demonstrate group behaviors such as aggregation, migration, homing and so on. The task for each group in this scenario is to perform a series of processes such as gathering into a whole group or splitting into two groups, and then to return to the base while avoiding collision with agents in different groups and maintaining the formation of each group.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.100-103
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• 2021

5G 의 발전과 함께 차량과 IT 통신 기술을 융합한 어플리케이션들이 급증하면서 멀티 액세스 엣지 컴퓨팅(MEC)이 차세대 기술로 등장했다. 낮은 지연시간 안에 계산 집약적인 서비스들을 제공하기 위해 단독적인 MECS 서버(MECS)에서의 수행이 아닌 다수의 MECS 에서 동시에 연산을 수행할 수 있도록 태스크를 파티셔닝하는 기법이 주목받고 있다. 특히 차량이 다수의 MECS 로 태스크를 파티셔닝하여 오프로딩하는 기법과 하나의 MECS 로 오프로딩한 후 다른 MECS 들로 파티셔닝하여 마이그레이션하는 기법들이 연구되고 있다. 본 논문에서는 오프로딩과 마이그레이션을 이용한 파티셔닝 기법들을 서비스 지연시간과 차량의 에너지 소비량 측면에서 성능을 비교 분석을 하였다.