• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• 정보처리학회논문지A
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• 제11A권3호
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• pp.181-188
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• 2004

인터넷 기반 분산/병렬 처리 시스템인 PDP(Parallel/Distributed Processing)는 인터넷의 유휴상태 호스트들을 이용하여 대용량 작업을 병렬로 처리해서 전체 수행 시간을 감소시킨다. 본 연구에서는 실시간 네트워크 모니터링을 활용하여 수시로 변화하는 네트워크 환경에 적응하여 병렬/분산 처리되는 방안을 제안한다. 실시간 네트워크 모니터링 정보를 PDP 주요 핵심 알고리즘들에 적용하여 네트워크 과부하 및 결함으로 발생하는 작업 지연 요소에 적응적으로 대처함으로써 전체 성능이 향상됨을 보인다.

• 한국정보통신학회논문지
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• 제15권3호
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• pp.753-758
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• 2011

군의 요구에 의해서 장비 성능에 대한 안정성과 긴박한 시간에 그 성능을 유지할 수 있는 생존성을 증대시키기 위한 방법이 대두되고 있으며, 그 방법 중의 하나로 시스템에서의 이중화 설계에 대한 이슈가 늘어나고 있는 추세이다. 일반적으로 시스템의 생존성을 증대시키기 위한 방법으로써 적용하는 이중화 기법은 두 개의 프로세스 상호간에 두 개의 네트워크망을 구성하여 이중화를 구현하는 것이다. 그러나 프로세스의 고장이나 물리적 네트워크망이 손실되었을 경우 기능을 제대로 수행하지 못할 수 있다. 이에 본 논문에서는 VMEbus의 master와 slave 간의 공유 메모리 영역, 인터럽트 방식 적용, 이중화를 담당하는 전용 task와 통신 이상 시 이를 처리하는 이벤트를 발생시키는 프로토콜을 직접 구현하고, 실험을 통하여 이 방안의 타당성을 확인한다.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.904-914
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• 2008

An action-selection-mechanism(ASM) has been proposed to work as a fully connected finite state machine to deal with sequential behaviors as well as to allow a state in the task program to migrate to any state in the task, in which a primitive node in association with a state and its transitional conditions can be easily inserted/deleted. Also, such a primitive node can be learned by a shortest path-finding-based reinforcement learning technique. Specifically, we define a behavioral motivation as having state-dependent value as a primitive node for action selection, and then sequentially construct a network of behavioral motivations in such a way that the value of a parent node is allowed to flow into a child node by a releasing mechanism. A vertical path in a network represents a behavioral sequence. Here, such a tree for our proposed ASM can be newly generated and/or updated whenever a new behavior sequence is learned. To show the validity of our proposed ASM, experimental results of a mobile robot performing the task of pushing- a- box-in to- a-goal(PBIG) will be illustrated.

• 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.

• 한국멀티미디어학회논문지
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• 제3권3호
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• pp.320-332
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• 2000

웹은 네트워크로 연결된 모든 컴퓨터를 하나로 묶는 거대한 가상 시스템을 구성한다. 인터넷에 존재하는 수많은 유휴 상태 시스템을 이용하여 병렬 처리함으로써 비용 대 성능비가 매우 높으며 강력한 컴퓨팅 파워를 요구하는 거대한 문제를 해결할 수 있다. 하지만, 로컬 네트워크가 아닌 인터 넷 전체를 대상으로 하는 글로벌 환경에서 병렬 수행하는데 호스트들간의 이질성, 접근의 용이성, 작업에 대한 신뢰성을 고려해야 한다. 본 논문은 가상 병렬 처리 시스템인 WebImg를 설계 및 구현하여 웹 컴퓨팅 이 가능하며 동일한 작업을 여러 호스트에게 분배하기 위한 유연성 있는 작업 할당 전략을 제시하고 그 성능을 평가한다. 작업에 참여한 이 기종 호스트들이 가변적인 환경에서 작업 수행 도중 시스템의 성능변화에 대처하여 재할당 연산을 이용한 유연성 있는 작업 할당 기법을 제시한다. 더욱이 제안한 작업 할당 전략은 참여 호스트의 상태를 수시로 제어하여 결함내성을 제공한다.

• 한국정보과학회논문지:시스템및이론
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• 제35권3호
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• pp.120-132
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• 2008

네트워크-온-칩은 미래 시스템-온-칩 제품을 위한 실용적인 개발 플랫폼으로서 부각되고 있다. 우리는 전압 조절이 가능한 회선을 가진 네트워크-온-칩에서 태스크간 통신으로 인한 전력 소모를 최소화하기 위한 정적 알고리즘을 제시한다. 최적의 통신 속도를 찾기 위해 제시된 (유전자 알고리즘에 기반한) 기법은 네트워크 망 구조, 태스크 할당, 타일 매핑, 라우팅 경로 할당, 태스크 스케줄링과 회선 속도할당을 포함한다. 제시된 설계 기법은 기존의 기법과 비교하여 평균 28%까지 전력 소비를 감소시킬 수 있다는 것을 실험 결과는 보여 준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1104-1120
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• 2020

The chest X-rays are a common way to diagnose lung cancer or pneumonia. In particular, the finding of a lung nodule is the most important problem in the early detection of lung cancer. Recently, a lot of automatic diagnosis algorithms have been studied to find the lung nodules missed by doctors. The algorithms are typically based on segmentation network like U-Net. However, the occurrence of false positives that similar to lung nodules present outside the lungs can severely degrade performance. In this study, we propose a multi-task learning method that simultaneously learns the lung region and nodule-labeled data based on the prior knowledge that lung nodules exist only in the lung. The proposed method significantly reduces false positives outside the lung and improves the recognition rate of lung nodules to 83.8 F1 score compared to 66.6 F1 score of single task learning with U-net model. The experimental results on the JSRT public dataset demonstrate the effectiveness of the proposed method compared with other baseline methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5269-5286
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• 2018

Task scheduling is one of the key issues in improving system performance and optimizing resource management in cloud computing environment. In order to provide appropriate services for heterogeneous users, we propose a novel task scheduling strategy with service differentiation, in which the delay sensitive tasks are assigned to the rapid cloud with high-speed processing, whereas the fault sensitive tasks are assigned to the reliable cloud with service restoration. Considering that a user can receive service from either local SaaS (Software as a Service) servers or public IaaS (Infrastructure as a Service) cloud, we establish a hybrid queueing network based system model. With the assumption of Poisson arriving process, we analyze the system model in steady state. Moreover, we derive the performance measures in terms of average response time of the delay sensitive tasks and utilization of VMs (Virtual Machines) in reliable cloud. We provide experimental results to validate the proposed strategy and the system model. Furthermore, we investigate the Nash equilibrium behavior and the social optimization behavior of the delay sensitive tasks. Finally, we carry out an improved intelligent searching algorithm to obtain the optimal arrival rate of total tasks and present a pricing policy for the delay sensitive tasks.