• International Journal of Computer Science & Network Security
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• 제23권10호
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• pp.73-80
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• 2023

The recent growth in the use of mobile devices has contributed to increased computing and storage requirements. Cloud computing has been used over the past decade to cater to computational and storage needs over the internet. However, the use of various mobile applications like Augmented Reality (AR), M2M Communications, V2X Communications, and the Internet of Things (IoT) led to the emergence of mobile cloud computing (MCC). All data from mobile devices is offloaded and computed on the cloud, removing all limitations incorporated with mobile devices. However, delays induced by the location of data centers led to the birth of edge computing technologies. In this paper, we discuss one of the edge computing technologies, i.e., cloudlet. Cloudlet brings the cloud close to the end-user leading to reduced delay and response time. An algorithm is proposed for scheduling tasks on cloudlet by considering VM's load. Simulation results indicate that the proposed algorithm provides 12% and 29% improvement over EMACS and QRR while balancing the load.

• 대한전자공학회논문지SD
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• 제41권2호
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• pp.55-65
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• 2004

본 논문에서는 레지스터 전송 수준의 데이터패스를 위한 효율적인 비주사 DFT 기법을 제안하였다. 데이터패스를 위해 제안된 비주사 DFT 기법은 레지스터 전송 수준(RTL : register transfer level) 회로에 대한 계층적 테스트 용이도(hierarchical testability) 분석을 통해 테스트 용이도를 향상시킴으로써 최소의 하드웨어 오버헤드를 가지고 데이터패스 버스 폭의 변화와 관계없이 항상 높은 고장 효율과 빠른 테스트 패턴 생성 시간을 보장한다. 실험 결과를 통하여 제안된 기법이 주사 기법보다 테스트 패턴 생성 시간, 테스트 패턴 적용 시간, 면적 오버헤드 면에서 우수함을 확인하였다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권9호
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• pp.399-406
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• 2023

클라우드 컴퓨팅은 에지 서버가 동작하는 포그(fog) 레이어가 결합된 에지(edge) 컴퓨팅 아키텍처로 진화하고 있다. 에지 컴퓨팅 아키텍처가 관심을 받는 이유는 짧은 통신 지연으로 실시간 IoT 응용을 지원할 수 있기 때문이다. 이와 동시에 인공지능 기술을 도입한 많은 클라우드 작업 스케줄링 기법들이 제안되었다. 인공지능 기반의 클라우드 작업 스케줄링 기법은 기존 기법보다 더 좋은 성능을 보이지만 스케줄링 시간이 다소 소요된다는 단점이 있다. 이 논문에서는 에지 컴퓨팅 환경에서 분산 딥러닝 학습 기반의 동적 스케줄링 기법을 제안한다. 제안하는 기법은 기존 기법보다 스케줄링 시간이 짧은 장점이 있다. 또한 멀티 에이전트를 통한 분산 딥러닝 학습의 효과성을 보이기 위해 확장적인 실험 환경에서 제안 기법과 기존 인공지능 기법의 성능일 비교 평가하였다. 성능 실험 결과 기존 인공지능 기반 클라우드 작업 스케줄링 기법보다 짧은 스케줄링 시간을 보여 IoT 실시간 응용에 적합함을 보였으며, 확장적인 실험에서도 제안 기법이 완료된 작업의 수에 대하여 우수한 성능을 보임을 증명하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1147-1161
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• 2023

The Internet of Things (IoT) requires a new processing model that will allow scalability in cloud computing while reducing time delay caused by data transmission within a network. Such a model can be achieved by using resources that are closer to the user, i.e., by relying on edge computing (EC). The amount of IoT data also grows with an increase in the number of IoT devices. However, building such a flexible model within a heterogeneous environment is difficult in terms of resources. Moreover, the increasing demand for IoT services necessitates shortening time delay and response time by achieving effective load balancing. IoT devices are expected to generate huge amounts of data within a short amount of time. They will be dynamically deployed, and IoT services will be provided to EC devices or cloud servers to minimize resource costs while meeting the latency and quality of service (QoS) constraints of IoT applications when IoT devices are at the endpoint. EC is an emerging solution to the data processing problem in IoT. In this study, we improve the load balancing process and distribute resources fairly to tasks, which, in turn, will improve QoS in cloud and reduce processing time, and consequently, response time.

• 한국컴퓨터정보학회논문지
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• 제11권2호
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• pp.131-143
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• 2006

무선통신 기술의 급속한 발전으로 무선 인터넷 서비스가 점차 확대되고 있고 그 중 모바일 실시간 처리가 큰 비중을 차지하고 있다. 모바일 트랜잭션 처리는 낮은 대역폭과 핸드오버, 응답시간 지연 등으로 그것의 활성화를 저해하는 여러 가지 문제점을 지니고 있음에도 불구하고 모바일 컴퓨팅 분야에 다양하게 응용되고 있다. 그래서 모바일 컴퓨팅 환경에서 제한된 대역폭을 효율적으로 사용하고, 병목현상을 개선한 새로운 동시성 제어 기법이 요구된다. 본 논문에서는 모바일 컴퓨팅 환경에서의 동시성 제어 문제를 효과적으로 해결하고 동시에 여러 트랜잭션을 처리하여 병렬성을 증진시키는 낙관적 동시성 기법을 제안하였다. 기존기법과 달리, 제안하는 기법은 같은 세그먼트 내에 다른 데이터를 접근하는 트랜잭션에게 세그먼트를 허용함으로써 불필요한 대기시간을 최소화 할 수 있도록 하여 시스템 처리율을 향상시켰다. 그리고 제안된 동시성 제어 기법의 알고리즘을 제안하였다.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.137-142
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• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.769-772
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• 2005

This paper describes a low-voltage and low-power channel selection analog front end with continuous-time low pass filters and highly linear programmable-gain amplifier(PGA). The filters were realized as balanced Gm-C biquadratic filters to achieve a low current consumption. High linearity and a constant wide bandwidth are achieved by using a new transconductance(Gm) cell. The PGA has a voltage gain varying from 0 to 65dB, while maintaining a constant bandwidth. A filter tuning circuit that requires an accurate time base but no external components is presented. With a 1-Vrms differential input and output, the filter achieves -85dB THD and a 78dB signal-to-noise ratio. Both the filter and PGA were implemented in a 0.18um 1P6M n-well CMOS process. They consume 3.2mW from a 1.8V power supply and occupy an area of $0.19mm^2$.

• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.300-307
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• 2016

Cloud computing that provide a elastic computing service is more complex compared to the existing computing systems. Accordingly, it has become increasingly important to maintain the stability and reliability of the computing system. And troubleshooting and real-time monitoring to address these challenges must be performed essentially. For these goals, the handling of the log data is needed, but this task in cloud computing environment may be more difficult compared to the traditional logging system. In addition, there are another challenges in order to have the admissibility of the collected log data in court. In this paper, we design secure logging service that provides the management and reliability of log data in a cloud computing environment and then analyze the proposed system.

• 한국멀티미디어학회논문지
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• 제17권3호
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• pp.353-363
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• 2014

Cloud computing is an internet-based technology, providing services to the virtualized IT environment, and allowing users to add or remove resources of hardware or software at their discretion. Since Cloud computing can construct virtually integrated environments out of multiple local computing environments, various information services can be provided by it. In addition, state organizations also strive to build the cloud computing environments due to the benefits of reduced costs to introduce the system and of reduced time to build and provide the IT services. This study suggests a web-based cloud computing system for the computing environments, to be applied for the Korean National Health and Nutrition Examination Survey (KNHANES) by the Ministry of Health and Welfare, Republic of Korea.

• 한국멀티미디어학회논문지
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• 제24권1호
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• pp.51-57
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• 2021

In this paper, we propose a task distribution scheme in fog computing environment considering opportunistic fog computing nodes. As latency is one of the important performance metric for IoT(Internet of Things) applications, there have been lots of researches on the fog computing system. However, since the load can be concentrated to the specific fog computing nodes due to the spatial and temporal IoT characteristics, the load distribution should be considered to prevent the performance degradation. Therefore, this paper proposes a task distribution scheme which considers the static as well as opportunistic fog computing nodes according to their mobility feature. Especially, based on the task requirements, the proposed scheme supports the delay sensitive task processing at the static fog node and delay in-sensitive tasks by means of the opportunistic fog nodes for the task distribution. Based on the performance evaluation, the proposed scheme shows low service response time compared to the conventional schemes.