• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1199-1202
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• 2017

IoT-Cloud 융합 가상 기계 시스템은 저성능의 사물인터넷 장비에서 고성능 클라우드 서버의 연산력을 제공받는 오프로딩 기법을 사용한다. 오프로딩 기법을 사용하는 경우 실행 대상 프로그램은 사물인터넷 장비와 클라우드 서버 사이에 일관성이 유지되어야하기 때문에 문맥 동기화가 필요하다. 기존 IoT-Cloud 융합 가상 기계의 문맥 동기화 방식은 전체 문맥 동기화를 시도하기 때문에 네트워크 오버헤드가 증가하여 비효율적이다. 네트워크 오버헤드는 오프로딩 실행 성능을 기존보다 감소시킬 수 있기 때문에 효율적인 오프로딩을 위해서는 오프로딩 실행에 필요한 문맥 정보만을 동기화하여 네트워크 오버헤드를 줄여야 한다. 본 논문에서는 효율적인 오프로딩 실행을 위해 정적 프로파일링을 통해 추출된 문맥 정보를 기반으로 오프로딩 실행에 필요한 문맥 정보만을 동기화하는 문맥 동기화기를 설계 및 구현하였다. 오프로딩 실행에 필요한 문맥 정보만 동기화가 이뤄지면 문맥 동기화 시 발생하는 네트워크 오버헤드의 크기가 줄어들기 때문에 효율적인 오프로딩 실행이 가능하다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.514-522
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• 2017

Traffic offloading is a promising solution to solve the explosive growth of mobile traffic. One of offloading schemes, in LIPA/SIPTO(Local IP Access and Selected IP Traffic Offload) offloading, we can offload mobile traffic that can satisfy QoS requirement for application. In addition, it is necessary for traffic offloading using social context due to large traffic from SNS. Thus, we propose the LIPA/SIPTO offloading algorithm using social context. We define the application selection probability using social context, the application popularity. Then, we find the optimal offloading weighting factor to maximize the QoS(Quality of Service) of small cell users in term of effective data rate. Finally, we determine the offloading ratio by this application selection probability and optimal offloading weighting factor. By performance analysis, the effective data rate achievement ratio of the proposed algorithm is similar with the conventional one although the total offloading ratio of the proposed algorithm is about 46 percent of the conventional one.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.89-92
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• 2020

According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.67-75
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• 2014

In this paper, we proposed offloading delay method which determines effectively offloading timing by measuring of handoff delay and offloading time at mobile node side in mobile environment. The propose method measures each of handoff delay and offloading time and making decision of proper offloading timing on mobile node side. Therefore, it is possible to support cloud computing without changing previous implemented cloud computing structure for fixed node in a mobile environment. We compare the energy consumption of server and node to analyze efficiency of proposed method by using existing method of energy consumption measurement. Simulation results shows the reducing energy consumption more than previous method and operation time similar to previous method.

• Journal of Internet Computing and Services
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• v.14 no.2
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• pp.73-85
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• 2013

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, /have been proposed. A typical approach to resolving resource problems of mobile nodes in MCC is to offload functional components to other resource-rich nodes. However, most of the current woks do not consider a characteristic of dynamically changed MCC environment and propose offloading mechanisms in a conceptual level. In this paper, in order to ensure performance of highly complex mobile applications, we propose four different types of offloading mechanisms which can be applied to diverse situations of MCC. And, the proposed offloading mechanisms are practically designed so that they can be implemented with current technologies. Moreover, we define cost models to derive the most sutilable situation of applying each offloading mechanism and prove the performance enhancement through offloadings in a quantitative manner.

• Journal of KIISE
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• v.44 no.9
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• pp.871-877
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• 2017

A vast amount of research has been carried out for executing compute-intensive applications on resource-constrained mobile devices. Computation offloading is a method in which heavy computations are dynamically migrated from a mobile device to a server, exploiting the powerful hardware of the server to perform complex computations. An important issue for offloading is the complexity of reconciling the execution state of applications between the server and the client. To address this issue, snapshot-based offloading has recently been proposed, which utilizes the snapshot of a web app as the portable description of the execution state. However, for web applications using the HTML5 canvas, snapshot-based offloading does not function correctly, because the snapshot cannot capture the state of the canvas. In this paper, we propose a code generation technique to save the canvas state as part of a snapshot, so that the snapshot-based offloading can be applied to web applications using the canvas.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1203-1206
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• 2017

IoT-Cloud 융합 가상 기계 시스템은 오프로딩 기법을 사용하여 저성능 사물인터넷 장비에서 고성능 클라우드 서버의 연산력을 제공받는다. 이 경우 오프로딩 실행 대상 프로그램은 사물인터넷 장비와 클라우드 서버의 실행환경에서 일관성이 유지되어야하기 때문에 문맥 동기화가 필요하다. 현재 문맥 동기화 방식은 전체 문맥 동기화를 시도하기 때문에 네트워크 오버헤드가 증가하여 비효율적이다. 본 논문은 오프로딩 실행에 필요한 문맥 정보만을 동기화하는 효율적인 문맥 동기화를 위해서 정적 프로파일링을 통해 오프로딩 실행 대상 작업에 동기화가 필요한 문맥 정보들을 사전에 추출하였다. 추출된 문맥 정보를 기반으로 문맥 동기화가 이뤄지면 오프로딩 실행에 필요한 문맥 정보만을 동기화하기 때문에 네트워크 통신 오버헤드 감소를 기대할 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.822-825
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• 2012

모바일 디바이스의 사용이 폭발적으로 증가하고 있고, 특히 스마트폰을 위한 많은 어플리케이션이 소개 되고 있지만, 여전히 스마트폰이 가지는 낮은 하드웨어 성능과 제한적인 배터리용량은 PC 환경을 대체하기가 어렵다. 본 논문에서는 클라우드가 가지는 서버 환경을 통해서 모바일 디바이스의 특정 태스크를 서버 사이드로 오프로딩 하여 실행하고, 단말은 그 결과만 전달받는 방식의 모바일 오프로딩 시스템을 제안한다. 실험을 통해서 모바일 오프로딩의 방법이 어플리케이션의 응답성을 높일 수 있음을 확인하였다. 또한 제시된 오프로딩 기법을 통해서 단말의 CPU utilization을 줄이고, 따라서 단말의 소모전력을 최대 70%까지 줄일 수 있었다.

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

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.5
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• pp.203-208
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• 2013

As smartphones are rapidly and widely spread, their applications request gradually larger computation power. Recently, in the personal computer, computing power of hardware has exceeded performance requirement of software sometimes. Computing power of smartphone, however, will not grow at the same pace as demand of applications because of form factor to seek thinner devices and power limitation by relatively slow technical progress of battery. Computation offloading is getting huge attention as one of solution for the problem. It has not commonly used technology in spite of advantages for performance and power consumption since the existing offloading frameworks are difficult for application developer to utilize. This paper presents an application developer-friendly offloading framework, named SorMob. Based on Aspect Oriented Programming model, SorMob provides a convenient environment for application development, and its performance was verified by comparing with the existing offloading framework.