• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.83-86
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• 2021

비디오 컨텐츠 사용이 증가하면서, 사용자가 요구한 파일을 제시간 안에 전달하는 문제가 중요해졌다. 사용자와 가까운 곳에 파일을 캐싱해 두고 필요할 때 다운받으면 파일을 보다 빨리 전달할 수 있는데 사용자가 움직일 경우 이동성을 고려해야 한다. 본 논문에서는 사용자의 이동 경로와 파일의 인기도를 함께 고려해 딜레이드 오프로딩(delayed offloading) 스키마를 적용한 환경에서 마이크로 기지국(micro base station, MBS)에서 다운받는 데이터 크기를 최소로 만들어 비용을 최소화 하는 캐싱 기법을 제안한다. 실험을 통해 타알고리즘에 비해 MBS 로부터 다운받는 양을 줄이고 스몰 셀 기지국(small cell base station, SBS)에서 다운받을 성공 확률을 높이는데 효과가 있다는 것을 보였다.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.43-50
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• 2022

As the use of mobile data increases, the proportion of video content is increasing steeply. In order to solve problems that arise when mobile users receive data from geographically remote cloud servers, methods of caching data in advance to edge servers geographically close to the users are attracting lots of attention. In this paper, we present a caching policy that stores data on Small Cell Base Station(SBS) to effectively provide content files to mobile users by applying a delayed offloading scheme in a cellular network. The goal of the proposed policy is to minimize the size of data transmitted from Macro Base Station(MBS) because the delayed offloading scheme requires more cost than when downloaded from MBS than from SBS. The caching policy is proposed to determine the size of content file and which content file to be cached to SBS using the probability of mobile users' paths and the popularity of content files, and to replace content files in consideration of the overlapping coverage of SBS. In addition, through performance evaluation, it has been proven that the proposed policy reduces the size of data downloaded from MBS compared to other algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.872-885
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• 2015

The rapid increase of smart mobile devices and mobile applications has led to explosive growth of data traffic in cellular network. Offloading data traffic becomes one of the most urgent technical problems. Recent work has proposed to exploit opportunistic communications to offload cellular traffic for mobile data dissemination services, especially for accepting large delayed data. The basic idea is to deliver the data to only part of subscribers (called target-nodes) via the cellular network, and allow target-nodes to disseminate the data through opportunistic communications. Human mobility shows temporal and spatial characteristics and predictability, which can be used as effective guidance efficient opportunistic communication. Therefore, based on the regularity of human mobility we propose NodeRank algorithm which uses the encounter characteristics between nodes to choose target nodes. Different from the existing work which only using encounter frequency, NodeRank algorithm combined the contact time and inter-contact time meanwhile to ensure integrity and availability of message delivery. The simulation results based on real-world mobility traces show the performance advantages of NodeRank in offloading efficiency and network redundant copies.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.3
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• pp.342-347
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• 2015

Floating LNG is a new concept which is used as LNG regasification/receiving facility and for LNG production/export facility. LNG Floating Production Storage and Offloading(FPSO) concept will put vitality into marginal gas fields which were delayed because of excessive investment cost in the world. LNG Floating Storage Regasification Unit(FSRU) also provides commercially competitive and effective solutions to the areas where onshore infrastructure is not well established. LNG cargo containment system is one of the key functions for FLNG to store produced LNG on a floating structure. This paper presents a new technology related to a LNG containment system; a combined cargo containment system utilizing the advantages of iIndependent tank type and membrane system. Technical advantages have been validated through research work.