• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4849-4864
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• 2019

Modern applications such as augmented reality, connected vehicles, video streaming and gaming have stringent requirements on latency, bandwidth and computation resources. The explosion in data generation by mobile devices has further exacerbated the situation. Mobile Edge Computing (MEC) is a recent addition to the edge computing paradigm that amalgamates the cloud computing capabilities with cellular communications. The concept of MEC is to relocate the cloud capabilities to the edge of the network for yielding ultra-low latency, high computation, high bandwidth, low burden on the core network, enhanced quality of experience (QoE), and efficient resource utilization. In this paper, we provide a comprehensive overview on different traits of MEC including its use cases, architecture, computation offloading, security, economic aspects, research challenges, and potential future directions.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.2
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• pp.179-187
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• 2013

Floating production storage and offloading (FPSO) facilities are used at most of the offshore oil fields worldwide. FPSO usage is expected to grow as oil fields move to deeper water, thus requiring the reliability and stability of mooring wires and risers in extreme environmental conditions. Except for the case of predictable attack angles of external loadings, FPSO facilities with turret single point mooring (SPM) systems are in general use. There are two types of turret systems: permanent systems and disconnectable turret mooring systems. Extreme environment criteria for permanent moorings are usually based on a 100-year return period event. It is common to use two or three environments including the 100-year wave with associated wind and current, and the 100-year wind with associated waves and current. When fitted with a disconnectable turret mooring system, FPSOs can be used in areas where it is desirable to remove the production unit from the field temporarily to prevent exposure to extreme events such as cyclones or large icebergs. Static and dynamic mooring analyses were performed to evaluate the stability of a spider buoy after disconnection from a turret during cyclone environmental conditions.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.513-522
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• 2016

We propose a mechanism for monitoring load in quality of service (QoS)-enabled wireless networks and show how it can be used for network management as well as for dynamic pricing. Mobile network traffic, especially video, has grown exponentially over the last few years and it is anticipated that this trend will continue into the future. Driving factors include the availability of new affordable, smart devices, such as smart-phones and tablets, together with the expectation of high quality user experience for video as one would obtain at home. Although new technologies such as long term evolution (LTE) are expected to help satisfy this demand, the fact is that several other mechanisms will be needed to manage overload and congestion in the network. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality while making a profit. In the current work, we address this issue by first investigating how the network load can be accurately monitored and then we show how this load metric can then be used to provide creative pricing plans. In addition, we describe its applications to features like traffic offloading and user satisfaction tracking.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.550-553
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• 2004

Recently, the demand for the Floating, Production, Storage, and Offloading facility (FPSO) which has some economic and technical advantages, has increased in offshore oil production areas. The 36,8000 DWT class FPSO was built in Hyundai Heavy Industries and will be installed in Offshore Angola. She dose not have self-propulsion system, but has additional facilities for oil production and positioning system. Main noise sources are contributing to the cabin noise of the accommodation are classified into three classes such as the machinery in the engine room and the deckhouse, HVAC system, and the topside equipments. In general, the noise regulation for the offshore structure is severer than that of the cargo ship and acceptable noise limit of cabin is specified as 45 dB(A). This paper describes the procedure of noise analysis, the countermeasures of noise control, and the measurement results of the quay trial. In order to minimize the noise levels, careful attention have to be paid by the special committee of experts from the initial design stage to the delivery. Proper countermeasures, considering the characteristics of sources and receiver spaces, were applied from the noise prediction and various experiment results. Finally, this ship was successfully delivered with excellent noise properties. The technology to minimize the noise levels for FPSO has been established throughout the construction of this ship.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.307-310
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• 2000

Recently, the demand for the Floating, Production Storage, and Offloading facility(FPSO) which has some economic and technical advantages, has increased in offshore oil production areas. The basic characteristics of a 343,000 DWT class FPSO which is being built in Hyundai Heavy Industries and shall be installed in offshore Angola, is almost same as that of oil carriers. However, she do not have self-propulsion system, but has additional facilities for oil production and positioning system. Main noise source contributing to the cabin noise of the accommodation, are classified into the machine in the engine room and the deckhouse, HVAC system, and the topside equipments. In general, the noise regulation for the offshore structure is much severer than that of the common commercial ships and the maximum acceptable sound pressure level of cabins is specified in 45dB(A). This paper describes the procedure of noise analysis along with its results. Noise analysis has been carried out for the case of emergency diesel generator running condition and the case of normal production condition and the results has been compared with the measurement results of the first case. Based on the results, proper countermeasures to reduce excessive noise level has been applied considering the characteristics of sources and receiver spaces and can be satisfied the specifications at all spaces.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.29-32
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• 2012

전통적으로 컴퓨터의 성능은 중앙 연산 장치 (CPU)의 성능에 따라 좌지우지 되어 왔다. 하지만 CPU의 성능이 지속적인 발전을 거듭하여 무어의 법칙을 비교적 충실히 따라가고 있는 반면, 메모리의 성능은 근래 들어 더디게 발전되는 형국이다. 때문에, CPU와 메모리 간의 성능격차로 인해 메모리의 낮은 성능이 전체 시스템의 성능을 저하시키는 "Memory Wall Problem"은 점점 큰 문제로 대두되고 있다. 이러한 문제를 해결하기 위해 많은 연구에서 메모리 자체의 성능을 발전시키는 것은 물론 메모리 내부에 연산 처리 능력을 추가하여 시스템 전체의 성능을 향상 시키는 시도들을 해왔다. 이 논문에서는 이러한 Intelligent한 메모리 시스템에서의 SW Off-loading을 위한 성능 분석을 다룬다. 이전의 연구들이 주로 큰 단위의 Off-load를 다뤘던 것에 비해 이 논문에서는 작은 단위의 Off-load, 더 정확히는 어셈블리 수준의 Off-load의 효과에 대해 분석한다. 또한 현재의 어셈블리 수준의 Off-load의 한계를 지적하고 이를 극복하기 위한 루프 레벨 Off-load, 새로운 Technology와 아키텍쳐에 대해서도 소개한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.107-108
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• 2019

모바일 엣지 컴퓨팅(Mobile Edge Computing, MEC)은 높은 컴퓨팅 성능을 요구하는 작업을 모바일 장치에서 가까운 MEC 서버로 오프로딩함으로써 모바일 서비스에 높은 계산 요구량을 효율적으로 제공할 수 있는 기술로 부상하였다. 본 논문에서는 실행 대기 시간과 장치 에너지 소비를 줄이기 위해 여러 가지의 독립적 작업을 통해 MEC 시스템에 대한 작업 오프로드 일정 및 전송 에너지 할당을 최적화하는 기법을 제안한다. 시뮬레이션 결과로 MEC 시스템에서 사용 가능한 무선 및 계산 리소스가 상대적으로 균형 잡혀있는 경우 작업 오프로딩 일정이 더 중요하다는 것을 확인했다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5614-5633
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• 2018

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

• ETRI Journal
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• v.44 no.5
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• pp.746-758
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• 2022

This paper focuses on a mobile edge-computing-enabled heterogeneous network. A battery level-aware task-scheduling framework is proposed to improve the energy efficiency and prolong the operating hours of battery-powered mobile devices. The formulated optimization problem is a typical mixed-integer nonlinear programming problem. To solve this nondeterministic polynomial (NP)-hard problem, a decomposition-based task-scheduling algorithm is proposed. Using an alternating optimization technology, the original problem is divided into three subproblems. In the outer loop, task offloading decisions are yielded using a pruning search algorithm for the task offloading subproblem. In the inner loop, closed-form solutions for computational resource allocation subproblems are derived using the Lagrangian multiplier method. Then, it is proven that the transmitted power-allocation subproblem is a unimodal problem; this subproblem is solved using a gradient-based bisection search algorithm. The simulation results demonstrate that the proposed framework achieves better energy efficiency than other frameworks. Additionally, the impact of the battery level-aware scheme on the operating hours of battery-powered mobile devices is also investigated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.689-692
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• 2021

This paper is a prior study to improve the efficiency of offloading based on mobile agents to optimize allocation of computing resources and reduce latency that support user proximity of application services in a Fog/Edge Computing (FEC) environment. We propose an algorithm that effectively reduces the execution time and the amount of memory required when extracting optimal moving patterns from the vast set of spatio-temporal movement history data of moving objects. The proposed algorithm can be useful for the distribution and deployment of computing resources for computation offloading in future FEC environments through frequency-based optimal path extraction.