• 방송공학회논문지
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• 제19권1호
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• pp.24-30
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• 2014

이 연구는 모바일 기기를 이용한 실시간 동영상 개인 방송 서비스에서 동영상 압축 계산의 부담을 클라우드 컴퓨팅에 오프로딩하는 효과에 대한 연구이다. 모바일 기기에 비해 클라우드는 컴퓨팅 자원과 전력 자원이 매우 풍부하다. 모바일 기기에서의 계산을 줄임으로써 전력사용을 줄일 수 있으나, 압축효율이 떨어져서 전송해야할 데이터양은 늘어난다. 본 연구에서는 전력 절약과 전송 데이터 양 증가의 트레이드오프 분석을 통하여 LTE 통신환경에 따라 오프로딩되는 계산량을 제어하여 최적의 운용조건을 찾을 수 있음을 보인다.

• KEPCO Journal on Electric Power and Energy
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• 제8권2호
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• pp.159-179
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• 2022

Often a network becomes complex, and multiple entities would get in charge of managing part of the whole network. An example is a utility grid. While the entire grid would go under a single utility company's responsibility, the network is often split into multiple subsections. Subsequently, each subsection would be given as the responsibility area to the corresponding sub-organization in the utility company. The issue of how to make subsystems of adequate size and minimum number of interconnections between subsystems becomes more critical, especially in real-time simulations. Because the computation capability limit of a single computation unit, regardless of whether it is a high-speed conventional CPU core or an FPGA computational engine, it comes with a maximum limit that can be completed within a given amount of execution time. The issue becomes worsened in real time simulation, in which the computation needs to be in precise synchronization with the real-world clock. When the subject of the computation allows for a longer execution time, i.e., a larger time step size, a larger portion of the network can be put on a computation unit. This translates into a larger margin of the difference between the worst and the best. In other words, even though the worst (or the largest) computational burden is orders of magnitude larger than the best (or the smallest) computational burden, all the necessary computation can still be completed within the given amount of time. However, the requirement of real-time makes the margin much smaller. In other words, the difference between the worst and the best should be as small as possible in order to ensure the even distribution of the computational load. Besides, data exchange/communication is essential in parallel computation, affecting the overall performance. However, the exchange of data takes time. Therefore, the corresponding consideration needs to be with the computational load distribution among multiple calculation units. If it turns out in a satisfactory way, such distribution will raise the possibility of completing the necessary computation in a given amount of time, which might come down in the level of microsecond order. This paper presents an effective way to split a given electrical network, according to multiple criteria, for the purpose of distributing the entire computational load into a set of even (or close to even) sized computational loads. Based on the proposed system splitting method, heavy computation burdens of large-scale electrical networks can be distributed to multiple calculation units, such as an RTDS real time simulator, achieving either more efficient usage of the calculation units, a reduction of the necessary size of the simulation time step, or both.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.226-238
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• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.

• 정보보호학회논문지
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• 제21권2호
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• pp.27-35
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• 2011

최근 IPTV 서비스 환경이 Mobile IPTV 서비스로 발전함에 따라 이동 단말에서 안전하게 IPTV 서비스를 제공받을 수 있도록 지원하는 보안 기술이 요구되고 있다. CAS는 IPTV 서비스 환경에서 콘텐츠 보호와 서비스 보호를 위해 사용되고 있다. 그러나 CAS의 경우 사용되는 보안키를 갱신하는 과정에서 사용하는 EMM으로 인한 채널 대역폭이 증가하고, 키 관리 서버에서 각 가입자들에게 서비스키를 갱신하기 위해 계산해야하는 연산량이 증가하는 문제점이 있다. 본 논문에서는 이러한 문제점을 해결하기 위해 서비스에 가입할 때 스마트카드 또는 USIM에 초기 마스터키를 보관하여 분배하고, 마스터키로부터 계층적 키를 유도함으로써 EMM을 사용하지 않고도 서비스키를 갱신 할 수 있도록 제안하였다.

• 대한교통학회지
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• 제27권6호
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• pp.129-137
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• 2009

첨단교통체계의 기술발전과 교통 분석의 수준이 상세해짐에 따라 동적 교통 분석에 대한 필요성이 증가하고 있다. 기존의 정적인 분석이 하루 평균 개념의 통행특성과 네트워크 상태를 묘사한 반면, 동적 분석에서는 시간흐름에 따른 네트워크의 상태를 분석한다. 본 논문에서는 교통시스템 동적 분석의 필요성을 인식하여, 고속도로망을 대상으로 FTMS 자료를 활용한 분석 방법론을 개발하였다. 개별 차량의 실제 통행기록 자료인 TCS 자료를 이용하여 전국 고속도로망을 대상으로 동적 기종점 통행량을 구축하였으며, 시뮬레이션 연산시간 문제 해결을 위해 분석범위를 설정한 Subarea 분석을 활용하였다. 이를 위해 전국 고속도로망을 대상으로 구축된 시간대별 기종점 통행량을 Subarea 기종점 통행량으로 전환하기 위한 방법론을 개발하였다. 구축된 모형의 적용을 위해 시나리오 분석을 실시하였으며, 이를 통해 각각의 시나리오에 대하여 기존의 단편적인 효과분석과 달리 하루 중 시간대별 교통여건에 따른 네트워크 상태분석을 수행하였다. 본 연구는 동적 교통 분석의 초기 시도라는 점과 실제 기종점 자료인 FTMS 자료를 활용한 분석이라는 점에서 의미를 가지며, 현재 교통 분석의 큰 흐름인 동적 교통 분석의 필요성을 부각시키고자 한다. 향후 고속도로뿐만이 아닌 기타 도로를 포함한 모형 구축이 필요하며, Hybrid 모형 및 프로그램 개발을 통해 궁극적인 목표인 실시간동적 분석 모형 개발을 위한 연산시간 문제 해결이 필요할 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.495-500
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• 1998

This paper introduces our three approaches to reduce the burden of human interactive EC operators: (1) improvement of the interface of presenting individuals, (2)improvement of the interface of inputting fitness values, and (3) fast EC convergence. We propose methods to display individuals in order of predicted fitness values by neural networks or Euclidean distance measure for (1), to input quantized fitness values for (2), and to make a new elite by approximating the EC search space with a quadratic function for (3). They are evaluated through simulations and subjective testes, and their effects have shown.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.771-776
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• 1991

In this paper. an indirect adaptive controller for manipulator which is composed of two controller structure is considered. One is feedforward controller in which the dynamics equation solved and the other is feedback controller in which the output error compensated. This controller has a good performance, but the computation burden of the feed forward controller keep from real time control. At this point, we proposed the two time adaptive controller where the sampling time of the feedforward controller is quite longer than that of the feedback controller. By the computer simulation, this proposed two time adaptive controller shows good performance in the view of accuracy in spite of decreasing computational burden.

• Communications for Statistical Applications and Methods
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• 제28권6호
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• pp.673-679
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• 2021

The moment calculation in a truncated multivariate normal distribution is a long-standing problem in statistical computation. Recently, Kan and Robotti (2017) developed an algorithm able to calculate all orders of moment under different types of truncation. This result was implemented in an R package MomTrunc by Galarza et al. (2021); however, it is difficult to use the package in practical statistical problems because the computational burden increases exponentially as the order of the moment or the dimension of the random vector increases. Meanwhile, Lee (2021) presented an efficient numerical method in both accuracy and computational burden using Gauss-Hermit quadrature. This article introduces trunmnt implementation of Lee's work as an R package. The Package is believed to be useful for moment calculations in most practical statistical problems.

• 한국정밀공학회지
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• 제12권6호
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• pp.128-136
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• 1995

The problem addressed in this paper is that of the on-line computational burden of time-optimal control laws for quick, strongly nonlinear systems like revolute robots. It will be demonstrated that a large amount of off-line computation can be substituted for most of the on-line burden in cases of time optimization with constrained inputs if differential point-to- point specifications can be relaxed to cell-to-cell transitions. These cells result from a coarse discretization of likely swaths of state space into a set of nonuniform, contiguous volumes of relatively simple shapes. The cell boundaries approximate stream surfaces of the phase fluid and surfaces of equal transit times. Once the cells have been designed, the bang- bang schedules for the inputs are determined for all likely starting cells and terminating cells. The scheduling process is completed by treating all cells into which the trajectories might unex- pectedly stray as additional starting cells. Then an efficient-to-compute control law can be based on the resulting table of optimal strategies.