• 한국통신학회논문지
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• 제38B권3호
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• pp.163-171
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• 2013

최근 HD급 동영상이나 3D 어플리케이션과 같은 이전보다 저사양, 모바일 단말에서는 구동하기 힘든 프로그램들에 대한 이용 요구가 확대되면서 처리해야 할 콘텐츠 데이터들이 고용량화 되고 있다. 클라우드 기반의 VDI(Virtual Desktop Infrastructure) 서비스는 이를 처리하기 위해 효율적인 데이터 처리 능력이 필요해졌으며 QoE(Quality of Experience) 보장을 위한 성능 개선 연구가 이슈가 되고 있다. 본 논문에서는 H/W 성능이 향상되어 CPU와 GPU를 탑재한 Thick Client기반의 3가지 Thick-Thin간 VDI 자원 공유 및 위임이 가능한 VDI 서비스에 대해 제안하며, VDI 서비스 성능의 개선을 위해 CPU와 GPU가 혼합된 Heterogeneous 멀티코어 환경에서 CPU와 GPU 병렬 처리 기법인 OpenMP와 CUDA를 활용하여 VDI 서비스 최적화 방안을 제안하고 기존의 VDI와 비교한 성능을 거론한다.

• 한국경영과학회지
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• 제16권2호
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• pp.118-127
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• 1991

In this paper, criteria and algorithms for the optimal service rate in a closed queueing network have been established. The objective is to minimize total cost. It is shown that system throughput is increasing concave over the service rate of a node and cycle time is increasing convex over the set of service times with a single calss of cubsomers. This enables developing an algorithm using a steepest descent method when the cost function for service rate is convex. The efficiency of the algorithm rests on the fact that the steepest descent direction is readily obtained at each iteration from the MVA algorithm. Several numerical examples are presented. The major application of this research is optimization of facility capacity in a manufacturing system.

• 산업경영시스템학회지
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• 제42권4호
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• pp.116-125
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• 2019

The Dynamic Vehicle Routing Problem (DVRP) involves a combinatorial optimization problem where new customer demands become known over time, and old routes must be reconfigured to generate new routes while executing the current solution. We consider the high level of dynamism problem. An application of highly dynamic DVRP is the ambulance service where a patient contacts the service center, followed by an evaluation of case severity, and a visit by a practitioner/ ambulance is scheduled accordingly. This paper considers a variant of the DVRP and proposes a decentralized algorithm in which collaborators (Depot and Vehicle), both have only partial information about the entire system. The DVRP is modeled as a periodic re optimization of VRP using the proposed decentralized algorithm where collaborators exchange local information to achieve the best global objective for the current state of the system. We assume the existence of a dispatcher e.g., headquarter of the company who can communicate to vehicles in order to gather information and assigns the new visits to them. The effectiveness of the proposed decentralized coordination algorithm is further evaluated using benchmark data given in literature. The results show that the proposed method performed better than the compared algorithms which utilize the centralized coordination in 12 out of 21 benchmark problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2840-2853
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• 2015

A major challenge in network service providers is to provide adequate resources in service level agreements based on forecasts of future demands. In this paper, we address the problem of capacity provisioning in a network subject to demand uncertainty such that a network coded multicast is applied as the data delivery mechanism with limited budget to purchase extra capacity. We address some particular type of uncertainty sets that obtain a tractable constrained capacity provisioning problem. For this reason, we first formulate a mathematical model for the problem under uncertain demand. Then, a robust optimization model is proposed for the problem to optimize the worst-case system performance. The robustness and effectiveness of the developed model are demonstrated by numerical results. The robust solution achieves more than 10% reduction and is better than the deterministic solution in the worst case.

• 산업공학
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• 제9권3호
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• pp.202-213
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• 1996

Video-on-demand is an interactive service that provides programs (movie, home shopping, etc.) to users connected to a network. This service will require high bandwidth network and video servers with a large amount of storage capacity. From the viewpoint of system analysis, there are optimization problems to be solved. In this paper, we present a dynamic programming method for allocating the storage for programs being served in a multi-level video-on-demand network. In the optimization of the network resource, we consider the three kinds of costs: installation cost for video servers, program storage cost, and transmission (or communication) cost. The factors related to the costs are investigated. An example is shown to illustrate the proposed method.

• 대한기계학회논문집A
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• 제34권8호
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• pp.1023-1028
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• 2010

최근에, 서비스용 지능형 로봇이 공공기관에서 방문객들에게 건물을 안내하고 정보를 제공하는데 사용되어지고 있다. 이 로봇은 지면 위치 인식 방식의 센서를 가지며 마름모형태의 네 바퀴로 스스로를 지탱한다. 로봇의 작동은 구동부분과 내부 구조가 하나의 결합된 몸체로 구성되어 있기 때문에 고르지 못한 장소에서는 제한을 받는다. 이와 같은 상태가 지속되면 로봇의 정밀한 부분에서 이상 징후가 발견 될 것이고, 각각의 연결 부위가 약화 될 것이다. 따라서 로봇의 동역학 모델이 만들어 졌고, 서스펜션과 함께 구동 특성들을 위한 모의실험도 이루어 졌다. 이 서스펜션 시스템은 로봇의 각 부분에 미치는 충격들을 줄이는데 최적화 되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권6호
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• pp.2050-2077
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• 2015

One of the major issues in emerging cloud management system needs the efficient service level agreement negotiation framework, with an optimal negotiation strategy. Most researchers focus mainly on the atomic service negotiation model, with the assistance of the Agent Controller in the broker part to reduce the total negotiation time, and communication overhead to some extent. This research focuses mainly on composite service negotiation, to further minimize both the total negotiation time and communication overhead through the pre-request optimization of broker strategy. The main objective of this research work is to introduce an Automated Dynamic Service Level Agreement Negotiation Framework (ADSLANF), which consists of an Intelligent Third-party Broker for composite service negotiation between the consumer and the service provider. A broker consists of an Intelligent Third-party Broker Agent, Agent Controller and Additional Agent Controller for managing and controlling its negotiation strategy. The Intelligent third-party broker agent manages the composite service by assigning its atomic services to multiple Agent Controllers. Using the Additional Agent Controllers, the Agent Controllers manage the concurrent negotiation with multiple service providers. In this process, the total negotiation time value is reduced partially. Further, the negotiation strategy is optimized in two stages, viz., Classified Similarity Matching (CSM) approach, and the Truncated Negotiation Group Gale Shapely Stable Matching (TNGGSSM) approach, to minimize the communication overhead.

• 대한전기학회논문지:전력기술부문A
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• 제50권2호
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• pp.67-75
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• 2001

This paper presents a fast and effective methodology for service restoration in large-scale distribution systems. The service restoration problem is formulated as a constrained optimization problem and requires the fast computation time and superior solution because the more unfaulted out-of-service area should be restored as soon as possible. The proposed methodology is designed to consider the fast computation time and priority service restoration by dijkstra algorithm and fuzzy theory in large-scale distribution systems. Simulation results demonstrate the validity and effectiveness of the proposed on a 26-bus and 140-bus system.

• 경영과학
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• 제33권3호
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• pp.89-103
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• 2016

In this paper, we design sampling inspections and service capacities simultaneously for multi-products. Products are supplied in batches after rectifying inspections, that is, rejected lot is subject to total inspection and defective products are reworked to good ones. When supplied, all defective products are uncovered and returned to service. Particularly, we extend Kim [1] by introducing the fixed costs of providing services and show that the cost function of a product is no longer linear or convex in terms of the level of service provision. We develop a framework for a product to deal with this joint design problem and a dynamic programming algorithm for multi-products which allocates the given number of the total service capacities among products with the considerably smaller computations than the total number of possible allocations.