• Journal of Information Processing Systems
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• 제2권2호
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• pp.130-134
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• 2006

In the distributed replicating server model, the provision of replicated services will improve the performance of the providing service and efficiency for clients. Efficiently composing the server selection algorithm decreases the retrieval time for replicated data. In this paper, we define the system model that selects and connects the replicated server that provides an optimal service using the server-side downstream measurement and propose a server selection algorithm.

• 한국시뮬레이션학회논문지
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• 제14권2호
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• pp.1-13
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• 2005

In distributed replicating server model, providing replicated services is able to improve the performance of providing a service and efficiency for several clients. And, the composition of the server selection algorithm is efficiently able to decrease the retrieval time for replicated data. In this paper, we define the system model that selects and connects the replicated server that provides optimal service using server-side downstream measurement and proposes an applicable algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1084-1089
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• 2004

This paper describes the improvement of web cache server by scoping in replacement algorithm of data which are collected from the clients. We have found that each replacement algorithm is suitable for each type of data in the web pages. Therefore, we introduce the mechanism to select the replacement algorithm depending on the size of data called the Replacement Algorithm Selection Mechanism (RASM). RASM allows the web cache server to have the suitable replacement algorithm for each type of data. As the result, the byte hit ratio of web cache server can be increased and the congestion in the network can be alleviated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.65-65
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• 2000

For Video on Demand(VoD) servers, a design of an efficient scheduler is important to the support a large number of clients having various playback speeds and receiving rates. In this paper, we propose the scheduling algorithm to handle establishing deadlines and selection using the earliest deadline first. To establish deadlines and selections, the period of the receiving rates for each client is located between the over-max receiving rate and the over-playback rate. To avoid video starvation and the buffer overflow of each client, the proposed algorithm guarantees providing the admission control. Because of establishing deadlines and selection, period of each client receiving is between one over max receiving rate and one over play back rate. Using Virtual Buffer in server, scheduling load is reduced. The efficiency of the proposed algorithm is verified using a Petri Net_Based simulation tool, Exspect.

• 한국인터넷방송통신학회논문지
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• 제11권5호
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• pp.217-228
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• 2011

중앙집중형 CDN에서는 사용자의 요청에 대해 서비스 망의 노드가 가용한 소스 노드들 중에서 하나를 선택하여 사용자에게 알려준다. 본 논문에서는, 사용자 요청이 오버레이 망에서 DHT(distributed hash table)를 이용한 P2P 알고리듬에 의해 컨텐츠 소스들에게 전달되고, 이 소스들로부터 받은 응답들을 바탕으로 사용자가 실시간 사용자 중심의 선택을 하는 분산형 CDN 구조 및 동작 알고리듬을 제안한다. 이를 위해 분산형 CDN 구조와 함께 수정된 Pastry 방식을 제안하고, 이를 이용한 컨텐츠의 등록, 검색, 선택을 방안을 기술 하였다. 제안한 CDN 구조는 분산형 구조가 갖는 부하 분산, 트래픽 분산, 확장성, 자가 구성 및 자가 회복에 의한 장애에 대한 관용성 등의 장점도 가진다. 다양한 시뮬레이션을 통하여 제안한 방안의 유효성을 보였으며, 제안한 방안의 여러 가지 변형 방안에 대한 성능을 비교, 검토하였다.

• 전기전자학회논문지
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• 제22권3호
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• pp.570-577
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• 2018

With the increasing number of network nodes, traditional client/server node selection mechanisms are under tremendous pressure. In order to select efficient cooperative nodes in a highly dynamic P2P network topology, this article uses greedy algorithm to translate the overall optimization into multiple local optimal problems, and to quickly select service nodes. Therefore, the service node with the largest comprehensive capacity is selected to reduce the transmission delay and improve the throughput of the service node. The final simulation results show that the node selection strategy based on greedy algorithm can effectively improve the overall performance of P2P streaming media system.

• 정보처리학회논문지A
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• 제11A권6호
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• pp.413-418
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• 2004

컴퓨터 하드웨어의 크기가 작아지고 성능이 향상되어 노트북, PDA 등 개인용 휴대 컴퓨터의 사용이 늘어남에 따라 물리적 위치에 관계없이 어느 곳에서나 원하는 정보를 손쉽게 접근하고자 하는 사용자들의 요구는 유비쿼터스 컴퓨팅 기술을 탄생시켰다. 본 연구에서는 기존의 유선환경에서 빠르고 안정적인 서비스를 위하여 사용한 콘텐츠 분산 네트워크 기술을 이동 환경에 적용하여 이동 호스트가 적절한 콘텐츠 서버를 선택하여 서비스 받음으로써 이동 중에도 단절 없이 콘텐츠를 서비스 받을 수 있는 방안을 제시하였다 이동 환경에 적합한 서버 선택 알고리즘을 제안함으로써 보다 효율적인 전송이 가능함을 실험을 통해 보였으며 이러한 연구는 유비쿼터스 컴퓨팅의 실현에 기여할 수 있을 것이다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 춘계학술발표대회
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• pp.118-120
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• 2015

현재, 급격한 IT 기술 발전의 산물인 스마트 디바이스에서 발생되는 데이터의 양이 기하급수적으로 증가함에 따라 효율적으로 저장하기 위한 다양한 연구 및 기술 개발이 진행되고 있다. 이 중에 Desktop Storage Virtualization(DSV)은 비가용 데스크톱 스토리지 자원을 하나의 통합된 스토리지로 만들고 이를 스토리지 사용자 니즈에 따라 스토리지를 제공한다. DSV는 분산된 데스크탑의 비가용 자원을 통합함에 따라 신뢰성이 매우 중요시된다. 그러나 DSV 환경에서 산발적 서버다운 및 기타 장애시 대응체계가 미흡하다. 본 논문에서는 이러한 상황을 고려한 Server Selection Algorithm(SSA)를 제시한다. SSA는 서버 장애 발생시 대체 서버를 분산된 데스크탑이 적응적 인지 및 서버를 변경함으로써 고가용성을 제공한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권3호
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• pp.921-940
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• 2015

In this paper, we investigate the multi-resource allocation problem, a unique feature of which is that the multiple resources can compensate each other while achieving the desired system performance. In particular, power and time allocations are jointly optimized with the target of energy efficiency under the resource-limited constraints. Different from previous studies on the power-time tradeoff, we consider a multi-server case where the concurrent serving users are quantitatively restricted. Therefore user selection is investigated accompanying the resource allocation, making the power-time tradeoff occur not only between the users in the same server but also in different servers. The complex multivariate optimization problem can be modeled as a variant of 2-Dimension Bin Packing Problem (V2D-BPP), which is a joint non-linear and integer programming problem. Though we use state decomposition model to transform it into a convex optimization problem, the variables are still coupled. Therefore, we propose an Iterative Dual Optimization (IDO) algorithm to obtain its optimal solution. Simulations show that the joint multi-resource allocation algorithm outperforms two existing non-joint algorithms from the perspective of energy efficiency.

• Journal of Communications and Networks
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• 제17권3호
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• pp.306-320
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• 2015

Due to an explosive growth in services running in different datacenters, there is need for service selection and routing to deliver user requests to the best service instance. In current solutions, it is generally the client that must first select a datacenter to forward the request to before an internal load-balancer of the selected datacenter can select the optimal instance. An optimal selection requires knowledge of both network and server characteristics, making clients less suitable to make this decision. Information-Centric Networking (ICN) research solved a similar selection problem for static data retrieval by integrating content delivery as a native network feature. We address the selection problem for services by extending the ICN-principles for services. In this paper we present Queue and Latency, a network-driven service selection algorithm which maps user demand to service instances, taking into account both network and server metrics. To reduce the size of service router forwarding tables, we present a statistical method to approximate an optimal load distribution with minimized router state required. Simulation results show that our statistical routing approach approximates the average system response time of source-based routing with minimized state in forwarding tables.