• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.217-228
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• 2011

In centralize CDN systems, the content server selection is performed by service node for every user request, and the selected node is notified to the user. In this paper, we present distributed CDN architecture and algorithm in which the request from a user is delivered to the content source by a P2P algorithm utilizing DHT(distributed hash table) through the overlay network and the user selects one of the source nodes based on real-time user-centric criteria. For this purpose, we propose a modified Pastry algorithm for contents registration, search and selection, in addition to the distributed architecture. The proposed architecture has the advantages of load balancing, traffic balancing, scalability, fault-tolerance due to the self-configuration, self-healing attributes of distributed architecture. Various simulation shows the feasibility of the proposed architecture and algorithm, and the performance is compared and discussed for the variations of the proposed scheme.

• Genomics & Informatics
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• v.4 no.1
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• pp.45-47
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• 2006

D2GSNP is a web-based server for the selection of single nucleotide polymorph isms (SNPs) within genes related to human diseases. The D2GSNP is based on a relational database created by downloading and parsing OMIM, GAD, and dbSNP, and merging it with positional information of UCSC Golden Path. Totally our server provides 5,142 and 1,932 non-redundant disease genes from OMIM and GAD, respectively. With the D2GSNP web interface, users can select SNPs within genes responding to certain diseases and get their flanking sequences for further genotyping experiments such as association studies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.327-333
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• 2013

In this paper, we propose a QoS information collection method at the information server in maritime networks with multi-network interfaces, and a route selection scheme based of the measured predictive QoS information comparing with parameters requested from a mobile node in a ship entering into a harbor from near-shore area. By changing network conditions and applying various application bandwidths, we check the operation of our proposed scheme and measure its performance of the original and proposed schemes in the viewpoints of the received packet traffic and end-to-end delays.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.283-290
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• 2004

With the development of Web technologies, the demand for multimedia contents and network bandwidth is increasing explosively. In this situation, Caching, P2P and CDN are using for fast transmission with low traffic. In this research, we designed and implemented a redirection system for best replica selection where contents are distributed to multiple replicated web servers. This redirection system selects a close and least loaded replica and redirect a client's request to the replica. As a result, this system improved user-perceived performance. It is expected that this redirection system will contribute to the faster and more stable transmission of massive multimedia contents.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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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.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.240-257
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• 2023

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

• Journal of Computing Science and Engineering
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• v.9 no.3
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• pp.142-154
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• 2015

Fault localization techniques help locate faults in source codes by exploiting collected test information and have shown promising results. To precisely locate faults, the techniques require a large number of test cases that sufficiently exercise the executable statements together with the label information of each test case as a failure or a success. However, during the process of software development, developers may not have high-coverage test cases to effectively locate faults. With the test case generation techniques, a large number of test cases without expected outputs can be automatically generated. Whereas the execution results for generated test cases need to be inspected by developers, which brings much manual effort and potentially hampers fault-localization effectiveness. To address this problem, this paper presents a method to select a few test cases from a number of test cases without expected outputs for result inspection, and in the meantime selected test cases can still support effective fault localization. The experimental results show that our approach can significantly reduce the number of test cases that need to be inspected by developers and the effectiveness of fault localization techniques is close to that of whole test cases.

• Journal of Korea Game Society
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• v.17 no.4
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• pp.137-148
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• 2017

Since the power consumption of data centers is large and computer serves take a large portion of it, there have been much research on the power saving of servers in various ways recently. Among the units of severs CPU is one of major power consuming units. In this paper, a method of client-server assignment for minimizing the CPU power consumption of servers in a game server cluster is proposed. We model the client-server assignment problem as an optimization problem, and find a solution to the problem using a simulated annealing-based technique. One of major features of our method is to select a proper operating frequency according to the amount of load on a server. The selection of a lower frequency in case of low load will result in reducing power consumption. To our survey, little research on client-server assignment in consideration of power consumption has been carried out.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.218-223
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• 2021

Pervasive enhancement and required enforcement of the Internet of Things (IoTs) in a distributed massively multiplayer online architecture have effected in massive growth of Big-Data in terms of server over-load. There have been some previous works to overcome the overloading of server works. However, there are lack of considered methods, which is commonly applicable. Therefore, we propose a combing Sparse Auto-Encoder and Load-Balancing, which is ProGReGA for Big-Data of server loads. In the process of Sparse Auto-Encoder, when it comes to selection of the feature-pattern, the less relevant feature-pattern could be eliminated from Big-Data. In relation to Load-Balancing, the alleviated degradation of ProGReGA can take advantage of the less redundant feature-pattern. That means the most relevant of Big-Data representation can work. In the performance evaluation, we can find that the proposed method have become more approachable and stable.