• The Journal of Korean Association of Computer Education
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• v.14 no.2
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• pp.75-82
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• 2011

Cloud computing is a computing paradigm that provides user's services anywhere, anytime in a virtualized form composed of large computing resources based on internet or intranet. In Cloud computing environments, reliability of system is impact factor because many applications handle large data. In this paper, we propose an adaptive scheduling technique based on reliability with fault tolerance that manages resource variable and resolves problems(change of user's requirement, failure occurrence) in Cloud computing environment. Futhermore, we verified the performance of the proposed scheduling through experiments in CloudSim Simulation.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2320-2331
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• 1999

Over the Internet, in order to utilize a collection of idle computers as a parallel computing platform, we propose a new scheme called GICE(Global Internet Computing Environment). GICE is motivated to obtain high programmability, efficient support for heterogeneous computing resources, system scalability, and finally high performance. The programming model of GICE is based on a single address space. GICE is featured with a Java based programming environment, a dynamic resource management scheme, and efficient parallel task scheduling and execution mechanisms. Based on a prototype implementation of GICE, we address the concept, feasibility, complexity and performance of Internet computing.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.50-64
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• 2012

Quality of Service (QoS) and fairness considerations are undoubtedly essential parameters that need to be considered in the design of next generation scheduling algorithms. This work presents a novel game theoretic cross-layer design that offers optimal allocation of wireless resources to heterogeneous services in Orthogonal Frequency Division Multiple Access (OFDMA) networks. The method is based on the Axioms of the Symmetric Nash Bargaining Solution (S-NBS) concept used in cooperative game theory that provides Pareto optimality and symmetrically fair resource distribution. The proposed strategies are determined via convex optimization based on a new solution methodology and by the transformation of the subcarrier indexes by means of time-sharing. Simulation comparisons to relevant schemes in the literature show that the proposed design can be successfully employed to typify ideal resource allocation for next-generation broadband wireless systems by providing enhanced performance in terms of queuing delay, fairness provisions, QoS support, and power consumption, as well as a comparable total throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1825-1842
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• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.3
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• pp.336-343
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• 1999

본 논문은 지능형 정보 제공 시스템(IP : Intelligent Peripheral)의 주요 소프트웨어 블록 중 하나인 자원 서비스 제어부의 구현 방법을 설명한 것이다. 본 연구의 자원 서비스 제어부는 ITU-T INCS-1에 정의된 특수자원 기능실체(SRF : Specialized Resource Function)의 상태모델을 실현시킨 소프트웨어 블록으로서 IP 하드웨어 구성요소의 하나인 특수자원교환기(SRS : Specialized Resource Switch) 의 CROS(Concurrent Realtime perating System)상에서 CHILL(CCITT High Level Programming Language)로 구현되었으며, 지능망서비스제어시스템(SCP : Service Control Point)이 보낸 지능망 응용프로토콜(INAP : Intelligent Network Application Protocol)오퍼레이션을 분석하여 IP가 보유한 자원 구동에 필요한 모든 절차를 제어한다. 또한 동시에 수신된 INAP오퍼레이션들에 대한 순서제어기능, 통계데이타 제공기능, 사용자 상호작용 종료 기능등을 제공한다. 제안된 구현기술은 자원서비스 제어부가 실제 자원을 동작시키는 IP 하드웨어 구성요소인 특수자원유닛(SRU : Specialized Resource Unit)을 클라이언트/서버형태로 유지하여 이들 자원의 상태를 관리함으로써 IP의 확장성을 보잔하여, 교환기 실시간 데이터베이스를 이용하여 IP가 생성하는 수만여개의 메시지를 효율적으로 관리할 수있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.239-240
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• 2012

When users access to use the computing resources in the cloud, they expect specific quality of service (QoS) which should be guaranteed by the service provider. Meanwhile, the service provider should adopt proper schemes to enhance the resource utilization. In this thesis, we propose the MapChem-Broker which aims to satisfy users' QoS requirements as well as enhance the resource utilization by controlling the provision of VM resources in the cloud. On the experimental cloud testbed, we compare the proposed scheme with an existing one for VM resource provisioning. Results show that the proposed scheme outperforms the existing one.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.45-47
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• 2022

Mobile edge computing (MEC), which enables mobile terminals to offload computational tasks to a server located at the user's edge, is considered an effective way to reduce the heavy computational burden and achieve efficient computational offloading. In this paper, we study a multi-user MEC system in which multiple user devices (UEs) can offload computation to the MEC server via a wireless channel. To solve the resource allocation and task offloading problem, we take the total cost of latency and energy consumption of all UEs as our optimization objective. To minimize the total cost of the considered MEC system, we propose an DRL-based method to solve the resource allocation problem in wireless MEC. Specifically, we propose a Asynchronous Advantage Actor-Critic (A3C)-based scheme. Asynchronous Advantage Actor-Critic (A3C) is applied to this framework and compared with DQN, and Double Q-Learning simulation results show that this scheme significantly reduces the total cost compared to other resource allocation schemes

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1041-1051
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• 2012

Attack on Cloud Computing, an intensive service solution using network infrastructure recently released, generates service breakdown or intrusive incidents incapacitating developmental platforms, web-based software, or resource services. Therefore, it is needed to conduct research on security for the operational information of three kinds of services (3S': laaS, PaaS, SaaS) supported by the Cloud Computing system and also generated data from the illegal attack on service blocking. This paper aims to build a system providing optimal services as a 4-stage defensive method through the test on the attack and defense of Cloud Computing services. It is a defense policy that conducts 4-stage, orderly and phased access control as follows: controlling the initial access to the network, controlling virtualization services, classifying services for support, and selecting multiple routes. By dispersing the attacks and also monitoring and analyzing to control the access by stage, this study performs defense policy realization and analysis and tests defenses by the types of attack. The research findings will be provided as practical foundational data to realize Cloud Computing service-based defense policy.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• Journal of KIISE:Information Networking
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• v.34 no.5
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• pp.379-388
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• 2007

With proliferation of computer and wireless network technology, it is common to access Internet through wireless network using mobile device. Ratio of using streaming media out of many applications through Internet is increasing not only in wired network but also in wireless network. Streaming media is much bigger than other contents and requires more network bandwidth and more computing resources. However mobile devices hate relatively poor computing resource and low network bandwidth. If media streaming service is provided for mobile devices without any consideration about network bandwidth and computing power, it is hard for the client to get high qualify service. Since mobile device is supported with very limited energy from the battery, media streaming should be adjusted to varying energy state of mobile device in realtime to ensure complete playback of streaming media. In this paper, we propose DFRC to provide high qualify service to mobile client through wireless network by controlling the number of frames transmitted to client based on computing resource and energy state of mobile device.