• The KIPS Transactions:PartC
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• v.15C no.2
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• pp.103-110
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• 2008

Internet telephone uses VoIP as its communication protocol, where it provides various additional services with inexpensive fare when the terminal is connected to the Internet. The existing auto provisioning systems that manage Internet telephone terminals are targeting large size VoIP service providers or enterprises, and has few consideration on the convenience of management for small size environments. The difficult installation and management procedures of the current auto provisioning systems prevents Internet telephone system from getting popular. Easy installation and management system is needed in order to spread out Internet telephone system. In this paper, we design and implement the auto provisioning system that provides easy installation and management services in small size environments such as SOHO environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5271-5289
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• 2016

On large-scale data analysis platforms deployed on cloud infrastructures over the Internet, the instability of the data transfer time and the dynamics of the processing rate require a more sophisticated data distribution scheme which maximizes parallel efficiency by achieving the balanced load among participated computing elements and by eliminating the idle time of each computing element. In particular, under the constraints that have the real-time and limited data buffer (in-memory storage) are given, it needs more controllable mechanism to prevent both the overflow and the underflow of the finite buffer. In this paper, we propose an auto regulated data provisioning model based on receiver-driven data pull model. On this model, we provide a synchronized data replenishment mechanism that implicitly avoids the data buffer overflow as well as explicitly regulates the data buffer underflow by adequately adjusting the buffer resilience. To estimate the optimal size of buffer resilience, we exploits an adaptive buffer resilience control scheme that minimizes both data buffer space and idle time of the processing elements based on directly measured sample path analysis. The simulation results show that the proposed scheme provides allowable approximation compared to the numerical results. Also, it is suitably efficient to apply for such a dynamic environment that cannot postulate the stochastic characteristic for the data transfer time, the data processing rate, or even an environment where the fluctuation of the both is presented.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.132-135
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• 2007

논문은 LG 데이콤의 TPS 서비스에서 사용되는 여러 단말의 초기 설치의 편의성을 최대한 보장하기 위한 자동 프로비저닝 시스템에 대한 연구이다. 이를 위해서 요구되는 단말기의 식별자와 암호화를 처리하기 위한 자동 프로비저닝 시스템의 수행 절차를 제안한다. 기본 구성은 홈게이트웨이를 이용한 홈네트워크를 구성하고 있다. 이를 기반으로 하여 IPTV 셋탑, WiFI 폰, PC 를 동시에 사용하기 위해서는 자동 프로비저닝 시스템에서 여러 단말기로 네트워크 접속에 필요한 정보(접속할 시스템의 주소(IP), 포트 및 환경 파일)를 전송하거나, 단말기가 직접 다운받을 수 있도록 한다. 이를 제공하는 시스템을 TPS 자동 프로비저닝 시스템이라 명하며, 이는 가입자의 개입없이 홈네트워크 환경과 멀티미어어 서비스 환경을 자동으로 설치함으로써 사용자의 편이성을 극대화하게 된다. 본 논문은 TPS 서비스와 디지털 홈 서비스의 근간이 되는 프로비저닝 플랫폼의 기술적 가능성을 검증함으로써 향후 관련 단말기 개발 및 개방형 서비스를 제공하기 위한 기초자료로 활용되고자 한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1A
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• pp.30-37
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• 2006

In this paper, we propose a QoS-aware efficient bandwidth re-provisioning scheme in a next generation wireless packet transport network. At the transport network layer, it classifies the traffic of the radio network layer into a real time class and a non-real time class. Using an auto-regressive time-series model and a given packet loss probability, our scheme predicts the needed bandwidth of the non-real time class at every re-provisioning interval. Our scheme increases the system capacity by releasing the unutilized bandwidth of the non-real time traffic class for the real-time traffic class while insuring a controllable upper bound on the packet loss probability of a non-real time traffic class. Through empirical evaluations using the real Internet traffic traces, our scheme is validated that it can increase the bandwidth efficiency while guaranteeing the quality of service requirements of the non-real time traffic class.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.45-47
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• 2017

하둡은 대표적인 빅데이터 처리 프레임워크로 널리 사용되고 있지만 하둡 어플리케이션은 고성능컴퓨팅 환경에서 하둡 분산파일시스템이 아닌 러스터 병렬 파일시스템 위에서도 수행될 수 있다. 그러나 이를 위해서 추가적으로 러스터 병렬파일시스템을 구축하고 관리하는 것은 시간 소모적인 업무가 될 수 있다. 본 연구는 러스터 병렬파일시스템의 오토 프로비저닝을 위한 암바리 서비스의 설계 방안에 대해서 제안한다. 암바리는 하둡 클러스터의 프로비저닝, 관리, 모니터링을 위한 운영 관리 프레임워크이며 운영자의 필요에 따라서 확장할 수 있는 서비스 프레임워크를 제공한다. 본 연구에서는 암바리를 통해서 러스터 병렬파일시스템을 오토 프로비저닝하고 관리하기 위한 확장 서비스를 설계하였으며 서비스를 위한 컴포넌트와 각 컴포넌트별 중요한 기능 사항에 대해서 논하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1625-1627
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• 2015

클라우드 컴퓨팅의 가상화된 인프라 기반 위에서 IT 자원 및 애플리케이션 서비스를 관리하고 배포하는 작업이 클라우드 프로비저닝이다. 본 논문에서는 IT 자원을 할당함에 있어 전문적인 지식을 가진 관리자의 개입을 최소화하기 위해 일련의 자원 할당 작업을 자동화하였다. 자동화된 자원 프로비저닝을 통해 관리자는 특정 전문 지식 없이도 자원 할당 및 배포가 가능해져 이용자의 요구를 보다 신속하게 처리할 수 있게 되었다.

• 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.