• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권6호
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• pp.2824-2837
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• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• 융합경영연구
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• 제9권2호
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• pp.1-10
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• 2021

Purpose: In this work, we examine several time series models to predict internet and mobile transaction amount in South Korea, whereas Jeong (2020) has obtained the optimal forecasts for online shopping transaction amount by using time series models. Additionally, optimal forecasts based on the model considered can be calculated and applied to the Corona 19 situation. Research design, data, and methodology: The data are extracted from the online shopping trend survey of the National Statistical Office, and homogeneous and comparable in size based on 46 realizations sampled from January 2007 to October 2020. To achieve the goal of this work, both multiplicative ARIMA model and Holt-Winters Multiplicative seasonality method are taken into account. In addition, goodness-of-fit measures are used as crucial tools of the appropriate construction of forecasting model. Results: All of the optimal forecasts for the next 12 months for two online shopping transactions maintain a pattern in which the slope increases linearly and steadily with a fixed seasonal change that has been subjected to seasonal fluctuations. Conclusions: It can be confirmed that the mobile shopping transactions is much larger than the internet shopping transactions for the increase in trend and seasonality in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권1호
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• pp.96-107
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• 2009

Worm attacks can greatly distort network performance, and countering infections can exact a heavy toll on economic and technical resources. Worm modeling helps us to better understand the spread and propagation of worms through a network, and combining effective types of mitigation techniques helps prevent and mitigate the effects of worm attacks. In this paper, we propose a mathematical model which combines both dynamic quarantine and passive benign worms. This Passive Worm Dynamic Quarantine (PWDQ) model departs from previous models in that infected hosts will be recovered either by passive benign worms or quarantine measure. Computer simulation shows that the performance of our proposed model is significantly better than existing models, in terms of decreasing the number of infectious hosts and reducing the worm propagation speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1796-1816
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• 2020

The health and safety of elderly and disabled patients who cannot live alone is an important issue. Timely detection of sudden events is necessary to protect these people, and anomaly detection in smart homes is an efficient approach to extracting such information. In the real world, there is a causal relationship between an occupant's behaviour and the order in which appliances are used in the home. Bayesian networks are appropriate tools for assessing the probability of an effect due to the occurrence of its causes, and vice versa. This paper defines different subsets of random variables on the basis of sensory data from a smart home, and it presents an anomaly detection system based on various models of Bayesian networks and drawing upon these variables. We examine different models to obtain the best network, one that has higher assessment scores and a smaller size. Experimental evaluations of real datasets show the effectiveness of the proposed method.

• 해양환경안전학회지
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• 제8권1호
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• pp.149-159
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• 2002

Various numerical models that have been developed for marine environments and applied to coastal waters in USA were introduced briefly. Inter alia, with regard to an integrated monitoring and modeling system, the main features and outline of system, the system architecture for data management and representation system, and the incorporation of internet based technology were described. An example of application of an integrated system to coastal waters was also presented. The prospective research works to improve the capabilities and to advance the functionality of an integrated monitoring, modeling and management system were suggested to be the instrumentations for various monitoring parameters, the new development and/or advancement of various numerical models, the relevant internet based technologies. etc..

• 한국멀티미디어학회논문지
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• 제2권2호
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• pp.166-175
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• 1999

인트라넷은 개방된 인터넷 기술과 기업 내 정보 시스템이 결합된 네트워크로써, 그 특성상 기업내 정보를 보호하기 위한 정보보호 기술이 필수적으로 요구된다. 현재까지 인트라넷 외부로부터 정보를 보호하기 위해 접근제어, 데이터 암호화 등을 중심으로 연구되었지만, 인트라넷 내부에서 정보를 보호하고자 하는 연구는 전무한 실정이다 본 논문에서는 현재 구현되고 있는 인트라넷 서비스에 대해 기업 내부에 초점을 맞추어 각종 보안위협들을 살펴본 후 그에 대응하는 보안 모델을 제안하고 각종 프로토콜 및 알고리즘을 컴퓨터 시뮬레이션을 통해 수행한다

• 인터넷정보학회논문지
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• 제5권4호
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• pp.35-42
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• 2004

밴연형 다단상호연결네트웍이 원하는 성능목표치를 만족시킬 수 있는지를 알아보기 위하여 해석적 모델을 제시한다. 입력트래픽은 일반적인 균일트래픽이 아니고 실제상황을 고려하기 위하여 비균일트래픽을 가정하였다. 버퍼는 단일 입력버퍼를 가정하여 개발하였고, 클럭 주기는 일반적이 내클럭주기 개념이 아니라 성능을 향상시키기 위한 소클럭주기 개념을 사용한다. 개발된 모델로부터의 결과와 시뮬레이션으로부터의 결과를 비교하여 구해진 모델의 우수성을 입증한다.

• International Journal of Internet, Broadcasting and Communication
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• 제9권1호
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• pp.1-8
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• 2017

Nowadays many articles describe the controlling models for four rotor flying vehicle. Basic approaches to the problem of these articles are mathematical expressions describing dynamics of the models of the vehicle and PID control for manipulating the object in 3 dimensional space. Design of control systems is usually started by careful consideration of its mathematical model description. We present a detailed mathematical model for a quad rotor. This paper first considers simulation of quadcopter control based on full state feedback technique with linearization in MATLAB environment and shows the results of the simulations. Finally will be shown experimental results of the state feedback control implemented in real model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권3호
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• pp.1113-1135
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• 2018

Existing trust evaluation models for wireless sensor networks can accurately and objectively evaluate trust value of nodes, but the nodes' energy saving problem was ignored. Especially when there are a few malicious nodes in a network, the overall trust value calculation for all nodes would waste lots of energy. Beside that, the network failure caused by nodes death was also not considered. In this paper, we proposed a method for avoiding energy hole which applied trust evaluation models and a trust evaluation method based on information entropy, so as to achieve the purpose of improving nodes utilization. Simulation results show that the proposed method can effectively improve nodes utilization, and it has reasonable detection rate and lower false alert rate compared to other classical methods.