• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.781-786
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• 2009

The cloud computing environment is a new trend of web based application parts. It can be IT business model that is able to easily support learning service and allocate resources through the internet to users. U-learning also is a maximal model with efficiency of the internet based learning. Thus, in this research, we proposed a design of u-learning's teaching and learning model that is applying the internet based learning. Proposal method is to fit u-learning and has 7 steps: Preparing, planning, gathering, learning process, analysis and evaluation, and feedback. We make a cloud u-learning server and cloud LMS to process and manage the service. And We also make a mobile devices meta data to aware the model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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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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• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.57-64
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• 2012

Computing environment combined with development of internet and IT technology is changing to cloud computing environment. In addition, cloud computing is revitalized more because of propagation of LTE and suggestion of N-screen Service. Virtualization is the point technology for suggest IT resource to service form to users in this cloud computing. This technology combines other system physically or divides one system logically and uses resource efficiently. Many users can be provided application and hardware as needed using this. But, lately various attack using weak point of virtualization technology are increasing rapidly. In this study, we analyze type and weak point of virtualization technology, the point of cloud computing. And we study about function and the position which intrusion detection system has to prepare in order to detect and block attack using this.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.658-661
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• 2005

Internet-based client/server architecture of Contents Delivery System suffers from frequent disconnections and security treats caused by dependency of the server or overload. But, We reached the limit to the increase of the server because a contents quality enhance and Internet user explosively increase. Therefore, a P2P based computing methods are used for sloving these issues. In this paper, We implement and design the Education Content Delivery System for cyber education system using idle Computing Power in P2P computing to share computing resources. We implement not only Internet infrastructure but also satellite infrastructure system, and designed to transfer real-time or non real-time contents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.444-461
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• 2016

A power-saving mechanism for smartphone devices is developed by analyzing the features of data that are received from Internet of Things (IoT) sensors devices to optimize the data processing policies. In the proposed GreenIoT architecture for power-saving in IoT, the power saving and feedback mechanism are implemented in the IoT middleware. When the GreenIoT application in the power-saving IoT architecture is launched, IoT devices collect the sensor data and send them to the middleware. After the scanning module in the IoT middleware has received the data, the data are analyzed by a feature evaluation module and a threshold analysis module. Based on the analytical results, the policy decision module processes the data in the device or in the cloud computing environment. The feedback mechanism then records the power consumed and, based on the history of these records, dynamically adjusts the threshold value to increase accuracy. Two smart living applications, a biomedical application and a smart building application, are proposed. Comparisons of data processed in the cloud computing environment show that the power-saving mechanism with IoT architecture reduces the power consumed by these applications by 24% and 9.2%.

• Convergence Security Journal
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• v.5 no.3
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• pp.15-22
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• 2005

The spread of Internet and the appear of Downsizing, SI(System Integration) is chaning centralized computing to distributed computing. Also distributed computing is rapidly changing to Ubiquitous computing escape from hard wire connected network. CORBA(Common Object Request Broker Architecture) is a middleware that used for smoothness communication between application program and operation system in a different environment. However distributed computing environment is not safe from the danger, the attack like virus, worm is too intellectual and variety. In this paper, we design a new DB security model and suggest efficiency of it in Ubiquitous environment base on CSS(CORBA Security Service) that present ed from OMG(Object Management Group).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3892-3912
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• 2021

The recent rapid growth of mobile network traffic places multi-access edge computing in an important position to reduce network load and improve network capacity and service quality. Contrasting with traditional mobile cloud computing, multi-access edge computing includes a base station cooperative cache layer and user cooperative cache layer. Selecting the most appropriate cache content according to actual needs and determining the most appropriate location to optimize the cache performance have emerged as serious issues in multi-access edge computing that must be solved urgently. For this reason, a cache placement algorithm based on comprehensive utility in big data multi-access edge computing (CPBCU) is proposed in this work. Firstly, the cache value generated by cache placement is calculated using the cache capacity, data popularity, and node replacement rate. Secondly, the cache placement problem is then modeled according to the cache value, data object acquisition, and replacement cost. The cache placement model is then transformed into a combinatorial optimization problem and the cache objects are placed on the appropriate data nodes using tabu search algorithm. Finally, to verify the feasibility and effectiveness of the algorithm, a multi-access edge computing experimental environment is built. Experimental results show that CPBCU provides a significant improvement in cache service rate, data response time, and replacement number compared with other cache placement algorithms.

• Journal of Internet Computing and Services
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• v.7 no.6
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• pp.87-103
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• 2006

Advances in computer and network technology provide new computing environment that were only possible with supercomputers before. In order to provide the environment, a distributed runtime system has to be provided, but most of the conventional distributed runtime systems lack in providing dynamic and flexible system reconfiguration depending on workload variance, due to a static architecture of fixed master node and slave working nodes. This paper proposes and implements a new model for distributed job allocation and management which is a distributed runtime system is P2P environment for flexible and dynamic system reconfiguration. The implemented systems enables job program transfer and management, remote compile and execution among cooperative developers based on P2P standard protocol Jxta platform. Since it makes dynamic and flexible system reconfiguration possible, the proposed method has some advantages in that it can collect and utilize idle computing resources immediately at a needed time for distributed job processing. Moreover, the implemented system's effectiveness and performance increase are shown by applying and processing the crawler jobs, in a distributed way, for collecting a large amount of data needed for internet search.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.25-41
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• 2008

In this paper, we describes a Compact Distributed Object Group Framework(CDOGF) for mobile collaboration service in ubiquitous computing. CDOGF support network connections of sensors and devices, management of mobile computing devices, and grouping of objects for mobile collaboration service according to the logical area. For this, we defined methods for detail functions and interface. And, we classified into four interactions of that sensors and a application, the CDOGF and a application, between the components of the CDOGF, the CDOGF on a mobile device and the DOGF on a server. We also defined mobile collaboration environment by analyzing existing technologies. In this environment we used the TMO scheme for interaction and the TMOSM for distributed middleware. Finally, we implemented u-hospital application that applied this environment. This application collects environment and health information by PDAs in wards. Also, It provides the information service for patient management task.