• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.1047-1059
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• 2022

With the development of cloud computing technology, container technology that provides services based on a virtual environment is also developing. Container orchestration technology is a key element for cloud services, and it has become an important core technology for building, deploying, and testing large-scale containers with automation. Originally designed by Google and now managed by the Linux Foundation, Kubernetes is one of the container orchestrations and has become the de facto standard. However, despite the increasing use of Kubernetes in container orchestration, the number of incidents due to security vulnerabilities is also increasing. Therefore, in this paper, we study the vulnerabilities of Kubernetes and propose a security policy that can consider security from the initial development or design stage through threat analysis. In particular, we intend to present a specific security guide by classifying security threats by applying STRIDE threat modeling.

• Information Systems Review
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• v.22 no.2
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• pp.1-24
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• 2020

Cloud computing technology is expanding its services to individual consumers through storage and applications. This study aims to compare the predisposing factors that affect the perceived value and the intention to use between users who have used or experienced services and those who have never experienced services from the perspective of benefit and sacrifice based on the value-based acceptance model. The results showed that the sacrifice factor (perceived cost) had a significant effect on perceived value and perceived value had a significant effect on intention to use, but showed a difference in perceived benefit. Perceived usefulness, ubiquity, and network effects had significant impact for experienced users' perceived value, but for inexperienced users, ubiquity did not have significant impact. In addition, usefulness was the most significant factor for experienced users while network effect was the same for inexperienced users. The results of this study suggest that consumers' intention to use personal cloud service is evaluated as a benefit and sacrifice point and a new attempt to re-examine the role of previous experience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1545-1559
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• 2023

In the cloud environment, microservices are implemented through Kubernetes, and these services can be expanded or reduced through the autoscaling function under Kubernetes, depending on the service request or resource usage. However, the increase in the number of nodes or distributed microservices in Kubernetes and the unpredictable autoscaling function make it very difficult for system administrators to conduct operations. Artificial Intelligence for IT Operations (AIOps) supports resource management for cloud services through AI and has attracted attention as a solution to these problems. For example, after the AI model learns the metric or log data collected in the microservice units, failures can be inferred by predicting the resources in future data. However, it is difficult to construct data sets for generating learning models because many microservices used for autoscaling generate different metrics or logs in the same timestamp. In this study, we propose a cloud data refining module and structure that collects metric or log data in a microservice environment implemented by Kubernetes; and arranges it into computing resources corresponding to each service so that AI models can learn and analogize service-specific failures. We obtained Kubernetes-based AIOps learning data through this module, and after learning the built dataset through the AI model, we verified the prediction result through the differences between the obtained and actual data.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.1-9
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• 2017

Smart Cities intelligently manage numerous infrastructures, including Smart-City IoT devices, and provide a variety of smart-city applications to citizen. In order to provide various information needed for smart-city applications, Smart Cities require a function to intelligently process large-scale streamed big data that are constantly generated from a large number of IoT devices. To provide smart services in Smart-City, the Smart-City Consortium uses stream reasoning. Our stream reasoning requires real-time processing of big data. However, there are limitations associated with real-time processing of large-scale streamed big data in Smart Cities. In this paper, we introduce one of our researches on cloud computing based real-time distributed-parallel-processing to be used in stream-reasoning of IoT big data in Smart Cities. The Smart-City Consortium introduced its previously developed smart-city middleware. In the research for this paper, we made cloud computing based real-time distributed-parallel-processing available in the cloud computing platform of the smart-city middleware developed in the previous research, so that we can perform real-time distributed-parallel-processing with them. This paper introduces a real-time distributed-parallel-processing method and system for stream reasoning with IoT big data transmitted from various sensors of Smart Cities and evaluate the performance of real-time distributed-parallel-processing of the system where the method is implemented.

• ETRI Journal
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• v.35 no.2
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• pp.348-351
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• 2013

Cloud computing has recently become a significant technology trend in the IT field. Among the related technologies, desktop virtualization has been applied to various commercial applications since it provides many advantages, such as lower maintenance and operation costs and higher utilization. However, the existing solutions offer a very limited performance for 3D graphics applications. Therefore, we propose a novel method in which rendering commands are not executed at the host server but rather are delivered to the client through the network and are executed by the client's graphics device. This method prominently reduces server overhead and makes it possible to provide a stable service at low cost. The results of various experiments prove that the proposed method outperforms all existing solutions.

• Annual Conference of KIPS
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• 2013.05a
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• pp.179-182
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• 2013

We develop Framework architecture of Online Shopping Services based on M2M and IoT for Handheld Devices in Cloud Computing. MapReduce model will be used as a method to simplify large scale data processing when user search for purchasing products online which provide efficient, and fast respond time. Therefore, providing user with a enhanced Quality of Experience (QoE) as well as Quality of Service (QoS) when purchasing/searching products Online from big data.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.67-74
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• 2022

One type of network security breach is the availability breach, which deprives legitimate users of their right to access services. The Denial of Service (DoS) attack is one way to have this breach, whereas using the Intrusion Detection System (IDS) is the trending way to detect a DoS attack. However, building IDS has two challenges: reducing the false alert and picking up the right dataset to train the IDS model. The survey concluded, in the end, that using a real dataset such as MAWILab or some tools like ID2T that give the researcher the ability to create a custom dataset may enhance the IDS model to handle the network threats, including DoS attacks. In addition to minimizing the rate of the false alert.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.261-268
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• 2021

Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.77-83
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• 2010

Recently, IT-based environment is changing rapidly as changing in web services platform, evolution of cloud computing environments and expanding the base of a smart market. Accordingly, monitoring development of environment is changing quickly. So a customizable SaaS-based monitoring tool is required to provide monitoring services. It has to support a variety of environmental monitoring and a resource managers with requested information, and by an enhanced monitoring framework in clouding environment of management system. In this paper, the 3D viewer for the management of sensor node management system was designed and built. Through the 3D viewer by enhancing the accessibility and visibility, the sensor network will allow resources to be used efficiently.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.255-261
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• 2014

This paper intends to suggest methods to design and implement a jQuery mobile based system in a future mobile webapp environment through a study on an N-Screen application in a mobile webapp. N-Screen is one of the representative services of cloud computing. It is promoted by the need of users to require universal functions for all devices. However, this situation is in conflict with the users' need to have the same experience and N-Screen cannot deal with these disparate services. Thus, this study intends to suggest a system analysis, structure of design, and a framework by implementing the N-Screen based movie reservation system in the jQuery mobile environment.