• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1192-1200
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• 2019

Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.32-39
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• 2017

Recently, usage of mobile cloud services has been increasing. In particular, beyond the constraints of a single cloud computing service, studies on the multi-cloud have been actively pursued. A user must authenticate multiple cloud service providers to use additional cloud services in a multi-cloud. In previous studies, an authentication method using single sign-on (SSO) was not available in all cloud services. Cloud services will not be available when the SSO server is not available due to malicious attacks, because all authentication is done via the SSO server. Additionally, using a broker, there is a vulnerability that can expose authentication information for the service provider to a user who did not sign up. In this paper, we propose a secure user authentication protocol using biometric authentication that does not expose user information when using additional cloud services. The proposed protocol can use a single biometric authentication for multi-cloud services without storing authentication information in each cloud service. In terms of key stability (to ensure stability through the key agreement process and the key area), by disabling various attack methods, such as man-in-the-middle attacks and replay attacks, we provide secure mobile cloud services.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.1
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• pp.81-87
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• 2016

Cloud computing technologies are utilized and merged in various domains. Cloud computing technology-based personal cloud service technologies provide mobility and free access by using user centered storages and smart devices such like smart phones and table PCs. Therefore, we should overcome limits on the storage by solving the capacity problems of devices to provide security services in the personal cloud environments It can be addressable to provide the convenience of various security technologies. However, there are some security threats inherited from existing cloud environments and the possibilities of information leakage when devices are lost or stolen. Therefore, we designed a framework for providing secure cloud services by adding objects, such as user authorization, access tokens, set permissions by key generation, and key management assignments, for user management in personal cloud environments. We analyzed the stability of the proposed framework in terms of irreverent use and abuse, access to insiders, and data loss or leakage. And we evaluated the proposed framework in terms of the security with access control requirements in personal cloud environments.

• Convergence Security Journal
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• v.14 no.7
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• pp.85-90
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• 2014

Cloud computing originated simply to request and execute the desired operation from the network of clouds. It means that an IT resource that provides a service using the Internet technology. It is getting the most attention in today's IT trends. In cloud computing networks, devices and data centers which are composed of the server, storage and application are connected over network. That is, data of computers in different physical locations are integrated using the virtualization technology to provide a service. Therefore cloud computing system is a key information resource, standardized methods and assessment system are required. In this paper, we aims to derive the parameters and information for research of technical standards stability evaluation method associated with various cloud computing equipment.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.276-284
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• 2022

In this paper, we implemented cloud rendering using WebRTC for high-quality AR and VR services. Cloud rendering is an applied technology of cloud computing. It efficiently handles the rendering of large volumes of 3D content. The conventional VR and AR service is a method of downloading 3D content. The download time is delayed as the 3D content capacity increases. Cloud rendering is a streaming method according to the user's point of view. Therefore, stable service is possible regardless of the 3D content capacity. In this paper, we implemented cloud rendering using WebRTC and analyzed its performance. We compared latency of 100MB, 300MB, and 500MB 3D AR content in 100Mbps and 300Mbps internet environments. As a result of the analysis, cloud rendering showed stable latency regardless of data volume. On the other hand, the conventional method showed an increase in latency as the data volume increased. The results of this paper quantitatively evaluate the stability of cloud rendering. This is expected to contribute to high-quality VR and AR services

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.300-307
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• 2016

Cloud computing that provide a elastic computing service is more complex compared to the existing computing systems. Accordingly, it has become increasingly important to maintain the stability and reliability of the computing system. And troubleshooting and real-time monitoring to address these challenges must be performed essentially. For these goals, the handling of the log data is needed, but this task in cloud computing environment may be more difficult compared to the traditional logging system. In addition, there are another challenges in order to have the admissibility of the collected log data in court. In this paper, we design secure logging service that provides the management and reliability of log data in a cloud computing environment and then analyze the proposed system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2305-2309
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• 2016

Cloud Computing Service should support efficiency and stability. United States of America, for example, provides FedRAMP (Federal Risk and Authorization Management Program) accreditation to certify cloud computing service and hence growth of computing service industry is giving benefits of cost reduction and efficiency to companies. However, the use of computing service brings more risk than ever. Because cloud computing holds all the data of multiple companies, problems such as hacking bring out control loss of service and as a result total data of companies can be lost. Unfortunately, cloud computing certification programs do not have any good solutions for this data loss and companies may lose all the important data without any proper data backup. This paper studies such problems in terms of backup problem and provides Data Availability Zone solution for recovery and safe saving of data so that computing service can offer better efficiency and stability.

• Journal of the Korean earth science society
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• v.30 no.1
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• pp.58-68
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• 2009

Three-dimensional distributions of longwave radiation flux for the April-September 1998 period are generated from radiative transfer calculations using the GEWEX Asian Monsoon Experiment (GAME) reanalysis temperature and humidity profiles and International Satellite Cloud Climatology Project (ISCCP) cloudiness as inputs to understand the effect of cloud radiative forcing in the monsoon season. By subtracting the heating of the clear atmosphere from the cloudy radiative heating, cloud-induced atmospheric radiative heating has been obtained. Emphasis is placed on the impact of horizontal gradients of the cloud-generated radiative heating on the Asian monsoon. Cloud-induced heating exhibits its maximum heating areas within the Indian Ocean and minimum heating over the Tibetan Plateau, which establishes the north-south oriented differential heating gradient. Considering that the differential heating is a ultimate source generating the atmospheric circulation, the cloud-induced heating gradient established between the Indian Ocean and the Plateau can enhance the strength of the north-south Hadley-type monsoon circulation. Cooling at cloud top and warming at cloud bottom, which are the vertical distributions of cloud-induced heating, can exert on the monsoon circulation by altering the atmospheric stability.

• Atmosphere
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• v.22 no.4
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• pp.437-447
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• 2012

There is still large uncertainty in estimating aerosol indirect effect despite ever-escalating efforts and virtually exponential increase in published studies concerning aerosol-cloud-precipitation interactions (CAPI). Probably most uncertainty comes from a wide range of observational scales and different platforms inappropriately used, and inherent complex chains of CAPI. Therefore, well-designed field campaigns and data analysis are required to address how to attribute aerosol signals along with clouds and precipitation to the microphysical effects of aerosols. Basically, aerosol influences cloud properties at the microphysical scales, "process scale", but observations are generally made of bulk properties over a various range of temporal and spatial resolutions, "analysis scale" (McComiskey & Feingold, 2012). In the most studies, measures made within the wide range of scales are erroneously treated as equivalent, probably resulting in a large uncertainty in associated with CAPI. Therefore, issues associated with the disparities of the observational resolution particular to CAPI are briefly discussed. In addition, the dependence of CAPI on the cloud environment such as stability and adiabaticity, and observation characteristics with varying situations of CAPI are also addressed together with observation framework optimally designed for the Korean situation. Properly designed and observation-based CAPI studies will likely continue to accumulate new evidences of CAPI, to further help understand its fundamental mechanism, and finally to develop improved parameterization for cloud-resolving models and large scale models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1877-1891
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• 2022

As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.