• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.231-244
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• 2022

With the improvement of people's living standards and the development of tourism, tourists have greater freedom in choosing destinations. Therefore, as an indicator of satisfaction with scenic spots, tourist comments are becoming increasingly prominent. This paper aims to compare and analyze the landscape image of the Five Great Mountains in China and provide specific strategies for its development. The online reviews of tourists on the Online Travel Agency (OTA) website about the Five Great Mountains from 2015 to 2018 are collected as research samples. The text analysis method and R language are used to analyze the content of the tourist reviews, while the high-frequency words in the word cloud are used for visual display. In addition, the entropy weight method is used to determine the index weight and tourist satisfaction is evaluated to understand the weaknesses of those scenic spots. The results of the study show that firstly, the tourist satisfaction with the Five Great Mountains is basically consistent with its popularity. Secondly, through weight analysis, tourists pay special attention to the landscape features and environmental health of the scenic area, so that relevant departments should focus on building the landscape characteristics and improving the environmental health of the scenic area. At the same time, the accommodation and service management of the scenic spot cannot be ignored. Finally, according to the analysis results, suggestions are made on how to improve the tourist satisfaction with the Five Great Mountains.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.7-18
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• 2018

Recently, serverless computing is spotlighted. Because it supports the development of application based on micro-service. Micro-service means a small-scale service that can operate independently. Applications with micro-service units have the advantage of enabling individual updates, easy and fast deployment. In addition, it has the advantage of supporting various languages and platforms for each service. Therefore many enterprise are trying to change from monolithic architecture to micro-service based architecture. However, there is a lack of research on methods and baseline for micro-service construction. In this paper, a method is proposed to construct the micro-service unit by analyzing UML design in monolithic application. It also shows the proposed approach can reconstruct monolithic application into micro-service based unit by implementing the constructed micro-services in a real serverless platform environment. In addition, the results of the comparative evaluation with the related studies are presented.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.150-164
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• 2013

Currently it is being gradually focused on the mobile application's processing performance implemented by Javascript and HTML (Hyper Text Markup Language) due to the dissemination of mobile web application supply based on the WAC (Wholesale Application Community). If the application software has a simple functional processing structure, then the problem is benign, however, the load of a browser is getting heavier as the amount of Javascript processing is being increased. There is a limitation on the processing time and capacity of the Javascript in the ordinary mobile browsers which are on the market now. In order to solve those problems, the Web Worker that is not supported from the existing Javascript technology is now provided by the HTML 5 to implement the multi thread. The Web Worker provides a mechanism that process a part from the single thread through a separate one. However, it can not guarantee the computing ability as a native application on the mobile and is not enough as a solution for improving the fundamental processing speed. The Cyclostorm overcomes the limitation of resources as a mobile client and guarantees the performance as a native application by providing high computing service and ascripting the Javascript process on the mobile to the computer server on the cloud. From the performance evaluation experiment, the Cyclostorm shows a maximally 6 times faster computing speed than in the existing mobile browser's Javascript and 3 to 6 times faster than in Web Worker of the HTML 5. In addition, the usage of memory is measured less than the existing method since the server's memory has been used. In this paper, the Cyclostorm is introduced as one of the mobile cloud computing services to conquer the limitation of the WAC based mobile browsers and to improve the existing web application's performances.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.97-103
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• 2020

Linux Cgroups takes a fundamental role for sharing system resources among multiple containers on container-based cloud computing environment. Especially for I/O resource, Linux Cgroups supports a mechanism for sharing I/O bandwidth in proportion to I/O weight. However, the current mechanism of Linux Cgroups using BFQ I/O scheduler seriously degrades the I/O performance with high bandwidth storage device such as NVMe SSDs. In this paper, we proposed a new feedback based I/O bandwidth sharing scheme for Linux Cgroups which allocates I/O credits to containers according to I/O weights and adjusts the amount of credits to performance fluctuation of NVMe SSDs. The proposed scheme is implemented on Linux kernel 5.3 and evaluated. The evaluation results show that it can share the I/O bandwidth among multiple containers proportionally to I/O weights while improving I/O performance more than twice as high as the existing scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.558-579
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• 2021

The cloud storage provides flexible data storage services for data owners to remotely outsource their data, and reduces data storage operations and management costs for data owners. These outsourced data bring data security concerns to the data owner due to malicious deletion or corruption by the cloud service provider. Data integrity verification is an important way to check outsourced data integrity. However, the existing data verification schemes only consider the case that a verifier launches multiple data verification challenges, and neglect the verification overhead of multiple data verification challenges launched by multiple verifiers at a similar time. In this case, the duplicate data in multiple challenges are verified repeatedly so that verification resources are consumed in vain. We propose a duplicate data verification algorithm based on multiple verifiers and multiple challenges to reduce the verification overhead. The algorithm dynamically schedules the multiple verifiers' challenges based on verification time and the frequent itemsets of duplicate verification data in challenge sets by applying FP-Growth algorithm, and computes the batch proofs of frequent itemsets. Then the challenges are split into two parts, i.e., duplicate data and unique data according to the results of data extraction. Finally, the proofs of duplicate data and unique data are computed and combined to generate a complete proof of every original challenge. Theoretical analysis and experiment evaluation show that the algorithm reduces the verification cost and ensures the correctness of the data integrity verification by flexible batch data verification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.766-773
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• 2021

This paper presents an implementation result and performance evaluation of pavilion management services that does not only provide real-time status of the pavilion in the forest but also prediction services through machine learning. The developed hardware prototype detects whether the pavilion is occupied using a motion detection sensor and then sends it to a cloud database along with location information, date and time, temperature, and humidity data. The real-time usage status of the collected data is provided to the user's mobile application. The performance evaluation confirms that the average response time from the hardware module to the applications was 1.9 seconds. The accuracy was 99%. In addition, we implemented a pavilion availability prediction service that applied a machine learning-based SVM (Support Vector Model) model to collected data and provided it through mobile and web applications.

• ETRI Journal
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• v.42 no.3
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• pp.446-458
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• 2020

In this study, an efficient scheme for hiding data directly in partially encrypted versions of high efficiency video coding (HEVC) videos is proposed. The content owner uses stream cipher to selectively encrypt some HEVC-CABAC bin strings in a format-compliant manner. Then, the data hider embeds the secret message into the encrypted HEVC videos using the specific coefficient modification technique. Consequently, it can be used in third-party computing environments (more generally, cloud computing). For security and privacy purposes, service providers cannot access the visual content of the host video. As the coefficient is only slightly modified, the quality of the decrypted video is satisfactory. The encrypted and marked bitstreams meet the requirements of format compatibility, and have the same bit rate. At the receiving end, data extraction can be performed in the encrypted domain or decrypted domain that can be adapted to different application scenarios. Several standard video sequences with different resolutions and contents have been used for experimental evaluation.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.87-94
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• 2019

IoT-based services are being released in accordance with the aging population and the demand for well-being pursuit needs. In addition to medical device companies, companies with ideas ranging from global ICT companies to startup companies are accelerating their market entry. The areas where these services are most commonly applied are health/medical, life/safety, city/energy, automotive and transportation. Furthermore, by expanding IoT technology convergence into the area of life care services, it contributes greatly to the development of service models in the public sector. It also provides an important opportunity for IoT-related companies to open up new markets. By addressing the problems of life care services that are still insufficient. We are providing opportunities to pursue the common interests of both users and workers and improve the quality of life. In order to establish IoT-based digital life care services, it is necessary to develop convergence technologies using cloud computing systems, big data analytics, medical information, and smart healthcare infrastructure.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.1
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• pp.60-65
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• 2017

Network virtualization enables us to make efficient use of resources in a physical network by embedding multiple virtual networks in the physical network. In this paper, we develop a prototype of a virtual network embedding system. Our system consists of OpenStack, which is an open source cloud service platform, and shell scripts. Because OpenStack does not provide a quality of service control function, we realize bandwidth reservation for virtual links by making use of the ingress policing function of Open vSwitch, which is a virtual switch used in OpenStack. The shell scripts in our system automatically construct the required virtual network on the physical network using the OpenStack command-line interface, and they reserve bandwidth for virtual links using the Open vSwitch command. Experimental evaluation confirms that our system constructs the requested virtual network and appropriately allocates node and link resources to it.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.179-184
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• 2021

In our study we performed a sentiments analysis from the images. For this purpose, we used 153 images that contain: people, animals, buildings, landscapes, cakes and objects that we divided into two categories: images that suggesting a positive or a negative emotion. In order to classify the images using the two categories, we created two models. The SAI-G model was created with Google's AutoML Vision service. The SAI-C model was created on the Clarifai platform. The data were labeled in a preprocessing stage, and for the SAI-C model we created the concepts POSITIVE (POZITIV) AND NEGATIVE (NEGATIV). In order to evaluate the performances of the two models, we used a series of evaluation metrics such as: Precision, Recall, ROC (Receiver Operating Characteristic) curve, Precision-Recall curve, Confusion Matrix, Accuracy Score and Average precision. Precision and Recall for the SAI-G model is 0.875, at a confidence threshold of 0.5, while for the SAI-C model we obtained much lower scores, respectively Precision = 0.727 and Recall = 0.571 for the same confidence threshold. The results indicate a lower classification performance of the SAI-C model compared to the SAI-G model. The exception is the value of Precision for the POSITIVE concept, which is 1,000.