• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3090-3102
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• 2015

The accuracy of an augmented reality (AR) application is highly dependent on the resolution of the object's image and the device's computational processing capability. Naturally, a mobile smart device equipped with a high-resolution camera becomes the best platform for portable AR services. AR applications require significant energy consumption and very fast response time, which are big burdens to the smart device. However, there are very few ways to overcome these burdens. Computation offloading via mobile cloud computing has the potential to provide energy savings and enhance the performance of applications executed on smart devices. Therefore, in this paper, adaptive mobile computation offloading of mobile AR applications is considered in order to determine optimal offloading points that satisfy the required quality of experience (QoE) while consuming minimum energy of the smart device. AR feature extraction based on SURF algorithm is partitioned into sub-stages in order to determine the optimal AR cloud computational offloading point based on conditions of the smart device, wireless and wired networks, and AR service cloud servers. Tradeoffs in energy savings and processing time are explored also taking network congestion and server load conditions into account.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.79-85
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• 2017

This paper proposes the use of mobile ad-hoc cloud for reducing the process time of panoramic image generation in mobile smart devices. In order to effectively assign tasks relevant to panoramic image generation to the mobile ad-hoc cloud, a method for image acquisition and sorting and an algorithm for task distribution and offloading decision making are proposed. The proposed methods are applied to Android OS based smart devices, and their effects on panoramic image generation are analyzed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.145-164
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• 2023

Cloud computing offers a platform that is both adaptable and scalable, making it ideal for outsourcing data for sharing. Various organizations outsource their data on cloud storage servers for availing management and sharing services. When the organizations outsource the data, they lose direct control on the data. This raises the privacy and security concerns. Cryptographic encryption methods can secure the data from the intruders as well as cloud service providers. Data owners may also specify access control policies such that only the users, who satisfy the policies, can access the data. Attribute based access control techniques are more suitable for the cloud environment as they cover large number of users coming from various domains. Multi-authority attribute-based encryption (MA-ABE) technique is one of the propitious attribute based access control technique, which allows data owner to enforce access policies on encrypted data. The main aim of this paper is to comprehensively survey various state-of-the-art MA-ABE schemes to explore different features such as attribute and key management techniques, access policy structure and its expressiveness, revocation of access rights, policy updating techniques, privacy preservation techniques, fast decryption and computation outsourcing, proxy re-encryption etc. Moreover, the paper presents feature-wise comparison of all the pertinent schemes in the field. Finally, some research challenges and directions are summarized that need to be addressed in near future.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.22-29
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• 2022

Recently, with the development of mobile computing power, mobile-based VR and AR services are being developed. Due to network performance and computing power constraints, VR and AR services using large-capacity 3D content have limitations. A study on an efficient 3D content load method for a mobile device is required. The conventional method downloads all 3D content used for AR services at the same time. In this paper, we propose an active 3D content load according to the user's track. The proposed method is a partitioned 3D object load. Edge servers were installed for each area and connected through the MESH network. Partitioned load the required 3D object in the area referring to the user's location. The location is identified through the edge server information of the connected AP. The performance of the proposed method and the conventional method was compared. As a result of the comparison, the proposed method showed a stable Mobile AR Service. The results of this study, it is expected to contribute to the activation of edge server-based AR mobile services.

• 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 Korea Contents Association
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• v.19 no.4
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• pp.79-90
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• 2019

As an increasing number of cloud service providers begin to provide cloud computing services, they form a competitive market to compete for users. Due to different resource configurations and service workloads, users may observe different response times for their service requests and experience different levels of service quality. To compete for cloud users, it is crucial for each cloud service provider to determine an optimal price that best corresponds to their service qualities while also guaranteeing maximum profit. To achieve this goal, the underlying rationale and characteristics in this competitive market must be clarified. In this paper, we analyze price competition in the multimedia cloud service market with two service providers. We characterize the nature of non-cooperative games in a duopoly multimedia cloud service market with the goal of capturing how each cloud service provider determines its optimal price to compete with the other and maximize its own profit. To do this, we introduce a queueing model to characterize the service process in a multimedia cloud data center. Based on performance measures of the proposed queueing model, we suggest a price competition problem in a duopoly multimedia cloud service market. By solving this problem, we can obtain the optimal equilibrium prices.

• Informatization Policy
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• v.26 no.3
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• pp.90-106
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• 2019

The cloud services market is growing rapidly from the on-premises environment to the cloud computing environment and the domestic cloud software market in Korea is expected to grow at a CAGR of around 15%. In Korea, research teams are providing open cloud platforms using open source software under the government taking the initiative, which intends to enhance the reliability and functionality of open cloud platforms, provide users with a world-class open cloud platform-based and developer-friendly environment that is managed on heterogeneous cloud infrastructure and supported by full-lifecycle management of application software. In this paper, we propose a method to utilize CaaS in the open cloud platform, through incorporating the platform with the container orchestration platform. Finally, by providing users with the application runtime and container runtime, it presents how the two platforms can coexist and cooperate in the same ecosystem.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.617-627
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• 2016

Many kinds of OGC-based web standards have been utilized in the lots of geo-spatial application fields for sharing and interoperable processing of large volume of data sets containing satellite images. As well, the number of cloud-based application services by on-demand processing of virtual machines is increasing. However, remote sensing applications using these two huge trends are globally on the initial stage. This study presents a practical linkage case with both aspects of OGC-based standard and cloud computing. Performance test is performed with the implementation result for cloud detection processing. Test objects are WPS 2.0 and two types of geo-based service environment such as web server in a single core and multiple virtual servers implemented on OpenStack cloud computing environment. Performance test unit by JMeter is five requests of GetCapabilities, DescribeProcess, Execute, GetStatus, GetResult in WPS 2.0. As the results, the performance measurement time in a cloud-based environment is faster than that of single server. It is expected that expansion of processing algorithms by WPS 2.0 and virtual processing is possible to target-oriented applications in the practical level.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.11
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• pp.319-328
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• 2023

Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.17-23
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• 2019

IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardwares. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy quickly by estimating costs for cloud infrastructures as soon as possible. However, swift response is not possible due to that cloud service providers provide a dozen or so hours delayed billing information. Our work proposes a realtime IaaS cost estimation model based on usages monitored by virtual machine instance. We operate PC laboratory service on a public cloud during full semester to validate our suggested model. From that experiment, an averaged disparity between estimation and actual cost is less than 5.2%.