• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1102-1108
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• 2020

Mobile edge computing is a technology that can prepare for a new era of cloud computing and compensate for shortcomings by processing data near the edge of the network where data is generated rather than centralized data processing. It is possible to realize a low-latency/high-speed computing service by locating computing power to the edge and analyzing data, rather than in a data center far from computing and processing data. In this article, we develop a virtual mobile edge computing testbed environment where the cloud and edge nodes divide computing tasks from mobile terminals using the EdgeCloudSim simulator. Performance of offloading techniques for distribution of computing tasks from mobile terminals between the central cloud and mobile edge computing nodes is evaluated and analyzed under the virtual mobile edge computing environment. By providing a virtual mobile edge computing environment and offloading capabilities, we intend to provide prior knowledge to industry engineers for building mobile edge computing nodes that collaborate with the cloud.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.193-196
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• 1997

A mobile computing environment has many difference in character from conventional communication over wired network. These include very presents distributed design system based the mobile agent for mobile computing environment. To integrate design resource, we presented ISA(Integration Service Agent, which allows a designer to build integrated application using distributed resources, and to collaborative by exchanging service. Also we propose ICM(XML based Intelligent Connection Manger) using mobile agent. And suggested new intelligent data and process transfer architecture using ICM to implement an agent based design system in mobile environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.450-470
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• 2023

Traditional cloud computing faces some challenges such as huge energy consumption, network delay and single point of failure. Edge computing is a typical distributed processing platform which includes multiple edge servers closer to the users, thus is more robust and can provide real-time computing services. Although outsourcing data to edge servers can bring great convenience, it also brings serious security threats. In order to provide image retrieval while ensuring users' data privacy, a privacy preserving image retrieval scheme in edge environment is proposed. Considering the distributed characteristics of edge computing environment and the requirement for lightweight computing, we present a privacy-preserving image retrieval scheme in edge computing environment, which two or more "honest but curious" servers retrieve the image quickly and accurately without divulging the image content. Compared with other traditional schemes, the scheme consumes less computing resources and has higher computing efficiency, which is more suitable for resource-constrained edge computing environment. Experimental results show the algorithm has high security, retrieval accuracy and efficiency.

• The Journal of Information Systems
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• v.16 no.2
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• pp.69-91
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• 2007

The mobile computing environment has already matured and mobile services are activated throughout many industries. In the following years, these changes are expected to evolve into a ubiquitous computing environment. In the meantime, whether newly developed information technologies will thrive or diminished depends on user's intention to adopt them. Hence, the necessity of user-centered research considering ubiquitous computing in mobile computing environment is obvious. This study, thus, investigated ubiquitous factors in various literature related to ubiquitous computing and technology acceptance and it proposes a research model of the ubiquitous factors affecting user's intention to use mobile services, in terms of meaning(connectivity, mobility), service(contextual offer), compatibility(compatibility), and infrastructure(privacy, truth). The proposed model is expected to help both researchers and practitioners extend their understanding about the ubiquitous factors in mobile computing environment

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.85-93
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• 2009

GOMS model is a cognitive modeling method of human performance based on Goal, Operators, Methods, Selection rules. GOMS model was originally designed for desktop environment so that it is difficult for GOMS model to be implemented into the mobile environment. In addition, GOMS model would be inaccurate because the original GOMS model was based on serial processing, excluding one of most important human information processing characteristics, parallel processing. Therefore this study was designed to propose a modified GOMS model including mobile computing and parallel processing. In order to encompass mobile environment, an operator of 'look for' was divided into 'visual move to' and 'recognize' whereas 'point to' and 'click' were combined into 'tab.' The results showed that newly introduced operators were necessary to estimate more accurate mobile computing behaviors. In conclusion, modified-GOMS model could predict human performance more accurately than the original GOMS model in the mobile computing environment.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1932-1940
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• 2000

We must solve problems caused by mobile computing environments for supporting efficient mobile computing services. The problem is the use of wireless medium having high error rates and low bandwidth, and the sudden network disconnection to reduce the power consumption of a mobile host and the cost of the network connection. For these problems, we proposed the architecture of the partial connection manager and designed and implemented that in this paper. In particular, The partial connection manager creates the limited number of mobile agents according to priority and sends them in parallel to server systems and combines results of them process rapidly the user request. By applying the proposed partial connection manager to the mobile computing services called cybermarket, we knew that the mobile agent technique could be suited to the mobile computing environment and overcome the partial connection problem caused by eh mobile computing environment.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.204-210
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• 2019

Mobile Crowd Computing is one of the most efficient and effective way to collect the Electronic health records and they are very intelligent in processing them. Mobile Crowd Computing can handle, analyze and process the huge volumes of Electronic Health Records (EHR) from the high-performance Cloud Environment. Electronic Health Records are very sensitive, so they need to be secured, authenticated and processed efficiently. However, security, privacy and authentication of Electronic health records(EHR) and Patient health records(PHR) in the Mobile Crowd Computing Environment have become a critical issue that restricts many healthcare services from using Crowd Computing services .Our proposed Efficient Multi-layer Encryption Framework(MLEF) applies a set of multiple security Algorithms to provide access control over integrity, confidentiality, privacy and authentication with cost efficient to the Electronic health records(HER)and Patient health records(PHR). Our system provides the efficient way to create an environment that is capable of capturing, storing, searching, sharing, analyzing and authenticating electronic healthcare records efficiently to provide right intervention to the right patient at the right time in the Mobile Crowd Computing Environment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.99-105
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• 2012

Given the numbers of smartphones, tablets and other mobile devices shipped every day, more and more users are relying on the cloud as the main driver for satisfying their computing needs, whether it is data storage, applications or infrastructure. Mobile cloud computing is simply cloud computing in which at least some of the devices involved are mobile. Each node is owned by a different user and is likely to be mobile. Using mobile hardware for cloud computing has advantages over using traditional hardware. These advantage include computational access to multimedia and sensor data without the need for large network transfer, more efficient access to data stored on other mobile devices and distributed ownership and maintenance of hardware. It is important to predict job execution time in mobile cloud computing because there are many mobile nodes with different capabilities. This paper analyzes the job execution time for mobile cloud computing in terms of network environment and heterogeneous mobile nodes using a mathematical model.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.6
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• pp.21-30
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• 2017

Physical computing is performed through interaction with the real world making it suitable for cultivating student abilities in computing knowledge and thought processes. Furthermore, if users can develop programs under block-coding environment, it will be more easy and more intuitive. However, the existing block coding environment has a problem that the physical devices must be continuously connected to the computer. Blockly is an open source library that adds a visual code editor linked with graphic blocks to demonstrate coding concepts through web and mobile apps. Using Blockly, we describe a development environment for physical computing on mobile platform, which combines physical computing with an established block-coding environment, and activates it through wireless communication.

• Journal of the Korean Data and Information Science Society
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• v.19 no.1
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• pp.11-24
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• 2008

In this paper, the patterns of movement used in the mobile communication systems are adopted in the mobile computing environment to reduce handover delay and to support seamless handover for MIPv6 based on IEEE 802.11 networks. That is, RtSolPr message and PrRtAdv message can be treated before handover. As the result, it is possible to assign NCoA to MN and Next Access Router(NAR) before handover starts. This can minimize handover delay and reduce the total handover delay.