• Journal of KIISE
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• v.42 no.6
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• pp.707-712
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• 2015

Mobile cloud computing is a technology that uses cloud services to overcome resource constrains of a mobile device, and it applies the computation offloading scheme to transfer a portion of a task which should be executed from a mobile device to the cloud. If the communication cost of the computation offloading is less than the computation cost of a mobile device, the mobile device commits a certain task to the cloud. The previous cost analysis models, which were used for separating functions running on a mobile device and functions transferring to the cloud, only considered the amount of data transfer and response time as the offloading cost. In this paper, we proposed a new task partitioning scheme that considers the frequency of function calls and data synchronization, during the cost estimation of the computation offloading. We also verified the energy efficiency of the proposed scheme by using experimental results.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.383-394
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• 2013

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, have been proposed. Typically, in MCC, many nodes with different operating systems and platform and diverse mobile applications or services are located, and a central manager autonomously performs several management tasks to maintain a consistent level of MCC overall quality. However, as there are a larger number of nodes, mobile applications, and services subscribed by the mobile applications and their interactions are extremely increased, a traditional management method of MCC reveals a fundamental problem of degrading its overall performance due to overloaded management tasks to the central manager, i.e. a bottle neck phenomenon. Therefore, in this paper, we propose a clustering-based optimization method to solve performance-related problems on large-scaled MCC and to stabilize its overall quality. With our proposed method, we can ensure to minimize the management overloads and stabilize the quality of MCC in an active and autonomous way.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.141-152
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• 2013

The applications and concerned technologies of cloud computing services, one of major trends in the information communication technology, are widely progressing and advancing. OpenStack, one of open source cloud computing platforms, is comprised of several service components; using these, it can be possible to build public or private cloud computing service for a given target application. In this study, a remote sensing image analysis processing service on cloud computing environment has designed and implemented as an operational test application in the private cloud computing environment based on OpenStack. The implemented service is divided into instance server, web service, and mobile app. A instance server provides remote sensing image processing and database functions, and the web service works for storage and management of remote sensing image from user sides. The mobile app provides functions for remote sensing images visualization and some requests.

• Journal of KIISE
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• v.45 no.2
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• pp.141-149
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• 2018

Nowadays, mobile computing has become a common computing paradigm that provides convenience to people's daily life. More and more useful mobile applications' appearance makes it possible for a user to manage personal schedule, enjoy entertainment, and do many useful activities. However, there are some inherent defects in a mobile device that battery constraints and bandwidth limitations. These drawbacks get a user into troubles when to run computationally intensive applications. As a remedy scheme, component offloading makes room for handling mentioned issues via migrating computationally intensive component to the cloud server. In this paper, we will present the predictive offloading method for efficient mobile cloud computing. At last, we will present experiment result for validating applicability and practicability of our proposal.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.70-76
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• 2012

This research tested how the perceived risk and the trust affect the usage intention of the cloud computing. To this end, this research setups a research model and tests it with the statistic tools. In order to build the model, TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology) were employed and, the factors such as the perceived risk, the trust and the intention of the cloud computing use were derived. This research finds that the perceived risk does not affect the intention of usage. Also the perceived risk has the negative effect for the trust. Thus this research has the following suggestions.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.118-123
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• 2022

We implemented a real-time cloud robotics application by offloading robot navigation engine over to 5G Mobile Edge Computing (MEC) sever. We also ran a fleet management system (FMS) in the server and controlled the movements of multiple robots at the same time. The mobile robots under the test were connected to the server through 5G SA network. Public 5G network, which is already commercialized, has been temporarily modified to support this validation by the network operator. Robot engines are containerized based on micro-service architecture and have been deployed using Kubernetes - a container orchestration tool. We successfully demonstrated that mobile robots are able to avoid obstacles in real-time when the engines are remotely running in 5G MEC server. Test results are compared with 5G Public Cloud and 4G (LTE) Public Cloud as well.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.315-320
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• 2021

Currently, cloud computing is being used as a technology that greatly changes the IT field. For many businesses, many cloud services are available in the form of custom, reliable, and cost-effective web applications. Most cloud service providers provide functions such as IoT, machine learning, AI services, blockchain, AR & VR, mobile services, and containers in addition to basic cloud services that support the scalability of processors, memory, and storage. In this paper, we will look at the most used cloud service providers and compare the services provided by the cloud service providers.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.427-432
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• 2010

The fast-emerging of cloud computing technology today has sufficiently benefited its wide range of users from individuals to large organizations. It carries an attractive characteristic by renting myriad virtual storages, computing resources and platform for users to manipulate their data or utilize the processing resources conveniently over Internet without the need to know the exact underlying infrastructure which is resided remotely at cloud servers. However due to the loss of direct control over the systems/applications, users are concerned about the risks of cloud services if it is truly secured. In the literature, there are cases where attackers masquerade as cloud users, illegally access to their accounts, by stealing the static login password or breaking the poor authentication gate. In this paper, we propose a two-factor authentication framework to enforce cloud services' authentication process, which are Public Key Infrastructure (PKI) authentication and mobile out-of-band (OOB) authentication. We discuss the framework's security analysis in later session and conclude that it is robust to phishing and replay attacks, prohibiting fraud users from accessing to the cloud services.

• Journal of Service Research and Studies
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• v.2 no.1
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• pp.61-68
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• 2012

Much technologies building cloud computing environment and supporting sevices on the cloud computing have been developing. Through the environment, accessing new services and sharing knowledge become easy. So far, they have just focused on companies which can support services and people who can use those services. In other words, the environment and models for cloud computing are the most important issue. However, the environment changes rapidly, mobile devices that are connected with each other not only will replace the computing environment based on desktop, but also can create Big data. Therefore, technologies and models are need to follow the trend including mobile based cloud computing environment. In this paper, we explain the cloud computing technologies and trend. Also we address Machine to Machine(M2M) technology and Web of things(WoT) in order to apply those into the cloud computing environment because these two concepts will enhance effectiveness and service reusability in the coming days.

• Convergence Security Journal
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• v.15 no.5
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• pp.3-8
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• 2015

Most mobile cloud computing system use public key cryptography to provide data security and mutual authentication. A variant of traditional public key technologies called Identity-Based Cryptography(IBC) has recently received considerable attention. The certificate-free approach of IBC may well match the dynamic qualities of cloud environment. But, there is a need for a lightweight secure framework that provides security with minimum processing overhead on mobile devices. In this paper, we propose to use hierarchical ID-Based Encryption in mobile cloud computing. It is suitable for a mobile network since it can reduce the workload of root Public Key Generators by delegating the privilege of user authentication and private key generation. The Identity-Based Encryption and Identity-Based Signature are also proposed and an ID-Based Authentication scheme is presented to secure data processing. The proposed scheme is designed by one-way hash functions and XOR operations, thus has low computation costs for mobile users.