• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.595-602
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• 2021

The robot is developing into a software-oriented shape that recognizes the surrounding situation and is given a task. Cloud Robotics Platform is a method to support Service Oriented Architecture shape for robots, and it is a cloud-based method to provide necessary tasks and motion controllers depending on the situation. As it evolves into a humanoid robot, the robot will be used to help humans in generalized daily life according to the three robot principles. Therefore, in addition to robots for specific individuals, robots as public goods that can help all humans depending on the situation will be universal. Therefore, the importance of information security in the Cloud Robotics Computing environment is analyzed to be composed of people, robots, service applications on the cloud that give intelligence to robots, and a cloud bridge that connects robots and clouds. It will become an indispensable element for In this paper, we propose a Security Scheme that can provide security for communication between people, robots, cloud bridges, and cloud systems in the Cloud Robotics Computing environment for intelligent robots, enabling robot services that are safe from hacking and protect personal information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2952-2971
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• 2016

Outsourcing jobs to a public cloud is a cost-effective way to address the problem of satisfying the peak resource demand when the local cloud has insufficient resources. In this paper, we studied the management of deadline-constrained bag-of-tasks jobs on hybrid clouds. We presented a binary nonlinear programming (BNP) problem to model the hybrid cloud management which minimizes rent cost from the public cloud while completes the jobs within their respective deadlines. To solve this BNP problem in polynomial time, we proposed a heuristic algorithm. The main idea is assigning the task closest to its deadline to current core until the core cannot finish any task within its deadline. When there is no available core, the algorithm adds an available physical machine (PM) with most capacity or rents a new virtual machine (VM) with highest cost-performance ratio. As there may be a workload imbalance between/among cores on a PM/VM after task assigning, we propose a task reassigning algorithm to balance them. Extensive experimental results show that our heuristic algorithm saves 16.2%-76% rent cost and improves 47.3%-182.8% resource utilizations satisfying deadline constraints, compared with first fit decreasing algorithm, and that our task reassigning algorithm improves the makespan of tasks up to 47.6%.

• Informatization Policy
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• v.21 no.2
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• pp.49-66
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• 2014

In the last few years, cloud computing has grown from being a promising business concept to one of the fast growing segments of the IT industry. However, as more and more information on individuals and companies are placed in the cloud, concerns on just how safe the computing environment is have gradually increased. In this study, it will be explored if key characteristics of cloud computing services would affect the behavioral intention to use public cloud computing services. A conceptual model is developed and seven research hypotheses are proposed for empirical testing. The proposed model is examined through structural equation analysis. The results show that perceived risk has statistically significant effect on the privacy concern of users and the privacy concern has a negative influence on the trust. Finally, the trust has a positive effect on the attitude and the attitude has statistically significant effect on use intention. Implications of these findings are discussed for both researchers and practitioners and future research issues are raised as well.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.91-100
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• 2015

Recently many companies began to feel the pressures of cost savings due to the global recession, so they have been interested in the Cloud Computing. Cloud Computing is one of using method of IT resources through the network. Users can borrow softwares or hardwares instead of buying them. Many people expect remarkable growth in Cloud Computing industry because of it's effectiveness. But Cloud Computing industry is still at an early stage. Especially, people who in the public sector hesitate to adopt Cloud Computing Services due to security issues and their conservative views. Also, they just have limited understanding, so we need to investigate what they really know and understand. Researches about the Cloud Computing generally focus on technical issues, so we can hardly find researches reference for decision making in considering the services. The study aims to investigate diverse factors for agencies' adoption decisions, such as benefits, costs, and risk in developing the most ideal type of cloud computing service for them, and performs priority analyses by applying ANP (Analytic Network Process). The results identify that features pertaining to the risk properties were considered the most significant factors. According to this research, the usage of private cloud computing services may prove to be appropriate for public environment in Korea. The study will hopefully provide the guideline to many governmental agencies and service providers, and assist the related authorities with cloud computing policy in coming up with the relevant regulations.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.33-37
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• 2019

According to the enforcement of the Cloud Computing Development and User Protection Act, a new paradigm called as Cloud Computing is coming to the fore among public and private domestic enterprises. Therefore, domestic companies should develop SaaS products specialized for the domestic market and try to preempt the IaaS market ahead of global companies. Now we are facing a necessity to combine all the cloud systems in Korean government to operate seamlessly in a harmony. In this paper, we will look at the prospect of future development of related industry through cloud computing concept and G-cloud's cloud management system (G-CMS). G-CMS can be seen as the first system to comprehensively manage heterogeneous Unix virtualization systems. G-CMS can also save costs by managing heterogeneous virtualization systems in data centers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2719-2735
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• 2015

In the cloud environment, users pay more attentions to their data security since all of them are stored in the cloud server. Researchers have proposed many mutual authentication schemes for the access control of the cloud server by using the smart card to protect the sensitive data. However, few of them can resist from the smart card lost problem and provide both of the forward security and the backward security. In this paper, we propose a novel authentication scheme for cloud computing which can address these problems and also provide the anonymity for the user. The trick we use is using the password, the smart card and the public key technique to protect the processes of the user's authentication and key exchange. Under the Elliptic Curve Diffie-Hellman (ECDH) assumption, it is provably secure in the random oracle model. Compared with the existing smart card based authentication schemes in the cloud computing, the proposed scheme can provide better security degree.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.736-739
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• 2012

Cloud Computing is attracting attention are activated and rapidly spread to companies and public institutions, etc. have been introduced are getting. Spotlighted these effects due to the utilization and integration of information system using cloud computing technology resources, and the resulting data security issue has been. In this paper, the side lights on due to the introduction of a cloud computing system, the resources of information systems, data security, and knowledge to provide the foundation for cloud computing infrastructure.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.389-394
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• 2012

The cloud computing is a system that provides IT resources service by using internet technologies, which grabs lots of attention today. Though cloud storage services provide service users with convenience, there is a problem in which data confidentiality is not guaranteed because it is hard for data owners to control the access to the data. This article suggested the technique by applying Public-Key Cryptosystem only to a block after dividing users' data into blocks in order to protect users' data in cloud system. Thus confidentiality and integrity are given to users' data stored in cloud storage server.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2824-2837
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• 2019

Container technologies are widely used in infrastructures to deploy and manage applications in cloud computing environment. As containers are light-weight software, the cluster of cloud applications can easily scale up or down to provide Internet-based services. Container-based applications can well deal with fluctuate workloads by dynamically adjusting physical resources. Current works of scheduling applications often construct applications' performance models with collected historical training data, but these works with static models cannot self-adjust physical resources to meet the dynamic requirements of cloud computing. Thus, we propose a self-adaptive automatic container scheduling framework AutoScale for cloud applications, which uses a feedback-based approach to adjust physical resources by extending, contracting and migrating containers. First, a queue-based performance model for cloud applications is proposed to correlate performance and workloads. Second, a fuzzy Kalman filter is used to adjust the performance model's parameters to accurately predict applications' response time. Third, extension, contraction and migration strategies based on predicted response time are designed to schedule containers at runtime. Furthermore, we have implemented a framework AutoScale with container scheduling strategies. By comparing with current approaches in an experiment environment deployed with typical applications, we observe that AutoScale has advantages in predicting response time, and scheduling containers to guarantee that response time keeps stable in fluctuant workloads.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5269-5286
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• 2018

Task scheduling is one of the key issues in improving system performance and optimizing resource management in cloud computing environment. In order to provide appropriate services for heterogeneous users, we propose a novel task scheduling strategy with service differentiation, in which the delay sensitive tasks are assigned to the rapid cloud with high-speed processing, whereas the fault sensitive tasks are assigned to the reliable cloud with service restoration. Considering that a user can receive service from either local SaaS (Software as a Service) servers or public IaaS (Infrastructure as a Service) cloud, we establish a hybrid queueing network based system model. With the assumption of Poisson arriving process, we analyze the system model in steady state. Moreover, we derive the performance measures in terms of average response time of the delay sensitive tasks and utilization of VMs (Virtual Machines) in reliable cloud. We provide experimental results to validate the proposed strategy and the system model. Furthermore, we investigate the Nash equilibrium behavior and the social optimization behavior of the delay sensitive tasks. Finally, we carry out an improved intelligent searching algorithm to obtain the optimal arrival rate of total tasks and present a pricing policy for the delay sensitive tasks.