• KIPS Transactions on Software and Data Engineering
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• v.9 no.6
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• pp.177-186
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• 2020

Recent advances in deep learning technology have improved image recognition performance in the field of computer vision, and serverless computing is emerging as the next generation cloud computing technology for event-based cloud application development and services. Attempts to use deep learning and serverless computing technology to increase the number of real-world image recognition services are increasing. Therefore, this paper describes how to develop an efficient deep learning based image recognition service system using serverless computing technology. The proposed system suggests a method that can serve large neural network model to users at low cost by using AWS Lambda Server based on serverless computing. We also show that we can effectively build a serverless computing system that uses a large neural network model by addressing the shortcomings of AWS Lambda Server, cold start time and capacity limitation. Through experiments, we confirmed that the proposed system, using AWS Lambda Serverless Computing technology, is efficient for servicing large neural network models by solving processing time and capacity limitations as well as cost reduction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2217-2223
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• 2012

As smartphone users are over 20 million, companies, which offer cloud computing services, try to support various mobile devices. If so, users can use the same cloud computing service using mobile devices, as sharing document. When user share the work, there are problem in configuration management, data confidentiality and integrity. In this paper, we propose a method that cloud computing users share document efficiently, edit encrypted docuements, and manage configuration based on homomorphic encryption, which integrity is verifiable.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.512-518
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• 2013

A resource allocation algorithm has a high impact on user satisfaction as well as the ability to accommodate and process services in a distributed cloud computing. In other words, service rejections, which occur when datacenters have no enough resources, degrade the user satisfaction level. Therefore, in this paper, we propose a resource allocation algorithm considering the cloud domain's remaining resources to minimize the number of service rejections. The resource allocation rate based on Q-Learning increases when the remaining resources are sufficient to allocate the maximum allocation rate otherwise and avoids the service rejection. To demonstrate, We compare the proposed algorithm with two previous works and show that the proposed algorithm has the smaller number of the service rejections.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.81-90
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• 2023

Cloud computing is an emerging business model popularized during the last few years by the IT industry. Providing "Everything as a Service" has shifted many organizations to choose cloud-based services. However, some companies still fear shifting their data to the cloud due to issues related to the security and privacy. The paper suggests a novel Trust based Mutual Authentication Mechanism using Secret P-box based Mutual Authentication Mechanism (TbMAM-SPb) on the criticality of information. It uses a particular passcodes from one of the secret P-box to act as challenge to one party. The response is another passcode from other P-box. The mechanism is designed in a way that the response given by a party to a challenge is itself a new challenge for the other party. Access to data is provided after ensuring certain number of correct challenge-responses. The complexity can be dynamically updated on basis of criticality of the information and trust factor between the two parties. The communication is encrypted and time-stamped to avoid interceptions and reuse. Overall, it is good authentication mechanism without the use of expensive devices and participation of a trusted third party.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.303-311
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• 2014

The accountability of cloud service which provides the cloud users with accountable services applies various technologies such as the compliance of service policy, monitoring and auditing, logging, and others. It ultimately intends to provide trustworthy cloud service by determining who is accountable for various problems happened during data processing and service offering. In this paper, we propose a cloud ecosystem formed from the chain of content and DRM Cloud service in order to offer secure and trust DRM cloud service when providing high value-added content service. Besides this, we analyse the requirements of cloud services for content owners and users and then propose some logging information to be recorded for trace of accountability and a structure of tool for monitoring.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.806-813
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• 2012

In a cloud computing environment, various solutions were introduced to provide the service to users such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) and Desktop as a Service (DaaS). Nowadays, Mobile as a Service (MaaS) to provide the mobility in a cloud environment. In other words, users must have access to data and applications even when they are moving. Thus, to support the mobility to a mobile Thin-Client is the key factor. Related works to support the mobility for mobile devices were Mobile IPv6 and Proxy Mobile IPv6 which showed performance drawbacks such as packet loss during hand-over which could be very critical when collaborating with cloud computing environment. The proposed model in this paper deploys middleware and replica servers to support the data transmission among cloud and PMIPv6 domain. It supports efficient mobility during high-speed movement as well as high-density of mobile nodes in local mobility anchor. In this paper, through performance evaluation, the proposed scheme shows the cost comparison between previous PMIPv6 and verifies its significant efficiency.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.107-118
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• 2021

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.75-81
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• 2021

The purpose of this research is to derive and evaluate priorities for critical factors that must be determined before an enterprise adopts a cloud computing service. AHP analysis techniques were used to reflect decisions made by experts as research methods. AHP is a decision-making technique that expresses complex decision-making problems hierarchically and derives the best alternatives through pairwise comparison between the items of the hierarchy. Compared to the existing statistical decision making techniques, the decision making process is systematic and simple, making it easy to understand. In addition, the procedure is also reasonable by providing an indicator to determine the consistency of the decision maker in the analysis process. The analysis results of this research showed that security was the first priority, reliability was the second priority, and economic efficiency was the third priority. Among the factors in the first-priority security items, the access control rights and the safety factors of external threats are the most important factors. Research results can be used as a guideline in future practice, and it is necessary to evaluate, compare and analyze the satisfaction of companies that have adopted cloud computing services in the future.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.476-490
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• 2017

In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down, the services hosted by various hosts in DC can't be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM's with the threshold limit beyond which it can't provide service. To maintain threshold, the host's in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.135-148
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• 2020

Virtualisation in cloud computing is vital for maintaining maximum resource utilization and easy access to operation and storage management of components. Platform virtualisation technology has the potential to be easily implemented with the support of scalability and security, which are the most important components for cloud-based services. Virtual resources must be allocated to a centralized pool called the cloud, and it is considered as cloud computing only when the virtual resources are orchestrated through management and automation software. Therefore, research and development on the latest technology for such a virtualisation platform provides both academia and industry the scope to deploy the fastest and most reliable technology in limited hardware resource. In this research, we reviewed and compared the popular current technologies for network and service management and automation technology.