• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.163-167
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• 2008

본 논문에서는 광범위 Community Computing 환경에서의 Community Computing Network의 에너지 효율과 신뢰성을 높이기 위한 수정된 SPaC(Simple Packet Combining)를 제안한다. 제안하는 수정된 SPaC는 같은 패킷을 두 개 이상의 오류가 있는 패킷을 이용하여 에러를 복구하는 기존의 SPaC를 수정하여 특정 threshold 값을 사용하여 감청 시 CPU의 처리량을 줄이고 패리티 패킷을 이용하여 높은 신뢰성과 보다 향상된 에너지 효율을 가진다.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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• pp.299-305
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• 2020

We have developed a scheduler that additionally consider network performance by extending the Kubernetes developed to manage lots of containers in cloud computing nodes. The network delay adapt characteristics of the compute nodes were learned during server operation and the learned results were utilized to develop placement algorithm by considering the existing measurement units, CPU, memory, and volume together, and it was confirmed that the low delay network service was provided through placement algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.75-85
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• 2012

In general, cellular network is deployed as distributed network architecture, so network equipment is spread out all over the coverage area. This case causes high cost. Recently, centralized network architecture has been deployable at cellular network since base station was able to be virtualized due to advance in computing power. The centralized network architecture in cellular network adjusts its cell radius dynamically and minimizes power consumption of the network. This paper introduces a new centralized deployment way of cellular network using SDR and cloud computing technology. Then, advantage and feasibility of the new network will be reviewed by implementing this novel network.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.43-52
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• 2013

Pervasive computing and social network are good resources in recommendation method. Collaborative filtering is one of the most popular recommendation methods, but it has some limitations such as rating sparsity. Moreover, it does not consider social network in pervasive computing environment. We propose an effective proactive friend recommendation method using social network and contexts in pervasive computing environment. In collaborative filtering method, users need to rate sufficient number of items. However, many users don't rate items sufficiently, because the rating information must be manually input into system. We solve the rating sparsity problem in the collaboration filtering method by using contexts. Our method considers both a static and a dynamic friendship using contexts and social network. It makes more effective recommendation. This paper describes a new friend recommendation method and then presents a music friend scenario. Our work will help e-commerce recommendation system using collaborative filtering and friend recommendation applications in social network services.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.107-114
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• 2023

The study provides the identification of vulnerabilities in the security issues by Wireless Network. To achieve it the research focus on packet flow analysis, end to end data communication, and the security challenges (Cybercrime, insider threat, attackers, hactivist, malware and Ransomware). To solve this I have used the systematic literature review mechanisms and demonstrative tool namely Wireshark network analyzer. The practical demonstration identifies the packet flow, packet length time, data flow statistics, end- to- end packet flow, reached and lost packets in the network and input/output packet statics graphs. Then, I have developed the proposed model that used to secure the Wireless network solution and prevention vulnerabilities of the network security challenges. And applying the model that used to investigate the security challenges and vulnerabilities of cloud computing services is used to fulfill the network security goals in Wireless network. Finally the research provides the model that investigate the security challenges and vulnerabilities of cloud computing services in wireless networks

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.89-100
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• 2022

With the advancement in the Internet of things Technology (IoT) cloud computing, billions of physical devices have been interconnected for sharing and collecting data in different applications. Despite many advancements, some latency - specific application in the real world is not feasible due to existing constraints of IoT devices and distance between cloud and IoT devices. In order to address issues of latency sensitive applications, fog computing has been developed that involves the availability of computing and storage resources at the edge of the network near the IoT devices. However, fog computing suffers from many limitations such as heterogeneity, storage capabilities, processing capability, memory limitations etc. Therefore, it requires an adequate task scheduling method for utilizing computing resources optimally at the fog layer. This work presents a comprehensive review of different task scheduling methods in fog computing. It analyses different task scheduling methods developed for a fog computing environment in multiple dimensions and compares them to highlight the advantages and disadvantages of methods. Finally, it presents promising research directions for fellow researchers in the fog computing environment.

• KNOM Review
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• v.22 no.3
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• pp.1-12
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• 2019

Recently, researching using big data and AI has emerged as a major issue in the ICT field. But, the size of big data for research is growing exponentially. In addition, users of data transmission of existing network method suggest that the problem the time taken to send and receive big data is slower than the time to copy and send the hard disk. Accordingly, researchers require dynamic and flexible network technology that can transmit data at high speed and accommodate various network structures. SDN/NFV technologies can be programming a network to provide a network suitable for the needs of users. It can easily solve the network's flexibility and security problems. Also, the problem with performing AI is that centralized data processing cannot guarantee real-time, and network delay occur when traffic increases. In order to solve this problem, the edge-computing technology, should be used which has moved away from the centralized method. In this paper, we investigate the concept and research trend of SDN, NFV, and edge-computing technologies, and analyze the trends of data central network technologies used by combining these three technologies.

• International Commerce and Information Review
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• v.13 no.3
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• pp.55-74
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• 2011

Web Service applications based on the social relation such as Social Network Service(SNS), Social Medias are making strong blast. Social Computing which is widely spreading to worldwide is affecting to our life including policies, economies, societies and culture. Based on Web 2.0, various services like as Social Collaboration, Social Publishing, Social Feedback are supplied, more evolved social computing services, Social Connection, Augmented Reality, will be served for the next days from now. These network based services, Social Network Service or Social Media frequently used terms, are not defined exactly and their characteristics are not gotten to the bottom yet. Theoretical and systematic studies on these themes are not made also. Applications to business area, especially the receptivity to social computing in international trade is barely made to these days. This study focuses on the concepts, characteristics and sorts of social computing and purposes to consider its possibilities of application of social computing to international trade. Considering the advantage of Social network service, it can be used in international trade, a kind of B2B transaction, while existing social network is mainly applied to B2e transaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2764-2783
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• 2012

Network virtualization supports future Internet environments and cloud computing. Virtualization can mitigate many hardware restrictions and provide variable network topologies to support variable cloud services. Owing to several advantages such as low cost, high flexibility, and better manageability, virtualization has been widely adopted for use in network virtualization platforms. Among the many issues related to cloud computing, to achieve a suitable cloud service quality we specifically focus on network and performance isolation schemes, which ensure the integrity and QoS of each virtual cloud network. In this study, we suggest a virtual network platform that uses Xen-based virtualization, and implement multiple virtualized networks to provide variable cloud services on a physical network. In addition, we describe the isolation of virtual networks by assigning a different virtualized network ID (VLAN ID) to each network to ensure the integrity of the service contents. We also provide a method for efficiently isolating the performance of each virtual network in terms of network bandwidth. Our performance isolation method supports multiple virtual networks with different levels of service quality.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.