• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1369-1378
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• 2017

Pub/Sub (Publish/Subscribe) paradigm is a simple and easy to use model for interconnecting applications in a distributed environment. In general, subscribers register their interests in a topic or a pattern of events and then asynchronously receive events matching their interest, regardless of the events' publisher. In order to build a low latency lightweight pub/sub system for Internet of Things (IoT) services, we propose a GQSFPS (Group Quorum System-based Fog Pub/Sub) system that is a core component in the event-driven service oriented architecture framework for IoT services. The GQSFPS organizes multiple installed pub/sub brokers in the fog servers into a group quorum based P2P (peer-to-peer) topology for the efficient searching and the low latency accessing of events. Therefore, the events of IoT are cached on the basis of group quorum, and the delay-sensitive IoT applications of edge devices can effectively access the cached events from group quorum fog servers in low latency. The performance of the proposed GQSFPS is evaluated through an analytical model, and is compared to the GQPS (grid quorum-based pud/sub system).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Journal of KIISE
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• v.43 no.6
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• pp.710-717
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• 2016

Recently, several research studies on things abstraction framework have been proposed in order to implement the multi-service Internet of Things (IoT) system, where various IoT services share the thing devices. Distributed things abstraction has an IoT service duplication problem, which aggravates power consumption of mobile devices and network traffic. On the other hand, cloud server-centric things abstraction cannot cover real-time interactions due to long network delay. Fog server-centric things abstraction has limits in insufficient IoT interfaces. In this paper, we propose Smart Fog which is a fog server-centric things abstraction framework to resolve the problems of the existing things abstraction frameworks. Smart Fog consists of software modules to operate the Smart Gateway and three interfaces. Smart Fog is implemented based on IoTivity framework and OIC standard. We construct a smart home prototype on an embedded board Odroid-XU3 using Smart Fog. We evaluate the network performance and energy efficiency of Smart Fog. The experimental results indicate that the Smart Fog shows short network latency, which can perform real-time interaction. The results also show that the proposed framework has reduction in the network traffic of 74% and power consumption of 21% in mobile device, compared to distributed things abstraction.

• ETRI Journal
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• v.41 no.3
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• pp.348-357
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• 2019

Fog radio access network (F-RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm-based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F-RAN. First, an F-RAN system model is presented that includes a certain number of randomly distributed fog access points (F-APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F-RANs is described. Third, the details of the proposed optimal genetic algorithm-based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.

• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.90-97
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• 2017

The Internet of Things(IoT) market is expected to grow from 15.5billion to 75.4 billion by 2015-2025. As the number of IoT devices increases, the amount of data that is sent to the cloud is increasing. Today's Cloud Computing models are not suited to handle the vast amount of data generated by IoT devices. In this paper, we propose a Cooperation Coordinator System that reduces server load and improved real-time processing capability under specific circumstances by using Band-Cloud. The cooperation coordinator system dynamically forms the cloud when cooperation is needed between mobile devices located near. It is called Band-Cloud. Band-Cloud provides services entrusted by Central Cloud. This paper describes the proposed system and shows the cooperation process using the Android-based mobile devices and Wi-Fi Direct technology. Such a system can be applied to cases where real-time processing is required in a narrow area such as a hospital ward or a school classroom.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.89-92
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• 2020

According to the various IoT(Internet of Things) services, there have been lots of task offloading researches for IoT devices. Since there are service response delay and core network load issues in conventional cloud computing based offloadings, fog computing based offloading has been focused whose location is close to the IoT devices. However, even in the fog computing architecture, the load can be concentrated on the for computing node when the number of requests increase. To solve this problem, the opportunistic fog computing concept which offloads task to available computing resources such as cars and drones is introduced. In previous fog and opportunistic fog node researches, the offloading is performed immediately whenever the service request occurs. This means that the service requests can be offloaded to the opportunistic fog nodes only while they are available. However, if the service response delay requirement is satisfied, there is no need to offload the request immediately. In addition, the load can be distributed by making the best use of the opportunistic fog nodes. Therefore, this paper proposes a delayed offloading scheme to satisfy the response delay requirements and offload the request to the opportunistic fog nodes as efficiently as possible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3870-3884
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• 2020

The proposed framework of Four Layer Robust Storage in Cloud (FLRSC) architecture involves host server, local host and edge devices in addition to Virtual Machine Monitoring (VMM). The goal is to protect the privacy of stored data at edge devices. The computational intelligence (CI) part of our algorithm distributes blocks of data to three different layers by partially encoded and forwarded for decoding to the next layer using hash and greed Solomon algorithms. VMM monitoring uses snapshot algorithm to detect intrusion. The proposed system is compared with Tiang Wang method to validate efficiency of data transfer with security. Hence, security is proven against the indexed efficiency. It is an important study to integrate communication between local host software and nearer edge devices through different channels by verifying snapshot using lamport mechanism to ensure integrity and security at software level thereby reducing the latency. It also provides thorough knowledge and understanding about data communication at software level with VMM. The performance evaluation and feasibility study of security in FLRSC against three-layered approach is proven over 2³² blocks of data with 98% accuracy. Practical implications and contributions to the growing knowledge base are highlighted along with directions for further research.

• Journal of Korean Elementary Science Education
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• v.25 no.1
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• pp.15-26
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• 2006

This study investigated the characteristics of contents of the Atmosphere and Weather in the elementary science curriculum. For this study, elementary science textbooks reflecting the elementary science curriculum from 1st to 7th were analyzed with a number of tools. The results were as follows: Several parts of the contents about Atmosphere and Weather were dealt continuously through the all of science curriculum. Atmospheric Pressure, Humidity and Atmospheric Pressure and Weather were applied at the fifth grade above continuously. And Cloud$\cdot$Fog$\cdot$Dew was applied at the third and fifth grade. Quantity of learning about Atmosphere was more than it's of Weather always. Especially, Movement of Atmosphere and Temperature Change were maintained continuously above $10\%$ of the contents about Atmosphere and Weather. Some of the detailed learning themes related Atmosphere and Weather were dealt commonly through the all of the elementary science curriculum. Finally, the results showed that the contents of Physical Nature of Atmosphere, Atmospheric Pressure, Movement of Atmosphere, Temperature and it's Change and Cloud$\cdot$Fog$\cdot$Dew had been learned always with the experiments and practical training.