• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.1018-1019
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• 2018

본 논문에서는 오픈 하드웨어 플랫폼인 라즈베리파이를 활용하여 IoT 디바이스-클라우드 간 발생 가능한 상호운용성 문제를 해결할 수 있는 EdgeX Open Framework 기반 IoT Edge Gateway 개발 과정을 기술하고 이를 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5654-5668
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• 2018

Driven by security and real-time demands of Internet of Things (IoT), the timing of fog computing and edge computing have gradually come into place. Gateways bear more nearby computing, storage, analysis and as an intelligent broker of the whole computing lifecycle in between local devices and the remote cloud. In fog computing, the edge broker requires X-aware capabilities that combines software programmability, stream processing, hardware optimization and various connectivity to deal with such as security, data abstraction, network latency, service classification and workload allocation strategy. The prosperous of Field Programmable Gate Array (FPGA) pushes the possibility of gateway capabilities further landed. In this paper, we propose a software-defined gateway (SDG) scheme for fog computing paradigm termed as Fog Computing Zero-Knowledge Gateway that strengthens data protection and resilience merits designed for industrial internet of things or highly privacy concerned hybrid cloud scenarios. It is a proxy for fog nodes and able to integrate with existing commodity gateways. The contribution is that it converts Privacy-Enhancing Technologies rules into provable statements without knowing original sensitive data and guarantees privacy rules applied to the sensitive data before being propagated while preventing potential leakage threats. Some logical functions can be offloaded to any programmable micro-controller embedded to achieve higher computing efficiency.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.49-58
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• 2019

In this paper, we propose an edge cloud platform architecture for implementing smart factory. The edge cloud platform is one of edge computing architecture which is mainly focusing on the efficient computing between IoT devices and central cloud. So far, edge computing has put emphasis on reducing latency, bandwidth and computing cost in areas like smart homes and self-driving cars. On the other hand, in this paper, we suggest not only common functional architecture of edge system but also light weight cloud based architecture to apply to the specialized requirements of smart factory. Cloud based edge architecture has many advantages in terms of scalability and reliability of resources and operation of various independent edge functions compare to typical edge system architecture. To make sure the availability of edge cloud platform in smart factory, we also analyze requirements of smart factory edge. We redefine requirements from a 4M1E(man, machine, material, method, element) perspective which are essentially needed to be digitalized and intelligent for physical operation of smart factory. Based on these requirements, we suggest layered(IoT Gateway, Edge Cloud, Central Cloud) application and data architecture. we also propose edge cloud platform architecture using lightweight container virtualization technology. Finally, we validate its implementation effects with case study. we apply proposed edge cloud architecture to the real manufacturing process and compare to existing equipment engineering system. As a result, we prove that the response performance of the proposed approach was improved by 84 to 92% better than existing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.46-54
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• 2018

The Internet of Things (IoT) is an environment in which various devices provide services to users through communications. Because of the nature of the IoT, data are stored and distributed in heterogeneous information systems. In this situation, IoT end applications should be able to access data without having information on where the data are or what the type of storage is. This mechanism is called Service Discovery (SD). However, some problems arise, since the current SD architectures search for data in physical devices. First, turnaround time increases from searching for services based on physical location. Second, there is a need for a data structure to manage devices and services separately. These increase the administrator's service configuration complexity. As a result, the device-oriented SD structure is not suitable to the IoT. Therefore, we propose an SD structure called Name-based Service-centric Service Discovery (NSSD). NSSD provides name-based centralized SD and uses the IoT edge gateway as a cache server to speed up service discovery. Simulation results show that NSSD provides about twice the improvement in average turnaround time, compared to existing domain name system and distributed hash table SD architectures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.313-316
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• 2021

In the IoT(IoT: Internet of Things) environment, network configuration is essential to collect data generated from objects. Various communication methods are used to process data of objects, and wireless communication methods such as Bluetooth and WiFi are mainly used. In order to collect data of objects, a communication module must be installed to collect data generated from sensors or edge devices in real time. And in order to deliver data to the database, a software architecture must be configured. Data generated from objects can be stored and managed in a database in real time, and data necessary for industrial safety can be extracted and utilized for industrial safety service applications. In this paper, a network environment was constructed using a LoRa(LoRa: Long Range) gateway to collect object data, and a client/server data collection model was designed to collect object data transmitted from the LoRa module. In order to secure the resources necessary for data collection and storage management without data leakage, data collection should be possible in real time. As an application service, location data required for industrial safety can be stored and managed in a database in real time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.442-454
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• 2017

As the demand for meat products has steadily increased in Korea, so the livestock industry has full grown. However, the opening of import meat products is taking a toll on the local industry. Cost reduction on livestock feed, which comprises the majority of costs involved in the industry is urgent to gain a competitive edge. As Internet of Things (IoT) technologies are being applied across a multiple of industries, so are the cases of applied Smart Farm technology for efficient production. The following research aims to utilize IoT technologies to measure, in real time, the rate of depletion of feed and remaining amount and to propose an effective automated reorder & delivery system. First, a method of utilization of ultrasonic and temperature/humidity sensors to obtain corresponding data of remaining feed in the Feedbin is proposed. In addition, a method of sending the obtained data via on-the-farm gateway to Supply Chain Management (SCM) servers is proposed. Finally, utilization of the stored data to construct an automated reorder & delivery service system is proposed. It is in the researcher's intention to contribute to and enable the local livestock industry with the application of various IoT services.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.153-154
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• 2019

본 논문에서는 사물인터넷(Internet of Things, IoT)에 적용되어 사용될 수 있는 다중 게이트웨이 환경에서 각 게이트웨이의 자원 상황에 따라 종단 노드를 클라우드 단으로 직접 트레이드하여 처리함으로서 게이트웨이의 자원 소모를 줄이고 높은 처리량을 요구하는 종단 노드를 빠르게 처리 가능한 기법을 제안한다. 본 논문에서는 해당 기법의 효율성 입증을 위하여 클라우드 컴퓨팅이라는 대규모 환경을 가정하여 실험을 진행하였으며, 해당 실험의 결과에 따르면 높은 처리량을 요구하는 종단 노드를 클라우드 단에 트레이드하여 직접 처리함으로서 클라우드 단 하부의 다중 게이트웨이의 자원 소모율 감소 및 데이터 처리 속도가 증대 되었음을 확인할 수 있다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.135-141
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• 2018

In this paper, we describe design and implementation of optimal smart home control system. Recent developments in technologies such as sensors and communication have enabled the Internet of Things to control a wide range of objects, such as light bulbs, socket-outlet, or clothing. Many businesses rely on the launch of collaborative services between them. However, traditional IoT systems often support a single protocol, although data is transmitted across multiple protocols for end-to-end devices. In addition, depending on the manufacturer of the Internet of things, there is a dedicated application and it has a high degree of complexity in registering and controlling different IoT devices for the internet of things. ARIoT system, special marking points and edge extraction techniques are used to detect objects, but there are relatively low deviations depending on the sampling data. The proposed system implements an IoT gateway of object based on OneM2M to compensate for existing problems. It supports diverse protocols of end to end devices and supported them with a single application. In addition, devices were learned by using deep learning in the artificial intelligence field and improved object recognition of existing systems by inference and detection, reducing the deviation of recognition rates.