• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.27-34
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• 2006

In the near future, people will wish to access many kinds of heterogeneous networks to use their services anytime and anywhere. Owing to the heterogeneity of networks, there must be many kinds of protocols to guarantee secure services. The mobile device can depend in a middleware for accessing services in the heterogeneous networks and the middleware helps the mobile device to communicate with services without blowing concrete protocols. If a secure channel is necessary, the middleware may access a private key in the mobile device to perform a security protocol. In this paper, we focus on the security of a private key in the mobile device against malicious middlewares. To do so, we introduce two models for a user to protect his/her private key against malicious middlewares by generating authentication data(e.g., digital signatures) without keeping the private key in the mobile device.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1947-1957
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• 2015

CCN networking is one of the future internet. With the rapid development of network platforms emerged a wide range of services through a virtual network environment. The performance of CCN in the high bandwidth delay is important to provide various services between nations. We can check the high bandwidth delay product in federation. Federation between the nations has the advantage of being effective to do a various services for the users, and the remote heterogeneous physical hardware engine supports various environments. Data transmission delay can be occur in long distance network even though the network is federated network. In this paper, we propose CCN-Helper protocol for data transmission delay in ling distance networks. We connect from KREONET in Korea to iLab.t in Belgique in order to test CCNx over heterogeneous federated environment.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.69-78
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• 2024

Recently, consumers have shown an increasing tendency to seek information related to environmental, social, and governance (ESG) aspects in order to choose products with higher social value and environmental friendliness. In this paper, we proposes a product recommendation system applying ESG indicators tailored to the recent consumer trend of value-based consumption, utilizing a model called MultiSAGE that combines GraphSAGE and GAT. To achieve this, ESG rating data for 1,033 companies in 2022 collected from the Korea ESG Standard Institute and actual product data from N companies were transformed into a Heterogeneous Graph format through a data processing pipeline. The MultiSAGE model was then applied in machine learning to implement a recommendation system that, given a specific product, suggests eco-friendly alternatives. The implementation results indicate that consumers can easily compare and purchase products with ESG indicators applied, and it is anticipated that this system will be utilized in recommending products with social value and environmental friendliness.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.50-58
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• 2017

Recently, some methods of converging heterogeneous fire sensor data have been proposed for effective fire detection, but the rule-based methods have low adaptability and accuracy, and the fuzzy inference methods suffer from detection speed and accuracy by lack of consideration for images. In addition, a few image-based deep learning methods were researched, but it was too difficult to rapidly recognize the fire event in absence of cameras or out of scope of a camera in practical situations. In this paper, we propose a novel fire detection system combining a deep learning algorithm based on CNN and fuzzy inference engine based on heterogeneous fire sensor data including temperature, humidity, gas, and smoke density. we show it is possible for the proposed system to rapidly detect fire by utilizing images and to decide fire in a reliable way by utilizing multi-sensor data. Also, we apply distributed computing architecture to fire detection algorithm in order to avoid concentration of computing power on a server and to enhance scalability as a result. Finally, we prove the performance of the system through two experiments by means of NIST's fire dynamics simulator in both cases of an explosively spreading fire and a gradually growing fire.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.162-162
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• 2017

구글에서 공개한 Tensorflow를 이용한 여러 학문 분야의 연구가 활발하다. 농업 시설환경을 대상으로 한 빅데이터의 축적이 증가함과 아울러 실효적인 정보 획득을 위한 각종 데이터 분석 및 마이닝 기법에 대한 연구 또한 활발한 상황이다. 한편, 타 분야의 성공적인 심층학습기법 응용사례에 비하여 농업 분야에서의 응용은 초기 성장 단계라 할 수 있다. 이는 농업 현장에서 취득한 정보의 난해성 및 완성도 높은 생육/환경 모델링 정보의 부재로 실효적인 전과정 처리 기술 도출에 소요되는 시간, 비용, 연구 환경이 상대적으로 부족하기 때문일 것이다. 특히, 센서 기반 데이터 취득 기술 증가에 따라 비약적으로 방대해진 수집 데이터를 시간 복잡도가 높은 심층 학습 모델링 연산에 기계적으로 단순 적용할 경우 시간 효율적인 측면에서 성공적인 결과 도출에 애로가 있을 것이다. 매우 높은 시간 복잡도를 해결하기 위하여 제시된 하드웨어 가속 기능의 경우 일부 개발환경에 국한이 되어 있다. 일례로, 구글의 Tensorflow는 오픈소스 기반 병렬 클러스터링 기술인 MPICH를 지원하는 알고리즘을 공개하지 않고 있다. 따라서, 본 연구에서는 심층학습 기법 연구에 있어서, 예상 가능한 다양한 자원을 활용하여 최대한 연산의 결과를 빨리 도출할 수 있는 하드웨어적인 접근 방법을 모색하였다. 호스트에서 수행하는 일방적인 학습 알고리즘과 달리 이기종간 심층 학습이 가능하기 위해선 우선, NFS(Network File System)를 이용하여 데이터 계층이 상호 연결이 되어야 한다. 이를 위해서 고속 네트워크를 기반으로 한 NFS의 이용이 필수적이다. 둘째로 제한된 자원의 한계를 극복하기 위한 메모 공유 라이브러리가 필요하다. 셋째로 이기종간 프로세서에 최적화된 병렬 처리용 컴파일러를 이용해야 한다. 가장 중요한 부분은 이기종간의 처리 능력에 따른 작업을 고르게 분배할 수 있는 작업 스케쥴링이 수행되어야 하며, 이는 처리하고자 하는 데이터의 형태에 따라 매우 가변적이므로 해당 데이터 도메인에 대한 엄밀한 사전 벤치마킹이 수행되어야 한다. 이러한 요구조건을 대부분 충족하는 Open-CL ver1.2(https://www.khronos.org/opencl/)를 이용하였다. 최신의 Open-CL 버전은 2.2이나 본 연구를 위하여 준비한 4가지 이기종 시스템에서 모두 공통적으로 지원하는 버전은 1.2이다. 실험적으로 선정된 4가지 이기종 시스템은 1) Windows 10 Pro, 2) Linux-Ubuntu 16.04.4 LTS-x86_64, 3) MAC OS X 10.11 4) Linux-Ubuntu 16.04.4 LTS-ARM Cortext-A15 이다. 비교 분석을 위하여 NVIDIA 사에서 제공하는 Pascal Titan X 2식을 SLI로 구성한 시스템을 준비하였다. 개별 시스템에서 별도로 컴파일 된 바이너리의 이름을 통일하고, 개별 시스템의 코어수를 동일하게 균등 배분하여 100 Hz의 데이터로 입력이 되는 온도 정보와 조도 정보를 입력으로 하고 이를 습도정보에 Linear Gradient Descent Optimizer를 이용하여 Epoch 10,000회의 학습을 수행하였다. 4종의 이기종에서 총 32개의 코어를 이용한 학습에서 17초 내외로 연산 수행을 마쳤으나, 비교 시스템에서는 11초 내외로 연산을 마치는 결과가 나왔다. 기보유 하드웨어의 적절한 활용이 가능한 심층학습 기법에 대한 연구를 지속할 것이다

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.43-54
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• 2009

As R&D(Research and Development) is going on actively to develop technologies for the ubiquitous computing environment, which Is the human-oriented future computing environment, GIS dealing with spatio-temporal data is emerging as a promising technology. This also increases the necessity of the middleware for providing services to give interoperability in various heterogeneous environments. The core technologies of the middleware are real-time processing technology of data streams coming unceasingly from positioning systems and data stream processing technology developed for non-spatio-temporal data. However, it has problems in processing queries on spatio-temporal data efficiently. Accordingly, this paper designed and implemented the spatio-temporal middleware that provides interoperability between a mobile spatio-temporal DBMS(DataBase Management System) and a server spatio-temporal MMDBMS(Main Memory DataBase Management System). The spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real-time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. In addition, it manages session for the connection of each spatio-temporal DBMS and manages resources for its stable operation. Finally, this paper proved the usability of the spatio-temporal middleware by applying it to a real-time position tracking system.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.602-613
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• 2001

Recently, the computing has developing in distributed object computing environment for supporting a programming paradigm of distributed application requiring interoperability between heterogeneous clients and servers. It involves the complex networking and the object-oriented technologies for various multimedia application service. In this paper, we construct the real-time object group platform for solving the difficulties of managements of distributed objects and the real-time constraints by requiring for real-time service supporting of applications in distributed computing environment. The existing researches are being tried to only improving the performance of systems by using real-time CORBA itself, or modifying the part of CORBA compliance. Hence, we design a new model of real-time object group platform that can support the real-time requirement without modifying the ORB. The structure of our real-time object group analyzed and defined the requirement about object management and real-time application service sides. And the role of the components of real-time object group is divided into 2 classes for reducing the side effect of interoperability between management and service. Also, we considered how to transparently express the parameters of real-time properties for clients and developers of server's service objects. If the expression of real-time parameters is transparent, then the developer can easily extend the real-time parameters simply and flexibly. Therefore, in this paper we defined the role of components of platform and described functions of each component and designed and then implemented the real-time object group platform. Finally, we showed the execution procedures of implemented our platform for verifying the functionality.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.293-306
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• 2003

In recent years, distributed computing environments have been radically changing to a structure of global, heterogeneous, federative and wide-area systems. This structure's environments consist of a let of objects which are implemented on telecommunication network to provide a wide range of services. Furthermore, all of objects existing on the earth have the duplicated characteristics according to how to categorize their own names or properties. But, the existing naming or trading mechanism has not supported the binding services of duplicated objects, because of deficiency of independent location service. Also, if the duplicated objects which is existing on different nodes provide the same service, it is possible to distribute the client requests considering each system's load. For this reason, we designed and implemented a new model that can not only support the location management of replication objects, but also provide the dynamic binding service of objects located in a system with minimum overload for maintaining load balancing among nodes in wide-area object computing environments. Our model is functionally divided into two parts; one part is to obtain an unique object handle of replicated objects with same property as a naming and trading service, and the other is to search one or more contact addresses by a location service using a given object handle. From a given model mentioned above, we present the procedures for the integrated binding mechanism in design phase, that is, Naming/Trading Service and Location Service. And then, we described in details the architecture of components for Integrated Binding Service implemented. Finally, we showed our implement environment and executing result of our model.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.1
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• pp.59-73
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• 2007

Although there exist many middlewares such as Havi, Jini, LonWorks, UPnP, and SLP, new middlewares specialized for diverse information appliances are expected to appear continuously as home networks evolve. In this paper, we examine an integrated architecture for supporting interoperability among heterogeneous middlewares under home network, we also propose and implement a scenario-based user-oriented integrated architecture for efficient home automation which is different from existing methods. HOMI(Homenetwork Middleware for Interoperability) architecture proposed in this paper provides interfaces that assist users with designing and modifying desirable scenarios using a script interpreter language HOMIL(HOMI Language). Different from an existing integrated middleware architecture, HOMI improves efficiency and convenience of interoperation between heterogeneous appliances for home automation allowing users to design and organize scenarios through these interfaces. HOMI classifies interoperation services into time contort, synchronization context, and asynchronization context and helps to execute next services considering contexts when a specific event occurs. Applying modified scenarios immediately to home network environment, HOMI provides users with seamless services without installing new applications, updating the server, or rebooting in order to adopt new scenarios. Lastly, distribution agents into several devices, we solved the overhead problem occurred in a centralized architecture for integrated middleware.