• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.83-90
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• 2022

Traditional Cloud Computing would be unable to safely host IoT data due to its high latency as the number of IoT sensors and physical devices accommodated on the Internet grows by the day. Because of the difficulty of processing all IoT large data on Cloud facilities, there hasn't been enough research done on automating the security of all components in the IoT-Cloud ecosystem that deal with big data and real-time jobs. It's difficult, for example, to build an automatic, secure data transfer from the IoT layer to the cloud layer, which incorporates a large number of scattered devices. Addressing this issue this article presents an intelligent algorithm that deals with enhancing security aspects in IoT cloud ecosystem using butterfly optimization algorithm.

• Smart Structures and Systems
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• 제1권1호
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• pp.1-12
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• 2005

This paper describes the area of intelligent systems research as funded by the Civil and Mechanical Systems (CMS) Division of the National Science Foundation (NSF). With developments in computer science, information technology, sensing and control the design of typical machines and structures by civil and mechanical engineers is evolving toward intelligent systems that can sense, decide and act. This trend toward electro-mechanical design is well-established in modern machines (e.g. vehicles, robots, disk drives) and often referred to as mechatronics. More recently intelligent systems design is becoming an important aspect of structures, such as buildings and bridges. We briefly review recent developments in structural control, including the role that NSF has played in their development, and discuss on-going CMS activities in this area. In particular, we highlight the interdisciplinary initiative on Sensors and Sensor Networks and the Network for Earthquake Engineering Simulation (NEES). NEES is a distributed cyberinfrastructure to support earthquake engineering research, and provides the pioneering NEES grid computing environment for simulation, teleoperation, data collection and archiving, etc.

• 한국지능시스템학회논문지
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• 제10권4호
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• pp.293-298
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• 2000

대단히 많은 수의 퍼지 규칙을 갖거나 대용량의 퍼지 데이터를 갖는 퍼지 전문가 시스템 또는 퍼지 데이터베이스 시스템에서는 많은 추론 시간을 요구한다. 따라서 이러한 추론 시간을 줄이기 위해서는 고성능 병렬 퍼지 컴퓨팅 환경을 필요로 한다. 본 온문에서는 병렬 컴퓨팅 환경에서 병렬 퍼지 추론 기법을 제안한다. 여기에서 퍼지 규칙은 분산되어 있고 동시에 수행된다. ONE_TO_ALL 알고리즘은 모든 노드에 퍼지 입력 백터를 broadcasting하는데 사용한다. MIN/MAX 연산의 결과는 ALL_TO_ONE 알고리즘에 의해 출력 프로세서로 전송된다. 퍼지 규칙 또는 데이터의 병렬 처리로 인해, 병렬 추론 알고리즘은 효과적인 병렬성의 추출 및 속도 향상을 가져온다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.288-298
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• 2008

We introduce new type of networked robot, Ubiquitous Robotic Companion (URC), embedded with ATLAS Service-oriented architecture for enhancing the space sensing capability. URC is a network-based robotic system developed by ETRI. For years of experience in deploying service with ATLAS sensor platform for elder and people with special needs in smart houses, we need networked robots to assist elder people in their successful daily living. Recently, pervasive computing technologies reveals possibilities of networked robots in smart spaces, consist of sensors, actuators and smart devices can collaborate with the other networked robot as a mobile sensing platform, a complex and sophisticated actuator and a human interface. This paper provides our experience in designing and implementing system architecture to integrate URC robots in pervasive computing environments using the University of Florida's ATLAS service-oriented architecture. In this paper, we focus on the integrated framework architecture of URC embedded with ATLAS platform. We show how the integrated URC system is enabled to provide better services which enhance the space sensing of URC in the smart space by applying service-oriented architecture characterized as flexibility in adding or deleting service components of Ubiquitous Robotic Companion.

• 한국지능시스템학회논문지
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• 제16권2호
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• pp.222-227
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• 2006

현재 막대한 병렬성을 갖는 DNA 컴퓨팅을 이용하여 Traveling Salesman Problem (TSP)를 해결하기 위한 연구가 진행되고 있다. 하지만 기존의 방법은 그래프 문제의 표현에서 DNA의 특성을 고려하지 않아, 실제 생물학적 실험 결과와의 차이가 발생하고 있다. 따라서 DNA의 특성을 반영하고 생물학적 실험 오류를 줄일 수 있는 DNA 서열 생성 알고리즘이 필요하다. 본 논문에서는 DNA 컴퓨팅에 진화 모델의 하나인 DNA 코딩 방법을 적용한 DNA 서열 생성 알고리즘을 제안한다. 제안한 알고리즘은 TSP에 적용하여 기존에 단순 유전자 알고리즘과 비교하였다. 그 결과 제안한 알고리즘은 오류를 최소화한 우수한 서열을 생성하고 생물학적 실험 오류율도 줄일 수 있었다.

• 인터넷정보학회논문지
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• 제23권2호
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• pp.1-7
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• 2022

Machine learning (ML) algorithms have been intended to seamlessly collaborate for enabling intelligent networking in terms of massive service differentiation, prediction, and provides high-accuracy recommendation systems. Mobile edge computing (MEC) servers are located close to the edge networks to overcome the responsibility for massive requests from user devices and perform local service offloading. Moreover, there are required lightweight methods for handling real-time Internet of Things (IoT) communication perspectives, especially for ultra-reliable low-latency communication (URLLC) and optimal resource utilization. To overcome the abovementioned issues, this paper proposed an intelligent scheme for traffic steering based on the integration of MEC and lightweight ML, namely support vector machine (SVM) for effectively routing for lightweight and resource constraint networks. The scheme provides dynamic resource handling for the real-time IoT user systems based on the awareness of obvious network statues. The system evaluations were conducted by utillizing computer software simulations, and the proposed approach is remarkably outperformed the conventional schemes in terms of significant QoS metrics, including communication latency, reliability, and communication throughput.

• 한국통신학회논문지
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• 제42권2호
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• pp.460-470
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• 2017

본 논문은 intelligent SSD (iSSD)를 통해 빅 데이터 마이닝을 효과적으로 처리하기 위한 방안에 대해서 소개한다. iSSD는 데이터 전송 비용을 줄이고 데이터가 저장된 장소와 가장 가까운 곳에서 데이터를 처리하기 위해, SSD 내부에 데이터 처리 능력을 부여한 장치이다. 본 논문에서는 먼저, iSSD의 등장 배경 및 효율적인 데이터 처리를 위한 iSSD 구조에 대해 소개한다. 더 나아가, iSSD를 이용하여 데이터 마이닝 알고리즘들을 빠르게 수행하는 방안을 소개한다. 끝으로, iSSD 뿐만 아니라 호스트 CPU, GPU 등 이질 (heterogeneous) 컴퓨팅 자원을 함께 활용하여 데이터 마이닝 알고리즘의 성능을 크게 향상시키는 협업 방안을 소개한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권9호
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• pp.4572-4586
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• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.65-74
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• 2021

The rapid change in gold price is an issue of concern in the global economy and financial markets. Gold has been used as a means for trading and transaction around the world for long period of time and it plays an integral role in monetary, business, commercial and financial activities. More importantly, it is used as economic measure for the global economy and will continue to play an important economic vital role - both locally and globally. There has been an explosive growth in demand for efficient and effective scheme to predict gold price due its volatility and fluctuation. Hence, there is need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper primarily proposed an intelligent based system for predicting and characterizing the gold market trend. The simulation result shows that the proposed intelligent gold price scheme has been able to predict the gold price with high accuracy and precision, and ultimately it has significantly reduced the prediction error when compared to baseline neural network (NN).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.3970-3990
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• 2021

In view of the problems of insufficient data collection and processing capability of multi-source heterogeneous equipment, and low visibility of equipment status at the ship block construction site. A data collection method for ship block construction equipment based on wireless sensor network (WSN) technology and a data processing method based on edge computing were proposed. Based on the Browser/Server (B/S) architecture and the OneNET platform, an online monitoring system for ship block construction equipment was designed and developed, which realized the visual online monitoring and management of the ship block construction equipment status. Not only that, the feasibility and reliability of the monitoring system were verified by using the intelligent tire frame system as the application object. The research of this project can lay the foundation for the ship block construction equipment management and the ship block intelligent construction, and ultimately improve the quality and efficiency of ship block construction.