• 한국시뮬레이션학회논문지
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• 제28권2호
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• pp.97-105
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• 2019

전술 에드혹 환경은 개별 지상 노드 간 분산적인 형태의 자율망으로 구성되므로 네트워크의 생존 가능성 및 유연성 측면에서 효과적이나 기동 간 통신 시 제한된 출력, 지형특성, 이동성 등의 제약으로 인하여 잦은 링크 단절 및 음영지역이 발생할 수 있다. 반면 위성 통신망은 지상 기동 망에 비해 지형특성과 이동성을 극복한 광역 무선 링크를 제공할 수 있는 장점이 있으나 상대적으로 한정된 대역폭 및 고지연 특성의 망이다. 미래 전장 환경에서 기존의 단독망 형태의 제약사항을 극복하고 지휘 통제 통신의 신뢰성 및 효율성을 높이기 위해서는 이종망 게이트웨이(Heterogeneous network gateway, HNG)를 중심으로 위성 통신망을 포함한 다계층 통합 네트워크 구조가 요구된다. 본 논문에서는 전술 에드혹 환경에서 위성-전술 에드혹 망을 통합적으로 고려하고 유통되는 임무 트래픽의 플로우 특성에 기반하여 신뢰성 있는 데이터 전달이 가능한 이종망 게이트웨이 구조 및 세부 알고리즘을 제시한다. 시뮬레이션은 네트워크 수준의 시뮬레이터인 Riverbed Modeler를 활용하여 제시하는 구조의 유효성을 확인하였다.

• Journal of Communications and Networks
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• 제4권4호
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• pp.282-291
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• 2002

3GPP (Third Generation Partnership Project) is defining UMTS (Universal Mobile Telecommunication System) releases which span the transition from GSM/UMTS coexistence to All-IP UMTS networks. The deployment of an UMTS network depends, in the first place, on the intended service offerings and the release an operator chooses to start service with. Other key decisions in-fluencing UMTS deployment relate to the timing of the functional enhancements and capacity increases along the economic life of the network. This paper gives an overview on the architectural and technical options for UMTS deployment. It also outlines the methodology underlying the business plan aimed at estimating the returns from investments in the UMTS infrastructure, thus helping to tune operators’ strategies for UMTS deployment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.159-177
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• 2018

Participatory sensing is becoming popular and has shown its great potential in data acquisition for ambient assisted living. In this paper, we propose an incentive mechanism in participatory sensing for ambient assisted living, which benefits both the platform and the mobile devices that participated in the sensing task. Firstly, we analyze the profit of participant and platform, and a Stackelberg game model is formulated. The model takes privacy, reputation, power state and quality of data into consideration, and aims at maximizing the profit for both participant and publisher. The discussion of properties of the game show that there exists an unique Stackelberg equilibrium. Secondly, two algorithms are given: one describes how to reach the Stackelberg equilibrium and the other presents the procedures of employing the incentive strategy. Finally, we conduct simulations to evaluate the properties and effectiveness of the proposed mechanism. Simulation results show that the proposed incentive mechanism works well, and the participants and the publisher will be benefitted from it. With the mechanism, the total amount of sensory data can be maximized and the quality of the data can be guaranteed effectively.

• 한국정보과학회논문지:정보통신
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• 제29권3호
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• pp.224-232
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• 2002

본 논문에서는 ALICE(Architecture for Location Independent CORBA Environment) 구조에 기반한 Mobile CORBA 환경에서 이동 게이트웨이(MG)간의 핸드오프에 따른 문제점을 해결하기 위한 경로 최적화 핸드오프를 제안한다. 이동 호스트가 빠르게 움직이고, 처리시간이 긴 작업의 경우에 핸드오프로 인한 MG간의 긴 터널링 체인이 발생할 수 있고, 이로 인해 메시지들이 불필요한 몇 단계의 라우팅과 재전송 과정을 거치게 된다. 이렇게 비효율적인 경로를 통해서 메시지 전송이 이루어지는 것은 여러가지 제약조건을 가지는 무선망의 환경에서는 커다란 장애요소가 될 수 있다. 본 논문에서 제안한 새로운 핸드오프 알고리즘은 핸드오프시 관련된 MG들이 이동성에 관한 정보를 메시지(binding update message) 형태로 받아서 캐쉬로 관리하도록 한다. 그 결과 핸드오프 이후의 관련 MG는 캐쉬를 이용하여 이동 호스트와 최적의 경로로 통신이 가능하다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.854-859
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• 2002

Location Based Services, or LBS refers to value-added service by processing information utilizing mobile user location. With the rapidly increasing wireless internet subscribers and world LBS market, the various location based applications are introduced such as buddy finder, proximity and security services. As the killer application of the wireless internet, the LBS has preconsidered technology about location determination technology, LBS middleware server for various application, and diverse contents processing technology. This paper describes the open architecture for LBS platform ensuring interoperability among the wireless networks and various location-based application services and the functional requirements for the LBS platform. The LBS platform in a narrow sense provides a standard interfaces for location management and network management for location services as follows, positioning (location acquisition through network or/and handset), location managing, location based functions, profile management, authentication and security, location based billing, information roaming between carriers and the system monitoring independent to specific network or ISP/CPs(Content Providers).

• Journal of Communications and Networks
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• 제9권3호
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• pp.296-311
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• 2007

Mobile multi-robot teams are useful in many critical applications such as search and rescue. Explicit communication among robots in such mobile multi-robot teams is useful for the coordination of such teams as well as exchanging data. Since many applications for mobile robots involve scenarios in which communication infrastructure may be damaged or unavailable, mobile robot teams frequently need to communicate with each other via ad hoc networking. In such scenarios, low-overhead and energy-efficient routing protocols for delivering messages among robots are a key requirement. Two important primitives for communication are essential for enabling a wide variety of mobile robot applications. First, unicast communication (between two robots) needs to be provided to enable coordination and data exchange. Second, in many applications, group communication is required for flexible control, organization, and management of the mobile robots. Multicast provides a bandwidth-efficient communication method between a source and a group of robots. In this paper, we first propose and evaluate two unicast routing protocols tailored for use in ad hoc networks formed by mobile multi-robot teams: Mobile robot distance vector (MRDV) and mobile robot source routing (MRSR). Both protocols exploit the unique mobility characteristics of mobile robot networks to perform efficient routing. Our simulation study show that both MRDV and MRSR incur lower overhead while operating in mobile robot networks when compared to traditional mobile ad hoc network routing protocols such as DSR and AODV. We then propose and evaluate an efficient multicast protocol mobile robot mesh multicast (MRMM) for deployment in mobile robot networks. MRMM exploits the fact that mobile robots know what velocity they are instructed to move at and for what distance in building a long lifetime sparse mesh for group communication that is more efficient. Our results show that MRMM provides an efficient group communication mechanism that can potentially be used in many mobile robot application scenarios.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (3)
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• pp.106-108
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• 2002

기존의 단말에서는 외부노드와 최초의 통신 시에 자신이 속해있는 HA(home Agent) 하나만을 거쳐간다. 그러나 이동망에서는 MR(Mobile Router) network의 하단에 다른 HA에 속해있는 이동 서브넷이 방문했을 때의 시나리오가 추가로 고려되어야 한다. 그런데 CN(Correspondance Node)과 방문한 네트워크의 노드와의 통신에서 전송된 패킷이 인터넷으로 연결하는 가장 상단의 이동망으로부터 자신이 속해있는 망까지 경로 상에 위치한 각각의 해당 HA를 모두 방문하여 우회하는 경로가 이루어지는 문제점이 있다. 따라서 본 논문에서는 이 문제의 해결을 위해 라우팅을 효율적으로 지원할 수 있는 MTA(Mobile Transmission Agent)를 제안한다.

• 제어로봇시스템학회논문지
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• 제5권2호
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• pp.180-188
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• 1999

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which complex global intelligence form from simple local interactions. Here, we propose an architecture of neural network learning with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigate in a group. As the results of the simulations, the optimum weight is obtained in real time, which not only prevent the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.

• Smart Structures and Systems
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• 제29권1호
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• pp.141-151
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• 2022

In recent years, the industry and research communities have focused on developing autonomous crack inspection approaches, which mainly include image acquisition and crack detection. In these approaches, mobile devices such as cameras, drones or smartphones are utilized as sensing platforms to acquire structural images, and the deep learning (DL)-based methods are being developed as important crack detection approaches. However, the process of image acquisition and collection is time-consuming, which delays the inspection. Also, the present mobile devices such as smartphones can be not only a sensing platform but also a computing platform that can be embedded with deep neural networks (DNNs) to conduct on-site crack detection. Due to the limited computing resources of mobile devices, the size of the DNNs should be reduced to improve the computational efficiency. In this study, an architecture called pruned crack recognition network (PCR-Net) was developed for the detection of structural cracks. A dataset containing 11000 images was established based on the raw images from bridge inspections. A pruning method was introduced to reduce the size of the base architecture for the optimization of the model size. Comparative studies were conducted with image processing techniques (IPTs) and other DNNs for the evaluation of the performance of the proposed PCR-Net. Furthermore, a modularly designed framework that integrated the PCR-Net was developed to realize a DL-based crack detection application for smartphones. Finally, on-site crack detection experiments were carried out to validate the performance of the developed system of smartphone-based detection of structural cracks.

• ETRI Journal
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• 제45권4호
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• pp.666-677
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• 2023

In the last few years, convolutional neural networks (CNNs) have demonstrated good performance while solving various computer vision problems. However, since CNNs exhibit high computational complexity, signal processing is performed on the server side. To reduce the computational complexity of CNNs for edge computing, a lightweight algorithm, such as a MobileNet, is proposed. Although MobileNet is lighter than other CNN models, it commonly achieves lower classification accuracy. Hence, to find a balance between complexity and accuracy, additional hyperparameters for adjusting the size of the model have recently been proposed. However, significantly increasing the number of parameters makes models dense and unsuitable for devices with limited computational resources. In this study, we propose a novel MobileNet architecture, in which the number of parameters is adaptively increased according to the importance of feature maps. We show that our proposed network achieves better classification accuracy with fewer parameters than the conventional MobileNet.