• 제목/요약/키워드: embedded computing

검색결과 537건 처리시간 0.026초

유비쿼터스 컴퓨팅을 위한 센서 디바이스 Plug & Play (Sensor Device Plug & Play for Ubiquitous Computing)

  • 박정선;은성배;윤현주
    • 대한임베디드공학회논문지
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    • 제7권3호
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    • pp.151-156
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    • 2012
  • When mounting the sensor device in the way of Plug&Play, sensor device drivers need to be loaded and linked dynamically. Since a sensor node platform is based on small 8 bit MCU, dynamic loading and linking technique used in Windows and Linux can not be applied. In this paper, we present how to link and load dynamically sensor device drivers for sensor device Plug&Play. We implement a prototype and evaluate it to make sure that there is no performance degradation like sensor device driver connection speed and memory usage. Connection speed overhead increases to 0.2ms. Memory usage overhead increases to hundreds byte. It shows that there is no heavy influence in running the actual program.

Q-learning 모델을 이용한 IoT 기반 주차유도 시스템의 설계 및 구현 (Design and Implementation of Parking Guidance System Based on Internet of Things(IoT) Using Q-learning Model)

  • 지용주;최학희;김동성
    • 대한임베디드공학회논문지
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    • 제11권3호
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    • pp.153-162
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    • 2016
  • This paper proposes an optimal dynamic resource allocation method in IoT (Internet of Things) parking guidance system using Q-learning resource allocation model. In the proposed method, a resource allocation using a forecasting model based on Q-learning is employed for optimal utilization of parking guidance system. To demonstrate efficiency and availability of the proposed method, it is verified by computer simulation and practical testbed. Through simulation results, this paper proves that the proposed method can enhance total throughput, decrease penalty fee issued by SLA (Service Level Agreement) and reduce response time with the dynamic number of users.

센서 융합기반의 추측항법을 통한 야지 주행 이동로봇의 위치 추정 및 제어 (Localization and Control of an Outdoor Mobile Robot Based on an Estimator with Sensor Fusion)

  • 전상운;정슬
    • 대한임베디드공학회논문지
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    • 제4권2호
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    • pp.69-78
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    • 2009
  • Localization is a very important technique for the mobile robot to navigate in outdoor environment. In this paper, the development of the sensor fusion algorithm for controlling mobile robots in outdoor environments is presented. The multi-sensorial dead-reckoning subsystem is established based on the optimal filtering by first fusing a heading angle reading data from a magnetic compass, a rate-gyro, and two encoders mounted on the robot wheels, thereby computing the dead-reckoned location. These data and the position data provided by a global sensing system are fused together by means of an extended Kalman filter. The proposed algorithm is proved by simulation studies of controlling a mobile robot controlled by a backstepping controller and a cascaded controller. Performances of each controller are compared.

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센서네트워크를 위한 Dual Priority Scheduling 기반 시스템 소프트웨어 모델링 (System Software Modeling Based on Dual Priority Scheduling for Sensor Network)

  • 황태호;김동순;문연국;김성동;김정국
    • 대한임베디드공학회논문지
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    • 제2권4호
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    • pp.260-273
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    • 2007
  • The wireless sensor network (WSN) nodes are required to operate for several months with the limited system resource such as memory and power. The hardware platform of WSN has 128Kbyte program memory and 8Kbytes data memory. Also, WSN node is required to operate for several months with the two AA size batteries. The MAC, Network protocol, and small application must be operated in this WSN platform. We look around the problem of memory and power for WSN requirements. Then, we propose a new computing model of system software for WSN node. It is the Atomic Object Model (AOM) with Dual Priority Scheduling. For the verification of model, we design and implement IEEE 802.15.4 MAC protocol with the proposed model.

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Analysis of Reduced-Width Truncated Mitchell Multiplication for Inferences Using CNNs

  • Kim, HyunJin
    • 대한임베디드공학회논문지
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    • 제15권5호
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    • pp.235-242
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    • 2020
  • This paper analyzes the effect of reduced output width of the truncated logarithmic multiplication and application to inferences using convolutional neural networks (CNNs). For small hardware overhead, output width is reduced in the truncated Mitchell multiplier, so that fractional bits in multiplication output are minimized in error-resilient applications. This analysis shows that when reducing output width in the truncated Mitchell multiplier, even though worst-case relative error increases, average relative error can be kept small. When adopting 8 fractional bits in multiplication output in the evaluations, there is no significant performance degradation in target CNNs compared to existing exact and original Mitchell multipliers.

내장형 정보기기를 위한 플래시 메모리 기반 색인 기법 (Flash Memory based Indexing Scheme for Embedded Information Devices)

  • 변시우;노창배;허문행
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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    • pp.267-269
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    • 2006
  • Recently, flash memories are one of best media to support portable computer's storages in mobile computing environment. The features of non-volatility, low power consumption, and fast access time for read operations are sufficient grounds to support flash memory as major database storage components of portable computers. However, we need to improve traditional Indexing scheme such as B-Tree due to the relatively slow characteristics of flash operation as compared to RAM memory. In order to achieve this goal, we devise a new indexing scheme called F-Tree. F-Tree improves tree operation performance by compressing pointers and keys in tree nodes and rewriting the nodes without a slow erase operation in node insert/delete processes.

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개선된 유비쿼터스 시스템 (An Improved Ubiquitous System)

  • 박춘명
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2013년도 춘계학술대회
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    • pp.931-932
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    • 2013
  • 본 논문에서는 21세기 지식기반의 정보화사회를 구현하기위한 한가지 방방에 대해 논의하였다. 제안한 방법은 디지털정보를 멀티미디어 형식의 정보로 내장시키고 이를 RFID/USN과 연동하여 유비쿼터스 시스템을 구현함을 보였다. 제안한 방법이 구현된다면 지금까지와는 다른 새로운 인간생활의 패러다임을 가져올 것으로 기대된다.

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바닥 특징점을 사용하는 실내용 정밀 고속 자율 주행 로봇을 위한 싱글보드 컴퓨터 솔루션 (An Embedded Solution for Fast Navigation and Precise Positioning of Indoor Mobile Robots by Floor Features)

  • 김용년;서일홍
    • 로봇학회논문지
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    • 제14권4호
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    • pp.293-300
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    • 2019
  • In this paper, an Embedded solution for fast navigation and precise positioning of mobile robots by floor features is introduced. Most of navigation systems tend to require high-performance computing unit and high quality sensor data. They can produce high accuracy navigation systems but have limited application due to their high cost. The introduced navigation system is designed to be a low cost solution for a wide range of applications such as toys, mobile service robots and education. The key design idea of the system is a simple localization approach using line features of the floor and delayed localization strategy using topological map. It differs from typical navigation approaches which usually use Simultaneous Localization and Mapping (SLAM) technique with high latency localization. This navigation system is implemented on single board Raspberry Pi B+ computer which has 1.4 GHz processor and Redone mobile robot which has maximum speed of 1.1 m/s.

퍼스널 클라우드 서비스를 위한 임의의 단말간 컨텐츠 동기화 방법 (The Method of Data Synchronization Among Devices for Personal Cloud Services)

  • 최은정;이전우
    • 대한임베디드공학회논문지
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    • 제6권6호
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    • pp.377-382
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    • 2011
  • This paper describes the method of data synchronization among devices for personal cloud services. Existing data synchronization for mobile devices is based on a central server to mobile devices or a PC to a mobile device. However, the purpose of this paper is to share user data in heterogeneous environments, without depending on central server. This technology can be applied to synchronize personal data between a device and a personal cloud storage for personal cloud services. The ad hoc synchronization needs a sync agent service discovery module, a user authentication module, a network adapter, and an application data synchronization module. The method described in this paper is better than existing synchronization technology based on client-server in availability, performance, scalability quality attributes.

3차원 합성곱 신경망 기반 향상된 스테레오 매칭 알고리즘 (Enhanced Stereo Matching Algorithm based on 3-Dimensional Convolutional Neural Network)

  • 왕지엔;노재규
    • 대한임베디드공학회논문지
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    • 제16권5호
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    • pp.179-186
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    • 2021
  • For stereo matching based on deep learning, the design of network structure is crucial to the calculation of matching cost, and the time-consuming problem of convolutional neural network in image processing also needs to be solved urgently. In this paper, a method of stereo matching using sparse loss volume in parallax dimension is proposed. A sparse 3D loss volume is constructed by using a wide step length translation of the right view feature map, which reduces the video memory and computing resources required by the 3D convolution module by several times. In order to improve the accuracy of the algorithm, the nonlinear up-sampling of the matching loss in the parallax dimension is carried out by using the method of multi-category output, and the training model is combined with two kinds of loss functions. Compared with the benchmark algorithm, the proposed algorithm not only improves the accuracy but also shortens the running time by about 30%.