• Title/Summary/Keyword: Sensor Node Deployment

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Optimized Charging in Large-Scale Deployed WSNs with Mobile Charger

  • Qin, Zhenquan;Lu, Bingxian;Zhu, Ming;Sun, Liang;Shu, Lei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.12
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    • pp.5307-5327
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    • 2016
  • Restricted by finite battery energy, traditional wireless sensor networks (WSNs) can only maintain for a limited period of time, resulting in serious performance bottleneck in long-term deployment of WSN. Fortunately, the advancement in the wireless energy transfer technology provides a potential to free WSNs from limited energy supply and remain perpetual operational. A mobile charger called wireless charging vehicle (WCV) is employed to periodically charge each sensor node and keep its energy level above the minimum threshold. Aiming at maximizing the ratio of the WCV's vocation time over the cycle time as well as guaranteeing the perpetual operation of networks, we propose a feasible and optimal solution to this issue within the context of a real-time large-scale deployed WSN. First, we develop two different types of charging cycles: initialization cycles and renewable cycles and give relevant algorithms to construct these two cycles for each sensor node. We then formulate the optimization problem into an optimal construction algorithm and prove its correctness through theoretical analysis. Finally, we conduct extensive simulations to demonstrate the effectiveness of our proposed algorithms.

A Study on Intelligent Edge Computing Network Technology for Road Danger Context Aware and Notification

  • Oh, Am-Suk
    • Journal of information and communication convergence engineering
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    • v.18 no.3
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    • pp.183-187
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    • 2020
  • The general Wi-Fi network connection structure is that a number of IoT (Internet of Things) sensor nodes are directly connected to one AP (Access Point) node. In this structure, the range of the network that can be established within the specified specifications such as the range of signal strength (RSSI) to which the AP node can connect and the maximum connection capacity is limited. To overcome these limitations, multiple middleware bridge technologies for dynamic scalability and load balancing were studied. However, these network expansion technologies have difficulties in terms of the rules and conditions of AP nodes installed during the initial network deployment phase In this paper, an intelligent edge computing IoT device is developed for constructing an intelligent autonomous cluster edge computing network and applying it to real-time road danger context aware and notification system through an intelligent risk situation recognition algorithm.

A Study on the Standard-interfaced Smart Farm Supporting Non-Standard Sensor and Actuator Nodes (비표준 센서 및 구동기 노드를 지원하는 표준사양 기반 스마트팜 연구)

  • Bang, Dae Wook
    • Journal of Information Technology Services
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    • v.19 no.3
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    • pp.139-149
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    • 2020
  • There are now many different commercial weather sensors suitable for smart farms, and various smart farm devices are being developed and distributed by companies participating in the government-led smart farm expansion project. However, most do not comply with standard specifications and are therefore limited to use in smart farms. This paper proposed the connecting structure of operating non-standard node devices in smart farms following standard specifications supporting smart greenhouse. This connecting structure was proposed as both a virtual node module method and a virtual node wrapper method. In addition, the SoftFarm2.0 system was experimentally operated to analyze the performance of the implementation of the two methods. SoftFarm2.0 system complies with the standard specifications and supports non-standard smart farm devices. According to the analysis results, both methods do not significantly affect performance in the operation of the smart farm. Therefore, it would be good to select and implement the method suitable for each non-standard smart farm device considering environmental constraints such as power, space, distance of communication between the gateway and the node of the smart farm, and software openness. This will greatly contribute to the spread of smart farms by maximizing deployment cost savings.

Performance Evaluation of CoAP-based Internet-of-Things System (CoAP 기반 사물인터넷 시스템 성능평가)

  • Choo, Young Yeol;Ha, Yong Jun;Son, Soo Dong
    • Journal of Korea Multimedia Society
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    • v.19 no.12
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    • pp.2014-2023
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    • 2016
  • Web presence is one of the key issues for extensive deployment of Internet-of-Things (IoT). An obstacle to overcome for Web presence is relatively low computing power of IoT devices. In this paper, we present implementation of an IoT platform based on Constrained Application Protocol (CoAP) which is a web transfer protocol proposed by Internet Engineering Task Force (IETF) for the low performance IoT devices such as Wireless Sensor Network (WSN) nodes and micro-controllers. To qualify the performance of CoAP-based IoT system for such an application as smart grid, we designed a test platform consisting of Raspberry Pi2, Kmote WSN node and a desktop PC. Using open source softwares, CoAP was implemented on top of the platform. Leveraging the GET command defined at CoAP specification, performance of the system was measured in terms of round-trip time (RTT) from web application to the Kmote sensor node. To investigate abnormal cases among the test results, hop-by-hop delays were measured to analyze resulting data. The average response time of CoAP-based communication except the abnormal data was reduced by 23% smaller than the previous research result.

Adaptive Success Rate-based Sensor Relocation for IoT Applications

  • Kim, Moonseong;Lee, Woochan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3120-3137
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    • 2021
  • Small-sized IoT wireless sensing devices can be deployed with small aircraft such as drones, and the deployment of mobile IoT devices can be relocated to suit data collection with efficient relocation algorithms. However, the terrain may not be able to predict its shape. Mobile IoT devices suitable for these terrains are hopping devices that can move with jumps. So far, most hopping sensor relocation studies have made the unrealistic assumption that all hopping devices know the overall state of the entire network and each device's current state. Recent work has proposed the most realistic distributed network environment-based relocation algorithms that do not require sharing all information simultaneously. However, since the shortest path-based algorithm performs communication and movement requests with terminals, it is not suitable for an area where the distribution of obstacles is uneven. The proposed scheme applies a simple Monte Carlo method based on relay nodes selection random variables that reflect the obstacle distribution's characteristics to choose the best relay node as reinforcement learning, not specific relay nodes. Using the relay node selection random variable could significantly reduce the generation of additional messages that occur to select the shortest path. This paper's additional contribution is that the world's first distributed environment-based relocation protocol is proposed reflecting real-world physical devices' characteristics through the OMNeT++ simulator. We also reconstruct the three days-long disaster environment, and performance evaluation has been performed by applying the proposed protocol to the simulated real-world environment.

A Secure Data Transmission Mechanism for Sensor Network Communication (센서네트워크 통신을 위한 안전한 데이터 전송 기법)

  • Doh, In-Shil;Chae, Ki-Joon
    • The KIPS Transactions:PartC
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    • v.14C no.5
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    • pp.403-410
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    • 2007
  • For reliable sensor network communication, secure data transmission mechanisms are necessary. In our work, for secure communication, we cluster the network field in hexagonal shape and deploy nodes according to Gaussian distribution. After node deployment, clusterheads and gateway nodes in each cluster play the role of aggregating and delivering the sensed data with suity information all the way to the base station. Our mechanism decreases the overhead and provides food performance. It also has resilience against various routing attacks.

A Smart Sensor Device Management System in Nano-Q+ (Nano-Q+에서 스마트 센서 디바이스 관리 시스템)

  • Kim, Bum-Suk;So, Sun-Sup;Kim, Byeong-Ho;Eun, Seong-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.1
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    • pp.31-39
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    • 2008
  • Sensor Node OS should support unified API and efficient sensor device management system to overcome the diversity of sensors and actuators. However, conventional OSs like Tiny-OS and Nano-Q+ do not. In this paper, we propose a sensor device driver management system that present application programmers with unified API and easy deployment of sensors. When a sensor is deployed in our device management system, the device driver is downloaded. This scheme differs from traditional OS like SOS in that only sensor device driver is downloaded, not the whole application image. We designed and implemented the system into Nano-Q+. We described the comparison with other OSs and showed that our system obtains the considerable speedup of downloading.

RRA : Ripple Routing Algorithm Considering the RF-Coverage of the node in WSN (RRA : 무선센서 네트워크에서 노드의 통신영역을 고려한 랜덤 배치 고정형 라우팅 알고리즘)

  • Lee, Doo-Wan;Kim, Min-Je;Jang, Kyung-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.10a
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    • pp.820-823
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    • 2011
  • WSN is composed of a lot of small sensors with the limited hardware resources. In WSN, at the initial stage, sensor nodes are randomly deployed over the region of interest, and self-configure the clustered networks by grouping a bunch of sensor nodes and selecting a cluster header among them. In this paper, we propose a self-configuration routing protocol for WSN, which consists of step-wise ripple routing algorithm for initial deployment, effective joining of sensor nodes. RRA is search node in RF-coverage of each node, which result in fast network connection, reducing overall power consumption, and extending the lifetime of network.

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Energy-Effective Low-Cost Small Mobile Robot Implementation for Mobile Sensor Network (모바일 센서 네트워크를 위한 에너지 효율적이고 경제적인 소형 이동 로봇의 개발)

  • Kim, Hong-Jun;Kim, Byung-Kook
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.3
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    • pp.284-294
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    • 2008
  • In this paper, we describe an implementation of small mobile robot that can be used at research and application of mobile sensor networking. This robot that will constitute the sensor network, as a platform of multi-robot system for each to be used as sensor node, has to satisfy restrictions in many aspects in order to perform sensing, communication protocol, and application algorithms. First, the platform must be designed with a robust structure and low power consumption since its maintenance after deployment is difficult. Second, it must have flexibility and modularity to be used effectively in any structure so that it can be used in various applications. Third, it must support the technique of wireless network for ubiquitous computing environment. At last, to let many nodes be scattered, it must be cost-effective and small. Considering the above restrictions of the mobile platform for sensor network, we designed and implemented robots control the current of actuator by using additional circuit for power efficiency. And we chose MSP430 as MCU, CC2420 as RF transceiver, and etc, that have the strength in the aspect of power. For flexibility and modularity, the platform has expansion ports. The results of experiments are described to show that this robot can act as sensor node by RF communication process with Zigbee standard protocol, execute the navigation process with simple obstacle avoidance and the moving action with RSSI(Received Signal Strength Indicator), operate at low-power, and be made with approx. $100.

Instruction-Level Power Estimator for Sensor Networks

  • Joe, Hyun-Woo;Park, Jae-Bok;Lim, Chae-Deok;Woo, Duk-Kyun;Kim, Hyung-Shin
    • ETRI Journal
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    • v.30 no.1
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    • pp.47-58
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    • 2008
  • In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

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