• Title/Summary/Keyword: position-based wireless sensor network

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Void Less Geo-Routing for Wireless Sensor Networks

  • Joshi, Gyanendra Prasad;Lee, Chae-Woo
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.433-435
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    • 2007
  • Geographic wireless sensor networks use position information for Greedy routing. Greedy routing works well in dense network where as in sparse network it may fail and require the use of recovery algorithms. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costlier for resource constrained position based wireless sensor type networks. In the present work, we propose a Void Avoidance Algorithm (VAA); a novel idea based on virtual distance upgrading that allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forward packet using greedy routing only without recovery algorithm. In VAA, the stuck node upgrades distance unless it finds next hop node which is closer to the destination than itself. VAA guarantees the packet delivery if there is a topologically valid path exists. NS-2 is used to evaluate the performance and correctness of VAA and compared the performance with GPSR. Simulation results show that our proposed algorithm achieves higher delivery ratio, lower energy consumption and efficient path.

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Localization for Cooperative Behavior of Swarm Robots Based on Wireless Sensor Network (무선 센서 네트워크 기반 군집 로봇의 협조 행동을 위한 위치 측정)

  • Tak, Myung-Hwan;Joo, Young-Hoon
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.8
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    • pp.725-730
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    • 2012
  • In this paper, we propose the localization algorithm for the cooperative behavior of the swarm robots based on WSN (Wireless Sensor Network). The proposed method is as follows: First, we measure positions of the L-bot (Leader robot) and F-bots (Follower robots) by using the APIT (Approximate Point In Triangle) and the RSSI (Received Signal Strength Indication). Second, we measure relative positions of the F-bots against the pre-measured position of the L-bot by using trilateration. Then, to revise a position error caused by noise of the wireless signal, we use the particle filter. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

An Estimation Method of Node Position in Wireless Sensor Network (무선 센서 네트워크에서의 노드 위치 추정)

  • Rhim, Chul-Woo;Kim, Young-Rag;Kang, Byung-Wook
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.3
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    • pp.123-129
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    • 2009
  • It is important to locate nodes in the research of wireless sensor network. In this paper, we propose a method that estimates the positions of nodes by using adjacent node information and signal strength in wireless sensor network. With this method, we can find positions of nodes easily because we use Information that nodes have. And we can make a map for all the nodes because we can measure a relative position for an node whose position is not known based on anchor nodes whose positions are already known. In addition, we can confirm whether nodes are placed appropriately. We confirmed that we can locate positions of unknown nodes with small error through verifying the proposed method.

A Grid-based Efficient Routing Protocol for a Mobile Sink in Wireless Sensor Networks

  • Lee, Taekkyeun
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.2
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    • pp.35-43
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    • 2018
  • In this paper, we propose a grid-based efficient routing protocol for a mobile sink in wireless sensor networks. In the proposed protocol, the network is partitioned into grids and each grid has a grid head. For the efficient routing to a mobile sink, the proposed protocol uses a mobile sink representative node to send the data to a mobile sink and grid heads are used as a mobile sink representative node. Furthermore, the proposed protocol uses nodes in the boundary of the center grid as position storage nodes. The position storage nodes store the position of a mobile sink representative node and provide source nodes with it for data delivery. With these features, the proposed protocol can reduce a lot of overhead to update the position information and improve the delay of data delivery to a mobile sink. The proposed protocol performs better than other protocols in terms of the delay and the energy consumption per node in the performance evaluation.

Target Position Estimation using Wireless Sensor Node Signal Processing based on Lifting Scheme Wavelet Transform (리프팅 스킴 웨이블릿 변환 기반의 무선 센서 노드 신호처리를 이용한 표적 위치 추정)

  • Cha, Dae-Hyun;Lee, Tae-Young;Hong, Jin-Keun;Han, Kun-Hui;Hwang, Chan-Sik
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.4
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    • pp.1272-1277
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    • 2010
  • Target detection and tracking wireless sensor network must have various signal processing ability. Wireless sensor nodes need to light weight signal processing algorithm because of energy constraints and communication bandwidth constraints. General signal processing algorithm of wireless sensor node consists of de-noising, received signal strength computation, feature extraction and signal compression. Wireless sensor network life-time and performance of target detection and classification depend on sensor node signal processing. In this paper, we propose energy efficient signal processing algorithm using wavelet transform. The proposed method estimates exact target position.

Localization Estimation Using Artificial Intelligence Technique in Wireless Sensor Networks (WSN기반의 인공지능기술을 이용한 위치 추정기술)

  • Kumar, Shiu;Jeon, Seong Min;Lee, Seong Ro
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.9
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    • pp.820-827
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    • 2014
  • One of the basic problems in Wireless Sensor Networks (WSNs) is the localization of the sensor nodes based on the known location of numerous anchor nodes. WSNs generally consist of a large number of sensor nodes and recording the location of each sensor nodes becomes a difficult task. On the other hand, based on the application environment, the nodes may be subject to mobility and their location changes with time. Therefore, a scheme that will autonomously estimate or calculate the position of the sensor nodes is desirable. This paper presents an intelligent localization scheme, which is an artificial neural network (ANN) based localization scheme used to estimate the position of the unknown nodes. In the proposed method, three anchors nodes are used. The mobile or deployed sensor nodes request a beacon from the anchor nodes and utilizes the received signal strength indicator (RSSI) of the beacons received. The RSSI values vary depending on the distance between the mobile and the anchor nodes. The three RSSI values are used as the input to the ANN in order to estimate the location of the sensor nodes. A feed-forward artificial neural network with back propagation method for training has been employed. An average Euclidian distance error of 0.70 m has been achieved using a ANN having 3 inputs, two hidden layers, and two outputs (x and y coordinates of the position).

CCAJS: A Novel Connect Coverage Algorithm Based on Joint Sensing Model for Wireless Sensor Networks

  • Sun, Zeyu;Yun, Yali;Song, Houbing;Wang, Huihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.10
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    • pp.5014-5034
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    • 2016
  • This paper discusses how to effectively guarantee the coverage and connectivity quality of wireless sensor networks when joint perception model is used for the nodes whose communication ranges are multi-level adjustable in the absence of position information. A Connect Coverage Algorithm Based on Joint Sensing model (CCAJS) is proposed, with which least working nodes are chosen based on probability model ensuring the coverage quality of the network. The algorithm can balance the position distribution of selected working nodes as far as possible, as well as reduce the overall energy consumption of the whole network. The simulation results show that, less working nodes are needed to ensure the coverage quality of networks using joint perception model than using the binary perception model. CCAJS can not only satisfy expected coverage quality and connectivity, but also decrease the energy consumption, thereby prolonging the network lifetime.

Routing Protocol for Wireless Sensor Networks Based on Virtual Force Disturbing Mobile Sink Node

  • Yao, Yindi;Xie, Dangyuan;Wang, Chen;Li, Ying;Li, Yangli
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.4
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    • pp.1187-1208
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    • 2022
  • One of the main goals of wireless sensor networks (WSNs) is to utilize the energy of sensor nodes effectively and maximize the network lifetime. Thus, this paper proposed a routing protocol for WSNs based on virtual force disturbing mobile Sink node (VFMSR). According to the number of sensor nodes in the cluster, the average energy and the centroid factor of the cluster, a new cluster head (CH) election fitness function was designed. At the same time, a hexagonal fixed-point moving trajectory model with the best radius was constructed, and the virtual force was introduced to interfere with it, so as to avoid the frequent propagation of sink node position information, and reduce the energy consumption of CH. Combined with the improved ant colony algorithm (ACA), the shortest transmission path to Sink node was constructed to reduce the energy consumption of long-distance data transmission of CHs. The simulation results showed that, compared with LEACH, EIP-LEACH, ANT-LEACH and MECA protocols, VFMSR protocol was superior to the existing routing protocols in terms of network energy consumption and network lifetime, and compared with LEACH protocol, the network lifetime was increased by more than three times.

Drone Deployment Using Coverage-and-Energy-Oriented Technique in Drone-Based Wireless Sensor Network (드론 기반 무선 센서 네트워크에서의 커버리지와 에너지를 고려한 드론 배치)

  • Kim, Tae-Rim;Song, Jong-Gyu;Im, Hyun-Jae;Kim, Bum-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.8
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    • pp.15-22
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    • 2019
  • Awireless sensor network utilizes small sensors with a low cost and low power being deployed over a wide area. They monitor the surrounding environment and gather the associated information to transmit it to a base station via multi-hop transmission. Most of the research has mainly focused on static sensors that are located in a fixed position. Unlike a wireless sensor network based on static sensors, we can exploit drone-based technologies for more efficient wireless networks in terms of coverage and energy. In this paper, we introduce a transmission power model and a video encoding power model to design the network environment. We also explain a priority mapping scheme, and deploy drones oriented for network coverage and energy consumption. Through our simulations, this research shows coverage and energy improvements in adrone-based wireless sensor network with fewer sensors, compared to astatic sensor-based wireless sensor network. Concretely, coverage increases by 30% for thedrone-based wireless sensor network with the same number of sensors. Moreover, we save an average of 25% with respect to the total energy consumption of the network while maintaining the coverage required.

An Indoor Localization Algorithm based on Improved Particle Filter and Directional Probabilistic Data Association for Wireless Sensor Network

  • Long Cheng;Jiayin Guan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.11
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    • pp.3145-3162
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    • 2023
  • As an important technology of the internetwork, wireless sensor network technique plays an important role in indoor localization. Non-line-of-sight (NLOS) problem has a large effect on indoor location accuracy. A location algorithm based on improved particle filter and directional probabilistic data association (IPF-DPDA) for WSN is proposed to solve NLOS issue in this paper. Firstly, the improved particle filter is proposed to reduce error of measuring distance. Then the hypothesis test is used to detect whether measurements are in LOS situations or NLOS situations for N different groups. When there are measurements in the validation gate, the corresponding association probabilities are applied to weight retained position estimate to gain final location estimation. We have improved the traditional data association and added directional information on the original basis. If the validation gate has no measured value, we make use of the Kalman prediction value to renew. Finally, simulation and experimental results show that compared with existing methods, the IPF-DPDA performance better.