Localization Algorithm for Mobile Sensor Nodes Using 3D Space in Wireless Sensor Network (original) (raw)
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International Journal of Engineering Research and Technology (IJERT), 2014
https://www.ijert.org/range-based-localization-scheme-for-3d-wireless-sensor-network-using-joint-distance-and-angle-informationa-brief-review https://www.ijert.org/research/range-based-localization-scheme-for-3d-wireless-sensor-network-using-joint-distance-and-angle-informationa-brief-review-IJERTV3IS061388.pdf This review paper describes range based 3D localization algorithm for wireless sensor network to satisfy the practical needs. The mentioned algorithm is anchor free, scalable and provides accurate physical position. To estimate ranges between neighbors both distance and direction measurement technique is used. Based on this information a global network with wide coordinate system is developed using local coordinate system leads to absolute position of nodes. Simulation results have shown that proposed algorithm achieves good tradeoff between localization percentage and precision when node degree equals 12 or around.
Improved 3D localization algorithm for large scale wireless sensor networks
Wireless Networks
As localization represents the main core of various wireless sensor network applications, several localization algorithms have been suggested in wireless sensor network research. In this article, we put forward an iterative bounding box algorithm enhanced by a Kalman filter to refine the unknown node’s estimated position. In fact, several research efforts are currently in progress to extend the 2D positioning algorithm in WSNs to 3D that reflects reality and the most practical applications. Subsequently, we replace a large number of GPS-equipped anchors with a single mobile anchor. In our studies, we consider the type of range-free sensor network exploiting the wireless sensors connectivity. We assess the performance of our algorithm using exhaustive experiments on several isotropic and anisotropic topologies. Our proposed algorithm can fulfill the joint goals of algorithm transparency and accuracy for various scenarios by evaluating parameters such as localization accuracy whilst c...
3D Localization for Mobile Node in Wireless Sensor Network
Wireless Communications and Mobile Computing
Wireless sensor network (WSN) is an emerging technology that can detect, collect, and transmit information in a specific unknown area in an unknown environment. It is currently playing an increasingly important role in the fields of national defense, medical and health, and daily life. WSN node location information is extremely important in many WSN applications. The data information collected by WSN is developed based on known node location information. The node location is one of the important issues in WSNs. Location information is very important for wireless sensors. A WSN without sensor node location information is meaningless because almost all WSN applications need to know node location information, such as animal populations, tracking research, early warning of building fires, management of goods in warehouses, and traffic monitoring systems. Several research works are underway to expand the 2D positioning algorithm in WSN to 3D regardless of the deployment structure of sens...
3D Localization Algorithms for Wireless Sensor Networks
Wireless sensor networks have a great impact on long time monitoring applications (environment monitoring, security surveillance, habitat monitoring etc.) but its potential is yet to be discovered, where it can be deployed in time critical situations when disaster happens. There is a significant gap between existing applications of sensor networks and the requirement of applications supporting rescue operations that involves the catastrophe of human lives. As we are dealing with the human lives here, we can't just rely on the localization schemes that depend upon the connectivity information (range-free) algorithms only. Further, rescue operations are carried out in highly noisy environments, so distance based (range-based) localization algorithms generate high error in distance measurements. An efficient algorithm is needed that can measure the location of the sensor nodes near to the living being or being attached to them in 3-D space with a high accuracy. To achieve such kind of accuracy a combination of both the strategies is required. Further, the algorithms should be efficient and less resource consuming for getting executed on sensor nodes with low processing power. This research proposes an algorithm which incorporates both the range-based and rangefree strategies.
3-D Localization in Wireless Sensor Network
Wireless sensor networks have a great impact on long time monitoring applications (environment monitoring, security surveillance, habitat monitoring etc.) but its potential is et to be discovered, where it can be deployed in time critical situations when disaster happens. There is a significant gap between existing applications of sensor networks and the requirement of applications supporting rescue operations that involves the catastrophe of human lives. As we are dealing with the human lives here, we can't just rely on the localization schemes that depend upon the connectivity information (range-free) algorithms only. Further, rescue operations are carried out in highly noisy environments, so distance based (range-based) localization algorithms generate high error in distance measurements. An efficient algorithm is needed that can measure the location of the sensor nodes near to the living being or being attached to them in 3-D space with a high accuracy. To achieve such kind ...
IJERT-Node localization using 3d coordinates in wireless sensor networks
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/node-localization-using-3d-coordinates-in-wireless-sensor-networks https://www.ijert.org/research/node-localization-using-3d-coordinates-in-wireless-sensor-networks-IJERTV2IS110669.pdf Sensor network provide heterogeneous information through the physical world. Sensor nodes are large in numbers; it gives the location information from where the data is taken. The location information is calculated through localization algorithm. The algorithm is process on every node for getting exact location of every fixed or mobile node devices. It calculate it position every time when the data is send through it. For localization many algorithm are introduced with the basis of two dimensions, this paper based on Ring Overlapping Based on Comparison of Received Signal Strength Indicator (ROCRSSI) algorithm that work on three dimensions coordinates. ROCRSSI is isotropic in nature so it provides equal range to all nodes, it does not effect from signal fading. Our work to implements this algorithm with fingerprint method for finding node position.
Information Fusion, 2014
Node localization is very important in Wireless Sensor Network (WSN) and distance estimation between pairs of nodes is the prerequisite for localization and thus the applicability of the reported events. The paper proposes a novel distance estimation algorithm to estimate distances of each node to every other node in the network. The main contribution of the paper is the definition of a dissimilarity matrix representing the distance of each node to every other node in the network. MDS based localization algorithm is used to determine coordinates of the node in a local coordinate system and Helmert Transformation is used to convert the local coordinates of the node into a global coordinate system. The effect of various parameters affecting the performance of proposed algorithm is also presented in the paper. Finally, the efficiency of the proposed algorithm is established through the simulation results.
Nodes Localization in 3D Wireless Sensor Networks Based on Multidimensional Scaling Algorithm
In the recent years, there has been a huge advancement in wireless sensor computing technology. Today, wireless sensor network (WSN) has become a key technology for different types of smart environment. Nodes localization in WSN has arisen as a very challenging problem in the research community. Most of the applications for WSN are not useful without a priory known nodes positions. Adding GPS receivers to each node is an expensive solution and inapplicable for indoor environments. In this paper, we implemented and evaluated an algorithm based on multidimensional scaling (MDS) technique for three-dimensional (3D) nodes localization in WSN using improved heuristic method for distance calculation. Using extensive simulations we investigated our approach regarding various network parameters. We compared the results from the simulations with other approaches for 3D-WSN localization and showed that our approach outperforms other techniques in terms of accuracy.
Effcient and Accurate Range-based Sensor Network Localization
Procedia Computer Science, 2012
Localization is defined as the problem of determining the geographical locations of nodes in a wireless ad hoc or sensor network. Networks typically have some nodes (called seeds) that know their locations (using GPS or other means). Other (non-seed) nodes compute their locations by exchanging messages with nodes within their radio range.
Geometrical Localization Algorithm for 3-D Wireless Sensor Networks
The issue of localization has been addressed in many research areas such as vehicle navigation systems, virtual reality systems, user localization in wireless sensor networks (WSNs). In this paper, we have proposed an efficient range-free localization algorithm: Geometrical Localization Algorithm (GLA) for large scale three dimensional WSNs. GLA uses moving anchors to localize static sensors. GLA consists of beacon message selection, circular cross section selection. Three beacon messages are used to compute the center of circular cross section using vector method and perpendicular bisector method. The static sensors are localized with help of the center of circular cross section and geometrical rules for sphere. GLA is simulated in SINALGO software and results have been compared with existing methods namely chord selection and point localization. GLA outperforms both the compared methods in terms of average localization time and beacon overhead.