An Adaptive Connectivity-based Centroid Algorithm for Node Positioning in Wireless Sensor Networks

In wireless sensor network applications, the position of nodes is randomly distributed following the contour of the observation area. A simple solution without any measurement tools is provided by range-free method. However, this method yields the coarse estimating position of the nodes. In this paper, we propose Adaptive Connectivity-based (ACC) algorithm. This algorithm is a combination of Centroid as range-free based algorithm, and hop-based connectivity algorithm. Nodes have a possibility to estimate their own position based on the connectivity level between them and their reference nodes. Each node divides its communication range into several regions where each of them has a certain weight depends on the received signal strength. The weighted value is used to obtain the estimated position of nodes. Simulation result shows that the proposed algorithm has up to 3 meter error of estimated position on 100x100 square meter observation area, and up to 3 hop counts for 80 meters' communication range. The proposed algorithm performs an average error positioning up to 10 meters better than Weighted Centroid algorithm.Keywords: adaptive, connectivity, centroid, range-free

Connection Between System Parameters and Localization Probability in Network of Randomly Distributed Nodes

This article deals with localization probability in a network of randomly distributed communication nodes contained in a bounded domain. A fraction of the nodes denoted as L-nodes are assumed to have localization information while the rest of the nodes denoted as NL nodes do not. The basic model assumes each node has a certain radio coverage within which it can make relative distance measurements. We model both the case radio coverage is fixed and the case radio coverage is determined by signal strength measurements in a Log-Normal Shadowing environment. We apply the probabilistic method to determine the probability of NL-node localization as a function of the coverage area to domain area ratio and the density of L-nodes. We establish analytical expressions for this probability and the transition thresholds with respect to key parameters whereby marked change in the probability behavior is observed. The theoretical results presented in the article are supported by simulations.Comment: To appear on IEEE Transactions on Wireless Communications, November 200

PEMETAAN POSISI DAN SISTEM NAVIGASI MOBILE ROBOT DALAM RUANG MENGGUNAKAN SENSOR PERPINDAHAN JENIS OPTICAL LASER

Pesatnya perkembangan teknologi robot pada saat ini memungkinkan seseorang untuk melakukan perkembangan teknologi ini. Saat ini perkembangan navigasi untuk mobile robot sangat berkembang pesat, antara lain adalah teknologi line tracer dan odometry dengan menggunakan rotary encoder. Semakin pesatnya teknologi membuat negara-negara berkembang khususnya Indonesia kalah bersaing dengan negara-negara maju lainnya dalam teknologi robot dan ajang-ajang perlombaan tingkat nasional. Pada proyek akhir ini merancang sebuah sistem untuk membentuk sebuah sistem koordinat secara cepat dan pemetaan posisi robot dalam ruang. Titik pusat koordinat berada pada titik awal sebelum robot bergerak. Setiap kali robot bergerak perubahan nilai perpindahan terhadap sumbu x dan sumbu y akan diakumulasikan dengan data sebelumnya. Pengukuran akurasi heading pada robot dilakukan dengan menempatkan dua titik sensor yang berbeda-beda pada badan robot yang dimaksudkan untuk mendapatkan posisi ideal untuk menekan kesalahan pembacaan heading. Pemilihan yang tepat dalam penggunaan sensor akan berpengaruh terhadap hasil yang dicapai. Sensor jenis optical laser merupakan salah satu pilihan untuk mendapatkan hasil yang presisi dari perhitungan yang digunakan. Pada sensor laser dapat digunakan sebagai pengganti dari rotary encoder di mana memiliki sensitivitas yang baik(persen error=7,4%) terhadap alas vinyl, karpet hijau, karpet abu-abu, dan multiplek hitam. Serta pada pencapaian target tidak terpaut jauh(selisih persen error=1.4%) dengan penggunaan rotary encoder pada umumnya

Sparse Localization with a Mobile Beacon Based on LU Decomposition in Wireless Sensor Networks

Node localization is the core in wireless sensor network. It can be solved by powerful beacons, which are equipped with global positioning system devices to know their location information. In this article, we present a novel sparse localization approach with a mobile beacon based on LU decomposition. Our scheme firstly translates node localization problem into a 1-sparse vector recovery problem by establishing sparse localization model. Then, LU decomposition pre-processing is adopted to solve the problem that measurement matrix does not meet the re¬stricted isometry property. Later, the 1-sparse vector can be exactly recovered by compressive sensing. Finally, as the 1-sparse vector is approximate sparse, weighted Cen¬troid scheme is introduced to accurately locate the node. Simulation and analysis show that our scheme has better localization performance and lower requirement for the mobile beacon than MAP+GC, MAP-M, and MAP-M&N schemes. In addition, the obstacles and DOI have little effect on the novel scheme, and it has great localization performance under low SNR, thus, the scheme proposed is robust

Sensor Node Easy Moving Monitoring Region Location Algorithm in Internet of Things

Because of the influence from geographical location, weather and other kinds of circumstances in monitored areas, the shift of the node location and non-uniform distribution, this paper proposed an improved DV-Hop location algorithm. First of all, the package structure by changing the anchor nodes to reduce the number of hops data acquisition phase node data storage; introducing weights to the average hop distance calculation phase the original average hop distance calculation method was improved, and between the node and anchor node distance calculated on the basis of reference anchor nodes are different; then, iterative refinement of node localization stage through the use of multilateral measurement method and Taylor series. Finally, simulation experiment of this method, and compared with the existing methods, the results prove that the method in this paper can greatly reduce positioning errors without adding hardware equipment and network traffic, improve the positioning accuracy, a better solution to the problem of node localization networking monitoring area

Range Free Localization Techniques in Wireless Sensor Networks: A Review

AbstractRecent developments in micro electro mechanical systems (MEMS) technology and wireless communication have propelled the growing applications of wireless sensor networks (WSNs). Wireless sensor network is comprised of large number of small and cheap devices known as sensors. One of the important functions of sensor network is collection and forwarding of data. In most of the applications, it is of much interest to find out the location of the data. This type of information can be obtained by use of localization techniques. So node localization is very crucial to find out the position of node with the help of localization algorithms. Hence, node localization becomes one of the fundamental challenges in WSNs. We make the rigorous reviews on different schemes of localization in sensor networks. On the basis of range measurements, the localization schemes can be broadly classified in two categories such as: range based and range free schemes. The cost and hardware limitation on sensing node preclude the use of range based localization schemes. In most of the sensor network application coarse accuracy is sufficient so range free localization schemes are considered as a substitute to range based schemes. In this paper, the detailed study has been carried out to understand and select the best range free localization algorithm for WSNs. At the end some issues are discussed for future research in the area of localization techniques for WSNs

A Practical Localization Algorithm Based on Wireless Sensor Networks

Many localization algorithms and systems have been developed by means of wireless sensor networks for both indoor and outdoor environments. To achieve higher localization accuracy, extra hardware equipments are utilized by most of the existing localization algorithms, which increase the cost and greatly limit the range of location-based applications. In this paper we present a method which can effectively meet different localization accuracy requirements of most indoor and outdoor location services in realistic applications. Our algorithm is composed of two phases: partition phase, in which the target region is split into small grids and localization refinement phase in which a higher accuracy location can be generated by applying a trick algorithm. A realistic demo system using our algorithm has been developed to illustrate its feasibility and availability. The results show that our algorithm can improve the localization accuracy.Comment: IEEE/ACM Int Conf on Green Computing and Communications (GreenCom), IEEE, Hangzhou, China, December 18-20, 201