A Low-Cost Anchor Placement Strategy for Range-Free Localization Problems in Wireless Sensor Networks

Abstract

The deployment of anchor nodes (or beacon nodes) is a key element in the design of range-free localization schemes for wireless sensor networks (WSNs). The majority of range-free localization schemes deploy numerous anchor nodes within the monitored region. However, in certain cases (e.g., hazardous areas), it may not be possible to manually install anchor nodes within the monitored region of a WSN. In this study, very few anchor nodes are installed at the boundary of a WSN monitored region to estimate the locations of unknown sensors. The locations of the unknown sensors are estimated based on the minimum hop counts to the anchor nodes. The average hop distance is estimated by applying parameters derived from prior experiments. The simulation results show that the range error of the proposed localization scheme can be as low as 0.15. The localization accuracy, computation cost, and communication cost of the proposed scheme are compared with those of the well-known DV-Hop method.

Node-Gosper Curve-Based Unknown Sensor Localization Using Single Mobile Anchor in Wireless Sensor Networks

“…Consequently, the energy consumption of a mobile anchor that uses a nodeGosper curve as the routing path is less than that of a mobile anchor using the other two curves. Experiment results of the localization simulations showed that the range error of the proposed method was less than 4.6%, which makes the method superior to those involving random, TGS, and Hilbert paths, and far superior to several existing static localization methods for WSNs, such as the methods used in [3][4][5][6].…”

“…When the mobile anchor reaches the turning points of the node-Gosper curve, it broadcasts a location message to the unknown sensors within its communication range. (4) Each unknown sensor estimates its location by a trilateration method (e.g., the trilateration method used in [3]) after it receives at least three messages from the mobile anchor from different locations ( Table 2 is used to estimate the distances between the mobile anchor and the unknown sensors, and the three nearest locations are chosen if messages are received from more than three locations).…”

“…The range error of the proposed method was lesser than 0.0459 (approximately 4.6%), even for the case where three times the standard deviation was added to the real distances between the mobile anchor and the unknown sensors. This result is far superior to those of the localization methods involving static anchor nodes, such as the methods used in [3][4][5][6]. In [3], the authors proposed two static localization methods, named BLM (Bilateration Localization Method) and LSMLM (Least-Squares Multilateration Localization Method).…”

“…This result is far superior to those of the localization methods involving static anchor nodes, such as the methods used in [3][4][5][6]. In [3], the authors proposed two static localization methods, named BLM (Bilateration Localization Method) and LSMLM (Least-Squares Multilateration Localization Method). Both methods used the hop-count technique to estimate the distances between the anchor node and each unknown node.…”

Localization of WSN Using Fuzzy Inference System with Optimized Membership Function by Bat Algorithm

“…The range-free localization methods calculate the distance based on the network connectivity of WSN. In spite of its deficiency in accuracy localization, it boasts simple equipment and lower cost and thus is widely applied [4], such as centroid localization, DV-Hop [5], APIT [6], and MDS-MAP [7] algorithms. In [8], based on the empirical model of signal transmission, the distance between the transmitter and the receiver can be attained by querying the mapping database.…”