Study of a Cost-Effective Localization Algorithm in Wireless Sensor Networks
Most of the current RSS (Received Signal Strength)-based localization algorithms in Wireless Sensor Networks (WSNs) rely on isotropic radio propagation model to infer the distance between a pair of nodes from received signal strength, which however has be
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Abstract. Most of the current RSS (Received Signal Strength)-based localization algorithms in Wireless Sensor Networks (WSNs) rely on isotropic radio propagation model to infer the distance between a pair of nodes from received signal strength, which however has been proved to be quite unreliable in recent research work. Performance analysis is important to evaluate the applicability of a localization algorithm, however little work has been done on evaluating the existing localization algorithms in simulated realistic settings. This paper firstly presents the motivation and detailed implementation of a proposed Link-State Based Annulus (LSBA) localization algorithm, and then gives a panorama of performance comparison among LSBA and other four localization algorithms in terms of estimation error, convergence speed, computational complexity and communication cost in the simulated realistic environment. Simulation results show that LSBA achieves the best tradeoff among all the four metrics in WSNs with moderate number of anchors, and has good adaptability to irregular node deployment as well. Keywords: RSS; wireless sensor networks; localization.
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Introduction
Localization approaches in WSNs are roughly classified as fine-grained approaches and coarse-grained approaches. Fine-grained approaches normally require accurate distance or angle measurements to compute the location of unknown node. TDOA (Time Difference of Arrival) [7] [8] [9], AOA (Angle of Arrival) [10], and RIPS (Radio Interferometric Positioning System) [12] rely on extra (sometimes expensive and complex) hardware other than radio transceiver to get accurate measurements. Use of RSS as ranging technique receives much recognition since radio transceiver is the only available ranging device for most of the common sensor nodes. Most of the existing RSS methods rely on an ideal
This work was supported by the National Natural Science Foundation of China under Grant No.60673173. Corresponding author.
H. Zhang et al. (Eds.): MSN 2007, LNCS 4864, pp. 584–595, 2007. c Springer-Verlag Berlin Heidelberg 2007
Study of a Cost-effective Localization Algorithm in WSNs
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radio propagation model [16] to get the distance from RSSI, which states that the received signal strength diminishes with the distance according to certain law. However, recent researches [13] [14] [15] show that radio propagation pattern is highly random in real world, and no one-to-one mapping exists between RSSI and distance in most situations. Therefore localization algorithms based on ideal radio model may perform poorly in realistic environment, and need to be reconsidered. Coarse-grained approaches normally rely on proximity and near-far information or less accurate distance estimation to infer the location of unknown node, of which Centroid [2], geometry constrains [6], DV-HOP [4], Amorphous [5] are typical. We provide a LSBA (Link State Based Annulus localization algorithm) [17]. Coarse-grained approaches are much popular in densely deployed large scale sensor networks since they av
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