Abstract
The ability of a sensor node to determine its position is a fundamental requirement for many applications in wireless sensor networks (WSNs). In this article, we address a scenario where a subset of sensors, called anchor nodes, knows its own position and helps other nodes determine theirs through range-based positioning techniques. Such techniques benefit from a high degree of connectivity, since range measurements from at least four anchor nodes are necessary (three-dimensional scenario). On the other hand, WSN topologies, most notably the cluster-tree topology, tend to limit connectivity between nodes to save energy. This results in very poor performance of the network in terms of localization. In this article, we propose LACFA, a network formation algorithm that increases the probability of localization of sensors in a cluster-tree topology. It does so by properly allocating anchor nodes to different clusters during the network formation phase. Our algorithm achieves very high localization probability when compared with existing cluster formation algorithms, at no additional cost. Moreover, a distributed cluster formation algorithm, with no need for any centralized information exchange mechanisms, is defined.
Highlights
Wireless sensor networks (WSNs) consist of small, lowcomplexity sensor nodes interconnected through wireless links
6 Simulations and results we present the simulations of the rangebased localization algorithm explained in Section 3 in different WSN topologies: mesh topology defined by Zigbee and 802.15.4a standards, cluster-tree topology defined by Zigbee, and a cluster-tree topology with 802.15.4a PHY layer
We have dealt with a scenario where a subset of sensors, called anchor or reference nodes, is aware of its own position and helps target nodes determine theirs through range-based positioning algorithms
Summary
Wireless sensor networks (WSNs) consist of small, lowcomplexity sensor nodes interconnected through wireless links. While the connectivity between nodes in a mesh network is high, it is considerably reduced in a cluster-tree topology This presents advantages, such as energy saving, but it severely degrades the performance of range-based localization. We propose LACFA, a network formation algorithm that increases the probability of positioning of sensors in a cluster-tree topology It does so by properly allocating anchor nodes to different clusters during the network formation phase, and by allowing peers in the same cluster to perform ranging with each other. We propose schemes for positioning in a cluster-tree topology Once range measurements are available, either resorting to TOA or RSSI techniques, the target node computes its position based on a simple algorithm to solve the trilateration problem. The application layer (that controls the localization algorithm) calls the corresponding MAC primitives directly for doing ranging between two nodes
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More From: EURASIP Journal on Wireless Communications and Networking
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