Localization in Wireless Sensor Networks and Anchor Placement

Applications of wireless sensor network (WSN) often expect knowledge of the precise location of the nodes. Many different localization protocols have been proposed that allow nodes to derive their location rather than equipping them with dedicated localization hardware such as GPS receivers, which increases node costs. We provide a brief survey of the major approaches to software-based node localization in WSN. One class of localization protocols with good localization performance patches together relative-coordinate, local maps into a global-coordinate map. These protocols require some nodes that know their absolute coordinates, called anchor nodes. While many factors influence the node position errors, in this class of protocols, using Procrustes Analysis, the placement of the anchor nodes can significantly impact the error. Through simulation, using the Curvilinear Component Analysis (CCA-MAP) protocol as a representative protocol in this category, we show the impact of anchor node placement and propose a set of guidelines to ensure the best possible outcome, while using the smallest number of anchor nodes possible

Anchor Nodes Placement for Effective Passive Localization

Wireless sensor networks are composed of sensor nodes, which can monitor an environment and observe events of interest. These networks are applied in various fields including but not limited to environmental, industrial and habitat monitoring. In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to find sensor node's positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. I do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. I show that, for effective passive localization, the optimal placement of the anchor nodes is at the center of the network in such a way that no three anchor nodes share linearity. The more the non-linearity, the better the localization. The localization for our network design proves better when I place anchor nodes at right angles

HEA-Loc: A robust localization algorithm for sensor networks of diversified topologies

In recent years, localization in a variety of Wireless Sensor Networks (WSNs) is a compelling but elusive goal. Several algorithms that use different methodologies have been proposed to achieve this goal. The performances of these algorithms depend on several factors, such as the sensor node placement, anchor deployment or network topology. In this paper, we propose a robust localization algorithm called Hybrid Efficient and Accurate Localization (HEA-Loc). HEA-Loc combines two techniques, Extended Kalman Filter (EKF) and Proximity-Distance Map (PDM) to improve localization accuracy. It is distributed in nature and works well in various scenarios as it is less susceptible to anchors deployment and the network topology. Furthermore, HEA-Loc has strong robustness and it can work well even the measurement errors are large. Simulation results show that HEA-Loc outperforms existing algorithms in both computational complexity and communication overhead. ©2010 IEEE.published_or_final_versionThe IEEE Wireless Communications and Networking Conference (WCNC 2010), Sydney, NSW., 18-21 April 2010. In Proceedings of WCNC, 2010, p. 1-