A survey of localization in wireless sensor network

Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

Evaluation and Analysis of Node Localization Power Cost in Ad-Hoc Wireless Sensor Networks with Mobility

One of the key concerns with location-aware Ad-hoc Wireless Sensor Networks (AWSNs) is how sensor nodes determine their position. The inherent power limitations of an AWSN along with the requirement for long network lifetimes makes achieving fast and power-efficient localization vital. This research examines the cost (in terms of power) of network irregularities on communications and localization in an AWSN. The number of data bits transmitted and received are significantly affected by varying levels of mobility, node degree, and network shape. The concurrent localization approach, used by the APS-Euclidean algorithm, has significantly more accurate position estimates with a higher percentage of nodes localized, while requiring 50% less data communications overhead, than the Map-Growing algorithm. Analytical power models capable of estimating the power required to localize are derived. The average amount of data communications required by either of these algorithms in a highly mobile network with a relatively high degree consumes less than 2.0% of the power capacity of an average 560mA-hr battery. This is less than expected and contrary to the common perception that localization algorithms consume a significant amount of a node\u27s power