Outlier Detection Techniques for Localization in Wireless Sensor Networks: A Survey

Abstract

In wireless sensor networks (WSNs), localization is one of the most important topics because the location information is typically useful for many applications. The primary data used in a localization process include the locations of anchor nodes and the distances between neighboring nodes. However, these data may contain outliers that deviate from their true values. The existence of the outliers might make the estimated positions not accurate. Thus, it is important to detect and handle outliers in order to achieve high localization accuracy. In this paper, we survey the existing outlier detection techniques for localization in wireless sensor networks. We provide taxonomy for classifying outlier detection techniques in WSNs localization based on different features. In addition, we present comparisons of these techniques. Finally, we discuss the future research directions in this area.