원문정보
초록
영어
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.
목차
1. Introduction
2. Background
2.1. Outliers in WSNs
2.2. Localization for WSNs
2.3. Outlier in Localization for WSNs
3. Motivation
4. Classification
4.1. Network Implementation
4.2. Detected Outlier Type
4.3. Handle Detected Outlier
5. Outlier Detection Techniques for Wireless Sensor Networks Localization
5.1. LAD Localization Anomaly Detection
5.2. RobustLoc Outlier Detection
5.3. Beyond Triangle Inequality
5.4. Detecting Outlier Measurements Based on Graph Rigidity
5.5. Range-Based Localization Using Density- Based Outlier Detection
5.6. Outlier-Detection-Based Indoor Localization System for WSN
5.7. Outlier Compensation in SN Self-Localization via the EM
5.8. Secure RSS-Based Localization in Sensor Networks
5.9. Robust Distributed Node Localization with Error Management
5.10. Robust Statistical Methods for Securing Wireless Localization
5.11. A Robust Localization Algorithm in WSNs
5.12. Robust Interval-Based Localization for Mobile Sensor Networks
6. Comparison of Outlier Detection Techniques for Localization in WSNS
7. Shortcomings of Outlier Detection Techniques for WSNS Localization and Future Research Directions
7.1. Shortcomings of Outlier Detection Techniques for WSNS Localization
7.2. Future Research Directions
8. Conclusions
References