Range-free localization schemes for large scale sensor networks
Proceedings of the 9th annual international conference on Mobile computing and networking
The n-hop multilateration primitive for node localization problems
Mobile Networks and Applications
Poster abstract: anchor-free distributed localization in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
The sybil attack in sensor networks: analysis & defenses
Proceedings of the 3rd international symposium on Information processing in sensor networks
Robust distributed network localization with noisy range measurements
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
The effects of ranging noise on multihop localization: an empirical study
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Robust statistical methods for securing wireless localization in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Attack-resistant location estimation in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Localization in sparse networks using sweeps
Proceedings of the 12th annual international conference on Mobile computing and networking
Rendered path: range-free localization in anisotropic sensor networks with holes
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
WASA '07 Proceedings of the International Conference on Wireless Algorithms,Systems and Applications
Distributed Localization Using a Moving Beacon in Wireless Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Localization with snap-inducing shaped residuals (SISR): coping with errors in measurement
Proceedings of the 15th annual international conference on Mobile computing and networking
Localization Algorithms and Strategies for Wireless Sensor Networks
Localization Algorithms and Strategies for Wireless Sensor Networks
Reliable Anchor-Based Sensor Localization in Irregular Areas
IEEE Transactions on Mobile Computing
Beyond triangle inequality: sifting noisy and outlier distance measurements for localization
INFOCOM'10 Proceedings of the 29th conference on Information communications
Multihop Range-Free Localization in Anisotropic Wireless Sensor Networks: A Pattern-Driven Scheme
IEEE Transactions on Mobile Computing
ETOC: Obtaining robustness in component-based localization
ICNP '10 Proceedings of the The 18th IEEE International Conference on Network Protocols
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In wireless sensor networks, a critical system service is the localization service that determines the locations of geographically distributed sensor nodes. The raw data used by this service are the distance measurements between neighboring nodes and the position knowledge of anchor nodes. However, these raw data may contain outliers that strongly deviate from their true values, which include both the outlier distances and the outlier anchors. These outliers can severely degrade the accuracy of the localization service. Therefore, we need a robust localization algorithm that can reject these outliers. Previous studies in this field mainly focus on enhancing multilateration with outlier rejection ability, since multilateration is a primitive operation used by localization service. But patch merging, a powerful operation for increasing the percentage of localizable nodes in sparse networks, is almost neglected. We thus propose a robust patch merging operation that can reject outliers for both multilateration and patch merging. Based on this operation, we further propose a robust network localization algorithm called RobustLoc. This algorithm makes two major contributions. (1) RobustLoc can achieve a high percentage of localizable nodes in both dense and sparse networks. In contrast, previous methods based on robust multilateration almost always fail in sparse networks with average degrees between 5 and 7. Our experiments show that RobustLoc can localize about 90% of nodes in a sparse network with 5.5 degrees. (2) As far as we know, RobustLoc is the first to uncover the differences between outlier distances and outlier anchors. Our simulations show that RobustLoc can reject colluding outlier anchors reliably in both convex and concave networks.