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OFA: An optimistic approach to conquer flip ambiguity in network localization
Authors:Xiaoping Wang  Yunhao Liu  Zheng Yang  Kai Lu  Jun Luo
Affiliation:1. School of Computer Science, National University of Defense Technology, ChangSha, China;2. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Kowloon, Hong Kong;3. TNLIST, School of Software, Tsinghua University, BeiJing, China;1. Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy;2. Département de Génie Électrique, École Polytechnique de Montréal, Canada;1. Dept. of Telecommunications and Media Informatics, Budapest University of Technology and Economics, 1117 Budapest, Hungary;2. Hungarian Academy of Science (MTA), Information System Research Group Széchenyi István tér 9., 1051 Budapest, Hungary;3. MTA-BME Future Internet Research Group Széchenyi István tér 9., 1051 Budapest, Hungary;4. Inter-University Centre for Telecommunications and Informatics, Kassai út 26., 4028 Debrecen, Hungary;5. Dept. of Telematics, Norwegian University of Science and Technology, N-7491 Trondheim, Norway;1. Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, PR China;2. Faculty of Mathematics and Computer Science, Universitat of Bremen, Bremen 28359, Germany;3. College of Information Science and Technology, Hunan Agricultural University, Changsha 410128, PR China
Abstract:Accurate self-localization is a key enabling technique for many pervasive applications. Existing approaches, most of which are multilateration based, often suffer ambiguities, resulting in huge localization errors. To address this problem, previous approaches discard those positioning results with possible flip ambiguities, trading the localization performance for the result robustness. However, the high false positive rate of flip prediction incorrectly rejects many reliable location estimates. By exploiting the characteristics of flip ambiguity, which causes either huge or zero error, we propose the concept of optimistic localization and design an algorithm, OFA, that employs a global consistency check and a location correction phase in the localization process. We analyze the performance gain and cost of OFA, and further evaluate this design through extensive simulations. The results show that OFA obtains robustness with extremely low performance cost, so as to reduce the requirement on the average degree from 25 to 10 for robustly localizing a network.
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