Abstract
The management of the uncertainties over data is an urgent problem of novel applications such as cyber-physical system, sensor network and RFID data management. In order to adapt the characteristics of evolving over time of sensor data in real-time location tracing service based on RFID, a measuring algorithm for the Uncertainty of RFID Data-PPMU (a particle filter and particle swarm optimization-based measuring uncertainty algorithm for RFID Data) is proposed in this paper. PPMU can change the number of samples adaptively on the basis of K–L distance to adapt the evolution of RFID data, and PPMU introduces an improved PSO (particle swarm optimization) method to enhance the efficiency of re-sampling phase of SIRPF (sequential importance re-sampling particle filter). Meanwhile, PPMU defines a fitness function base on Conventional Weighted Aggregation for PSO that balances the importance between the priori density and likelihood density to detect the most optimal samples among candidate sample sets. It provides a measurement with confidence factor for initial tuples in the probability RFID database. Experiments on real dataset show the proposed method can effectively measure the underlying uncertainty over RFID data. Compared with existing algorithms, PPMU can be further improved particle degradation and particle impoverishment problem.
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Acknowledgments
Supported by the National Natural Science Foundation of China under Grant No. 60803001, 61170035, 60850002, National Natural Science Foundation of Jiangsu under Grant No. BK2011225, the Special Grants of China Postdoctoral Science Foundation (No. 200902517), the Jiangsu Province Postdoctoral Science Foundation under Grant No. 0801043B, the special project of Nanjing Scientific Committee Foundation (No. 020142010), the Qing Lan Project Foundation of Jiangsu Province 2010, the Star of Excellence Zijin Foundation of NJUST 2009.
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Wang, Y., Qian, J. Measuring the uncertainty of RFID data based on particle filter and particle swarm optimization. Wireless Netw 18, 307–318 (2012). https://doi.org/10.1007/s11276-011-0401-4
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DOI: https://doi.org/10.1007/s11276-011-0401-4