Adaptive Joint Estimation Protocol for Arbitrary Pair of Tag Sets in a Distributed RFID System

Radio frequency identification (RFID) technology has been widely used in Applications, such as inventory control, object tracking, and supply chain management. In this domain, an important research problem is called RFID cardinality estimation, which focuses on estimating the number of tags in a certain area covered by one or multiple readers. This paper extends the research in both temporal and spatial dimensions to provide much richer information about the dynamics of distributed RFID systems. Specifically, we focus on estimating the cardinalities of the intersection/differences/union of two arbitrary tag sets (called joint properties for short) that exist in different spatial or temporal domains. With many practical applications, there is, however, little prior work on this problem. We will propose a joint RFID estimation protocol that supports adaptive snapshot construction. Given the snapshots of any two tag sets, although their lengths may be very different depending on the sizes of tag sets they encode, we design a way to combine their information and more importantly, derive closed-form formulas to use the combined information and estimate the joint properties of the two tag sets, with an accuracy that can be arbitrarily set. By formal analysis, we also determine the optimal system parameters that minimize the execution time of taking snapshots, under the constraints of a given accuracy requirement. We have performed extensive simulations, and the results show that our protocol can reduce the execution time by multiple folds, as compared with the best alternative approach in literature.

[1]  Daniel W. Engels,et al.  Colorwave: an anticollision algorithm for the reader collision problem , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[2]  Jin Cao,et al.  A Quasi-Likelihood Approach for Accurate Traffic Matrix Estimation in a High Speed Network , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[3]  Bo Sheng,et al.  Efficient Continuous Scanning in RFID Systems , 2010, 2010 Proceedings IEEE INFOCOM.

[4]  Kyu-Young Whang,et al.  A linear-time probabilistic counting algorithm for database applications , 1990, TODS.

[5]  Alanson P. Sample,et al.  Design of an RFID-Based Battery-Free Programmable Sensing Platform , 2008, IEEE Transactions on Instrumentation and Measurement.

[6]  Wei Gong,et al.  Arbitrarily accurate approximation scheme for large-scale RFID cardinality estimation , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[7]  Harald Vogt,et al.  Efficient Object Identification with Passive RFID Tags , 2002, Pervasive.

[8]  Alex X. Liu,et al.  Every bit counts: fast and scalable RFID estimation , 2012, Mobicom '12.

[9]  Mo Li,et al.  ZOE: Fast cardinality estimation for large-scale RFID systems , 2013, 2013 Proceedings IEEE INFOCOM.

[10]  Himanshu Gupta,et al.  Slotted Scheduled Tag Access in Multi-Reader RFID Systems , 2007, 2007 IEEE International Conference on Network Protocols.

[11]  Chae-Woo Lee,et al.  An enhanced dynamic framed slotted ALOHA algorithm for RFID tag identification , 2005, The Second Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services.

[12]  Wenbo He,et al.  Towards adaptive continuous scanning in large-scale RFID systems , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[13]  Binbin Chen,et al.  Understanding RFID Counting Protocols , 2016, IEEE/ACM Transactions on Networking.

[14]  Wonjun Lee,et al.  Adaptive splitting protocols for RFID tag collision arbitration , 2006, MobiHoc '06.

[15]  Yunhao Liu,et al.  Cardinality Estimation for Large-Scale RFID Systems , 2008, IEEE Transactions on Parallel and Distributed Systems.

[16]  Kavé Salamatian,et al.  Traffic matrix estimation: existing techniques and new directions , 2002, SIGCOMM '02.

[17]  Robert L. Wolpert,et al.  Statistical Inference , 2019, Encyclopedia of Social Network Analysis and Mining.

[18]  Bo Sheng,et al.  Counting RFID Tags Efficiently and Anonymously , 2010, 2010 Proceedings IEEE INFOCOM.

[19]  Bin Xiao,et al.  Differential estimation in dynamic RFID systems , 2013, 2013 Proceedings IEEE INFOCOM.

[20]  Shigang Chen,et al.  Energy Efficient Algorithms for the RFID Estimation Problem , 2010, 2010 Proceedings IEEE INFOCOM.

[21]  Shigang Chen,et al.  Missing-Tag Detection and Energy–Time Tradeoff in Large-Scale RFID Systems With Unreliable Channels , 2014, IEEE/ACM Transactions on Networking.

[22]  Daniel W. Engels,et al.  The reader collision problem , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[23]  Mo Li,et al.  PET: Probabilistic Estimating Tree for Large-Scale RFID Estimation , 2011, IEEE Transactions on Mobile Computing.

[24]  Murali S. Kodialam,et al.  Fast and reliable estimation schemes in RFID systems , 2006, MobiCom '06.

[25]  Shigang Chen,et al.  Efficient Protocols for Identifying the Missing Tags in a Large RFID System , 2013, IEEE/ACM Transactions on Networking.

[26]  David Wetherall,et al.  A software radio-based UHF RFID reader for PHY/MAC experimentation , 2011, 2011 IEEE International Conference on RFID.