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Title: Analog on-tag hashing : towards selective reading as hash primitives in Gen2 RFID systems
Authors: Yang, L 
Lin, Q 
Duan, C 
An, Z 
Keywords: EPCGlobal Gen2
Hash function
Hash table function
Issue Date: 2017
Publisher: Association for Computing Machinery
Source: Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM, 2017, v. Part F131210, p. 301-314 How to cite?
Abstract: Deployment of billions of Commercial off-the-shelf (COTS) RFID tags has drawn much of the attention of the research community because of the performance gaps of current systems. In particular, hash-enabled protocol (HEP) is one of the most thoroughly studied topics in the past decade. HEPs are designed for a wide spectrum of notable applications (e.g., missing detection) without need to collect all tags. HEPs assume that each tag contains a hash function, such that a tag can select a random but predicable time slot to reply with a one-bit presence signal that shows its existence. However, the hash function has never been implemented in COTS tags in reality, which makes HEPs a 10-year untouchable mirage. This work designs and implements a group of analog on-tag hash primitives (called Tash) for COTS Gen2-compatible RFID systems, which moves prior HEPs forward from theory to practice. In particular, we design three types of hash primitives, namely, tash function, tash table function and tash operator. All of these hash primitives are implemented through selective reading, which is a fundamental and mandatory functionality specified in Gen2 protocol, without any hardware modification and fabrication. We further apply our hash primitives in two typical HEP applications (i.e., cardinality estimation and missing detection) to show the feasibility and effectiveness of Tash. Results from our prototype, which is composed of one Impin J reader and 3, 000 Alien tags, demonstrate that the new design lowers 60% of the communication overhead in the air. The tash operator can additionally introduce an overhead drop of 29.7%.
Description: 23rd Annual International Conference on Mobile Computing and Networking, MobiCom 2017, Snowbird, Utah, USA, 16-20 October, 2017
ISBN: 9781450349161
DOI: 10.1145/3117811.3117835
Appears in Collections:Conference Paper

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