# An Admission-Control-Based Dynamic Query Tree Protocol for Fast Moving RFID Tag Identification
## 1 Introduction  
Industry 4.0, which is triggered by the Industrial Internet of Things (IIoT), has become the current trend of automation and data exchange in manufacturing technologies [1]. Thanks to the automatic identification techniques, such as radio frequency identification (RFID) and wireless sensors, used in the perception layer of the IIoT [2], the efficiency of modern manufacturing is greatly improved. As a non-contact identification technology, RFID has been widely used in various applications, such as object tracking, smart warehouse management, product line monitoring, etc. A typical RFID system usually consists of readers, tags and a back-end server. Each tag is identified by a unique identifier and sends data information by backscattering the reader's signal. The back-end server is used to store tag information for further processing and analyses. In RFID systems, the reader usually needs to recognize a large number of unknown tags within its reading range. When multiple tags reply simultaneously, a collision occurs where the reader cannot successfully decode the received message [3]. Unknown tag identification has always been one of the most critical techniques to enable object tracing and goods management in RFID systems. In recent research, lots of RFID tag identification protocols have been proposed. Among them, tree-based ones that make use of bit tracking technology [4, 5] exhibit better performance, e.g., higher system efficiency and shorter identification delay. In such protocols, the reader usually divides colliding tags intomultiple subsets with tree splitting. Thanks to the position information of colliding bits in the received message, the splitting process is more efficient. The most representative tree-based protocols are collision tree (CT) [4], collision window tree (CwT) [5] and M-ary collision tree (MCT) [6]. These algorithms use one or more colliding bits to split colliding tags into multiple subsets to accelerate the identification process. Recently, [PERSON] et al. proposed some tree-based algorithms, e.g, the dual prefix probing (DPPS) [7] and group-based tree splitting (GBSA) [8] to quickly identify tags. However, existing works make little use of the collision information. There is still room for improvement in bit-tracking-based tree splitting algorithms. Moreover, these works only consider the identification efficiency of a single reading round in static environments. The impact of tag mobility on the identification process lacks intensive study. In most applications, conveyor belts are widely used to accelerate the sorting efficiency for goods management [9; 10; 11]. For example, more and more airports have used RFID technology to place luggage on conveyor belts for fast identification, and other applications have also identified tagged goods on conveyor belts, such as the traditional retail giant Walmart [9]. In such systems, one or more RFID readers are mounted above or beside the conveyor belt in some fixed positions. Objects attached with RFID tags move with the conveyor belt. Readers are responsible for collecting the ID information of all passing tags. Usually, tags' IDs are unknown, and all tags send messages to the reader only when they receive the reader's query request. Without any prior information, the reader cannot aim at any specific tag in its query request. One common strategy is carrying a query prefix in the reader's query request. If a tag matches with the received prefix, it replies to the reader. When more than one tag replies simultaneously, a collision occurs which increases the identification delay. The identification task is more challenging in mobile systems where tags quickly go through the reader's reading range. Tags have a very limited time to participate in the identification process. Therefore, a tag may be unrecognized after it moves out of the reader's reading range, i.e., becomes a lost tag [12]. With higher moving speed, the tag lost probability is larger.