# An Admission-Control-Based Dynamic Query Tree Protocol for Fast Moving RFID Tag Identification
## 2 Related Works  
In this section, we review some representative tag identification protocols for both static and mobile RFID systems. In static systems, the tag set is assumed unchanged during the identification process. In such systems, the key problem is to reduce tag collisions, especially when the number of tags is large. In general, tag identification protocols mainly consist of two categories, i.e., the aloha-based, and the tree-based ones. In the first category, the reader identifies tags with a frame-slotted manner, and a tag replies to the reader with a randomly selected slot in each frame. However, using a random response manner, aloha-based protocols are of low efficiency. To improve the performance, some tag number estimation and frame adjustment strategies are proposed based on the statistical information of tag responses. For example, the Q-algorithm dynamically adjusts frame length with the feedback of slot status [16]. The maximum likelihood estimation algorithm estimates the number of tags with the Bayes method to optimize frame length settings in a dynamic frame-slotted aloha protocol [17]. In the second category, the reader identifies tags with a tree splitting method by grouping colliding tags into smaller subsets, such as query tree (QT) [18], binary tree splitting (BTS) [19], collision tree (CT) [4], etc. The identification process of these protocols follows a tree splitting structure in which each non-leaf vertex in the tree corresponds to a collision slot, and each leaf vertex refers to a successful or idle slot. With a bit tracking technique, identification efficiency of tree-based protocols is efficiently improved. In the collision tree (CT) protocol [4], the reader splits colliding tags into two subsets based on the position of the first colliding bit without generating any idle slots. However, the splitting process is slow, and many collision slots are generated. Next, [PERSON] et al. proposed a collision window tree (CwT) protocol [5] that uses a heuristic bit window strategy in the collision tree splitting process in order to reduce identification time and tags' communication overhead. In CwT, the number of total slots are increased, and the reader has to transmit more query messages to identify all tags. To further reduce collision slots, [PERSON] et al. proposed a dual prefix probing (DPPS) protocol [7] that makes use of the first two consecutive colliding bits to split colliding tags into more subsets. In [6], [PERSON] et al. proposed an M-ary collision tree (MCT) protocol to further accelerate the splitting process by making use of more colliding bits information. Recently, [PERSON] et al. also proposed a modified dual prefixes matching (MDPM) algorithm [20] that makes a bit query strategy in the M-ary query tree. [PERSON] et al. designed a multi-bit identification collision tree (MICT) algorithm [21] and [PERSON] et al. developed a knowledge-based query tree algorithm [22]. However, these works only consider a static situation. In mobile systems, the tag set changes dynamically and tag participating time is very limited. These works cannot effectively identify tags in such situations. In mobile situations, when the reader begins a new reading round, tags that have been recognized in preceding rounds may still be in the reader's reading range which results in duplicate recognition. Meanwhile, some newly arrived tags may join the identification process which further aggravates the tag collision situation. How to effectively control participating tags and quickly identify moving tags is very challenging. In the past decade, some works considered the moving tag identification problem. In [23], [PERSON] et al. first proposed an aloha-based framework for both static and mobile environments. Next, [PERSON] et al. analyzed the tag lost ratio in dynamic RFID systems and gave optimal configurations of frame-slotted aloha algorithms [24; 25; 26]. Later on, [PERSON] et al. developed a reliable splitting strategy in an aloha algorithm to accelerate the identification process of moving tags [27].