  Recent statistics have demonstrated that missing items have become the main
cause of loss for retailers in inventory management. To quickly identify
missing tags, traditional protocols adopt Aloha-based strategies which take a
long time, especially when the number of tags is large. Among them, few works
considered the effect of unexpected unknown tags on the missing tag
identification process. With the presence of unknown tags, some missing tags
may be falsely identified as present. Thus, the system's reliability is hardly
guaranteed. In this work, we propose an efficient early-breaking estimation and
tree-splitting-based missing tag identification (ETMTI) protocol for
large-scale RFID systems. In ETMTI, a new early-breaking estimation and
deactivation method is developed to effectively estimate the number of unknown
tags and deactivate them within a short time. Next, a new tree-splitting-based
missing tag identification method is proposed to quickly identify missing tags
with a B-ary splitting tree. Besides, a bit-tracking response strategy is
designed to further reduce the time cost. The optimal parameters, time cost,
and false negative rate of ETMTI are analyzed theoretically. Simulation results
are presented to demonstrate that the proposed ETMTI protocol takes a smaller
time and has a lower false negative rate than the best-performing benchmarks.
