报告题目: A Near-optimal Protocol for the Subset Selection Problem in RFID Systems
报告地点：zoom在线会议 会议ID：939 3075 5234 密码： nMsa4a
In many real-time RFID-enabled applications (e.g., logistic tracking and warehouse controlling), a subset of wanted tags is often selected from a tag population for monitoring and querying purposes. How this subset of tags is rapidly selected, which is referred to as the subset selection problem, becomes pivotal for boosting the efficiency in RFID systems. Current state-of-the-art schemes result in high communication latencies, which are far from the optimum, and this degrades the system performance. This problem is addressed in this paper by using a simple Bit-Counting Function $BCF()$, which has also been employed widely by other protocols in RFID systems. In particular, we first propose a near-OPTimal SeLection protocol, denoted by OPT-SL, to rapidly solve this problem based on the simple function $BCF()$. Second, we prove that the communication time of OPT-SL is near-optimal with rigorous theoretical analysis. Finally, we conduct extensive simulations to verify that the communication time of the proposed OPT-SL is not only near-optimal but also significantly less than that of benchmark protocols.
报告人简介：王修君 副教授 安徽工业大学
Dr. Xiujun Wang got his Ph.D. degree in computer software and theory from the University of Science and Technology of China in 2011. He is currently an associate professor at the School of Computer Science and Technology, Anhui University of Technology. His research covers diverse grounds in data stream processing and RFID system management, both of which are motivated by many recent applications emerging with Big data and the Internet of Things (IoT). Besides, he is interested in the research that explores lower bounds in communication complexity. He received the best paper award of MSN 2020.