Scheduling RFID networks in the IoT and smart health era

As a potential way to dramatically save energy and live in a green and smarter planet, the internet of things (IoT) aims to utilize energy-efficient enabling technologies such as the RFID systems in our daily life applications. RFID, or Radio Frequency Identification, is used to efficiently locate items using tags and readers. In this paper, we propose localized reader scheduling algorithms for RFID networks. We consider readers with limited amounts of energy, powered by a battery. Using only local information, the readers schedule themselves to minimize energy usage and maximize network lifetime. We compare the performance of our localized algorithms to a centralized heuristic (the research problem is NP hard) based on a set cover approximation solution and show that the localized algorithms obtain equal or better performance in comparison to centralized solution, achieving 5% higher area under the curve (AUC) in scenarios with 50% readers, and 13 and 8% higher AUC in 25% and 15% reader scenarios, respectively.