Enabling Ultra Large-Scale Radio Identification Systems
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Radio Frequency IDentification (RFID) is growing prominence as an automated identification technology able to turn everyday objects into an ad-hoc network of mobile nodes; which can track, trigger events and perform actions. Energy scavenging and backscattering techniques are the foundation of low-cost identification solutions for RFIDs. The performance of these two techniques, being wireless, significantly depends on the underlying communication architecture and affect the overall operation of RFID systems. Current RFID systems are based on a centralized master-slave architecture hindering the overall performance, scalability and usability. Several proposals have aimed at improving performance at the physical, medium access, and application layers. Although such proposals achieve significant performance gains in terms of reading range and reading rates, they require significant changes in both software and hardware architectures while bounded by inherited performance bottlenecks, i.e., master-slave architecture. Performance constraints need to be addressed in order to further facilitate RFID adoption; especially for ultra large scale applications such as Internet of Things. A natural approach is re-thinking the distributed communication architecture of RFID systems; wherein control and data tasks are decoupled from a central authority and dispersed amongst spatially distributed low-power wireless devices. The distributed architecture, by adjusting the tag's reflectivity coefficient creates micro interrogation zones which are interrogated in parallel. We investigate this promising direction in order to significantly increase the reading rates and reading range of RFID tags, and also to enhance overall system scalability. We address the problems of energy-efficient tag singulations, optimal power control schemes and load aware reader placement algorithms for RFID systems. We modify the conventional set cover approximation algorithm to determine the minimal number of RFID readers with minimal overlapping and balanced number of tags amongst them. We show, via extensive simulation analysis, that our approach has the potential to increase the performance of RFID technology and hence, to enable RFID systems for ultra large scale applications.