Schedulers in radio frequency identification dense environments aim at distributing optimally a set of t slots between\r\na group of m readers. In single-channel environments, the readers within mutual interference range must transmit at\r\ndifferent times; otherwise, interferences prevent identification of the tags. The goal is to maximize the expected\r\nnumber of tags successfully identified within the t slots. This problem may be formulated as a mixed integer\r\nnon-linear mathematical program, which may effectively exploit available knowledge about the number of\r\ncompeting tags in the reading zone of each reader. In this paper, we present this optimization problem and analyze\r\nthe impact of tag estimation in the performance achieved by the scheduler. The results demonstrate that optimal\r\nsolutions outperform a reference scheduler based on dividing the available slots proportionally to the number of tags\r\nin each reader. In addition, depending on the scenario load, the results reveal that there exist an optimum number of\r\nreaders for the topology considered, since the total average number of identifications depend non-linearly on the\r\nload. Finally, we study the effect of imperfect tag population knowledge on the performance achieved by the readers.
Loading....