Link Scheduling for Data Collection in Multi-Hop Backscatter IoT Wireless Networks

Recently, many works have seek to exploit the negligible transmission cost of backscattering Radio Frequency (RF) signals, and also demonstrated its feasibility in allowing passive or batteryless tags to communicate over multiple hops. In this context, this paper studies data collection in a multi-hop Internet of Things (IoT) wireless network consisting of tags equipped with sensor(s). These tags forward data via tag-to-tag communications to a gateway. Our aim is for the gateway to collect the maximum amount of data from tags over a given time frame. To do so, we optimize the time used by tags to sample their environment and data transmission, which involves solving an NP-hard link scheduling problem. We present a Mixed Integer Non-Linear Program (MINLP) to determine the transmitting tags in each time slot as well as the sensing duration of tags. We also propose a heuristic called Max-L that aims to maximize the number of links in each transmission set in order to reduce the transmission time of samples. Our results show that Max-L collects 85% of the optimal amount of samples