A Distributed Framework for Low-Latency Data Collection in Battery-Free Wireless Sensor Networks

Battery-free wireless sensor networks (BF-WSNs) extend the lifetime of wireless sensor networks (WSNs) using ambient energy sources. Thus, it becomes an emerging research area of Internet of Things (IoT) in recent years. Although many existing works in this area study data collection, few of them focus on optimizing the latency of data collection. In this article, we propose a novel distributed framework (DCF) for low-latency data collection in BF-WSNs. DCF uses an adaptive routing strategy, so battery-free nodes can select receivers depending on their status. It also provides transmitting opportunities for as many nodes as possible in each time slot to achieve high spatial parallelism. We also propose two strategies embedded in DCF to generate local schedules. These strategies allow nodes to determine their schedules based only on information from neighboring nodes. We then analyze the theoretical latency bounds of DCF with and without algorithm parameters, respectively. By comparing with the bound of the existing method, we conclude that the latency bound of DCF is superior. Finally, extensive simulations show that DCF significantly outperforms the existing method.