Energy-Aware Concurrent Data Aggregation Scheduling for Wireless Powered IoT Leveraging Hypergraph Theory

This letter investigates the minimum-delay data aggregation scheduling problem for wireless powered Internet of Things (WPIoT). Unlike traditional Internet of Things (IoT), WPIoT devices should harvest enough energy before data transmission or reception. Hence, many existing solutions for traditional IoT cannot be directly applied to WPIoT. In this letter, we propose a delay-efficient algorithm by fully considering the energy features and cumulative interference effects of WPIoT. This algorithm constructs the data aggregation tree based on the fewest-children-first rule and implements a novel energy-aware concurrent link scheduling method leveraging the hypergraph theory. This novel link scheduling method can satisfy both the residual energy constraint and signal interference constraint. The performance of our algorithm is evaluated by extensive experiments based on a real-world dataset under non-linear energy harvesting models with both perfect and imperfect channel state information. The results confirm the superiority of our algorithm over the baseline algorithms.