DtS-IoT Resource Allocation Analysis Framework: Assessing DQ and RESS-IoT

The demand for expanding connectivity to remote and isolated areas has intensified the need for global Internet of Things (IoT) solutions. Direct-to-Satellite IoT (DtS-IoT), enabled by advances in nanosatellite technology, allows cost-effective global and direct connectivity between IoT devices and low Earth orbit satellites. However, the most cost-effective DtSIoT networks face resource limitations in user, ground, and space segments, demanding scalable solutions to fully realize their scalability potential. While several resource allocation protocols have been proposed for DtS-IoT, they have mainly been evaluated using static topologies or simplified simulations, overlooking the time-evolving orbital and channel dynamics crucial to DtS-IoT performance. This work bridges this gap by introducing the DtS-IoT Resource Allocation Analysis Framework (DRAAF), a comparison methodology and toolchain for evaluating resource allocation mechanisms in realistic DtS-IoT scenarios. Our method is framed in scalability, energy efficiency, throughput, delay, fairness, and overhead metrics. Utilizing FLoRaSat, a realistic LoRa-based DtS-IoT network simulator, we showcase the methodology with a use case investigating two energy-efficient MAC protocols for DtS-IoT: RESS-IoT and Distributed Queuing (DQ). Results indicate that DQ excels in throughput and node energy efficiency, whereas RESS-IoT reduces delay. Both protocols maintain satellite energy efficiency and enhance fairness in uplink transmissions. These findings underscore the value of our approach in evaluating resource allocation within complex DtS-IoT systems.