Optimizing Energy-Efficient Cooperative MAC Strategies for Data Collection in IoT Networks With Terrestrial and Nonterrestrial Relays

This article investigates optimal distributed medium access control (MAC) strategies for wireless Internet of Things (IoT) networks, incorporating both terrestrial and nonterrestrial relays, including UAVs. While prior research has primarily focused on single-relay forwarding, we address the complexities of energy-efficient multirelay data forwarding. This involves managing the challenges of relay probing, optimized relay utilization, and balancing energy tradeoffs to maximize system energy efficiency (EE). To address these challenges, we propose a novel strategy called distributed data collection with opportunistic relaying (DDC/OR), designed to optimize MAC performance in multirelay IoT networks. Our approach leverages a decision-theoretic framework based on optimal sequential planning, extending traditional cooperative MAC models to support multiple relays. The proposed DDC/OR strategy offers a statistically optimized solution that maximizes average EE, with a rigorous proof of optimality. Additionally, we present a low-complexity implementation of the DDC/OR algorithm, suitable for practical deployments. For scenarios involving dynamic nonterrestrial movements and varying relay interdistances, we introduce a two-timescale, self-organized algorithm to adaptively reconfigure relay strategies. To ensure scalability for large relay networks, several optimizations are introduced to enhance the feasibility of the DDC/OR approach. We validate the effectiveness of the DDC/OR strategy through extensive simulations, demonstrating significant EE gains in both terrestrial and nonterrestrial relay configurations. Notably, it also achieves comparatively better performance in latency, throughput, and overall energy consumption.