Life-time Throughput Optimization of Slotted-Aloha

This paper aims to improve energy efficiency in large-scale slotted Aloha networks. We introduce the life-time throughput as a measure of energy efficiency, characterized by the Last-Come-First-Serve with preemption (LCFS-PR) discipline and the Bernoulli sampling model. To address the bi-stable nature of the slotted Aloha network and the energy efficiency performance bottleneck in massive sensor scenarios, we optimize the packet sampling probability and channel access probability to enhance the life-time throughput. The optimization results show that the proposed schemes effectively improve the robustness of the Aloha network in the presence of bistability, mitigating the sharp decline in optimal life-time throughput as the number of sensors increases. Compared to fixed parameter settings, the optimized schemes maintain a good transmission state in dense deployment scenarios, thereby enhancing energy efficiency.