Timely Reliability Evaluation and Optimization of Wireless Sensor Networks Considering Channel Capacity Randomness and Energy Depletion

The real-time and reliable transmission of data packets is a critical foundation for ensuring Internet of Things applications. Therefore, how to ensure the timely reliability of wireless sensor networks has become a hotspot. However, existing timely reliability models often overlook the impacts of energy depletion and channel capacity randomness on wireless transmission. Additionally, most evaluations focus on single-hop, single-path scenarios, while practical data transmission typically requires multi-hop and multi-path strategies. To overcome the above shortcomings, this study conducts the timely reliability evaluation and optimization of wireless sensor networks considering channel capacity randomness and energy depletion. First, focusing on data transmission delay modeling, this study emphasizes the effects of energy depletion and channel capacity randomness on wireless data transmission, and further proposes a timely reliability evaluation model based on the G/G/1 queuing model. Secondly, to tackle the computational challenges of multi-hop and multi-path data transmission, this study proposes a timely reliability solving algorithm that integrates the binary decision diagrams with Monte Carlo simulation.. Building on these foundations, this study develops a periodic optimization model for signal transmission power, balancing sensor lifetime and network transmission performance. Finally, taking the military Internet as an example, the effectiveness of the proposed method is verified.