论文标题
PAS：基于预测的自适应睡眠，用于传感器网络中的环境监测
PAS: Prediction-based Adaptive Sleeping for Environment Monitoring in Sensor Networks
论文作者
论文摘要
事实证明，能源效率是主导WSN监视系统工作期的重要因素。进行了密集的研究以提供节能能力管理机制。在本文中，我们提出了PAS，这是一种基于预测的自适应睡眠机制，用于环境监测传感器网络以节省能量。 PAS专注于扩散刺激（DS）方案，这在环境监测的应用中非常普遍且重要。与以前的大多数作品不同，PAS探讨了DS扩散过程的特征，以获得更高的能源效率。在PAS中，传感器根据观察到的DS扩散的紧急情况确定其睡眠时间表。当DS边界附近的传感器保持清醒以准确捕获可能的刺激到达时，远方传感器会变成睡眠模式以节省能量。仿真实验表明，PAS很大程度上降低了能源成本而不降低系统性能
Energy efficiency has proven to be an important factor dominating the working period of WSN surveillance systems. Intensive studies have been done to provide energy efficient power management mechanisms. In this paper, we present PAS, a Prediction-based Adaptive Sleeping mechanism for environment monitoring sensor networks to conserve energy. PAS focuses on the diffusion stimulus (DS) scenario, which is very common and important in the application of environment monitoring. Different with most of previous works, PAS explores the features of DS spreading process to obtain higher energy efficiency. In PAS, sensors determine their sleeping schedules based on the observed emergency of DS spreading. While sensors near the DS boundary stay awake to accurately capture the possible stimulus arrival, the far away sensors turn into sleeping mode to conserve energy. Simulation experiment shows that PAS largely reduces the energy cost without decreasing system performance
