A status updating system is considered in which multiple data sources generate packets to be delivered to a destination through a shared energy harvesting sensor. Only one source's data, when available, can be transmitted by the sensor at a time, subject to energy availability. Transmissions are prune to erasures, and each successful transmission constitutes a status update for its corresponding source at the destination. The goal is to schedule source transmissions such that the collective long-term average age-of-information (AoI) is minimized. AoI is defined as the time elapsed since the latest successfully-received data has been generated at its source. To solve this problem, the case with a single source is first considered, with a focus on threshold waiting policies, in which the sensor attempts transmission only if the time until both energy and data are available grows above a certain threshold. The distribution of the AoI is fully characterized under such a policy. This is then used to analyze the performance of the multiple sources case under maximum-age-first scheduling, in which the sensor's resources are dedicated to the source with the maximum AoI at any given time. The achievable collective long-term average AoI is derived in closed-form. Multiple numerical evaluations are demonstrated to show how the optimal threshold value behaves as a function of the system parameters, and showcase the benefits of a threshold-based waiting policy with intermittent energy and data arrivals.

翻译：状态更新系统将考虑多种数据源生成的包包通过共享的能源采集传感器发送到目的地; 只有一个来源的数据,如果可用的话,可同时由传感器传输,但须视能源的提供情况而定; 传输为淡化,每个成功传输构成其相应来源在目的地的状态更新; 目标是将源传输安排成集体的长期平均信息平均年龄(AoI)最小化; 将AoI定义为自最新的成功接收数据在源头生成以来的时间间隔; 为了解决这一问题,首先考虑单一来源的情况,以阈值等待政策为重点,只有在能源和数据均超过某一阈值之前的时间,传感器才尝试传输。 AoI的分布在这种政策下具有充分的特点。 然后,将AoI用于分析多种来源在基于最大年龄的列表下的情况,在该列表中,传感器的资源专门用于源,在任何特定时间的源值最高为AoI。 为了解决该问题,将一个单一来源的案件首先考虑,侧重于阈值的临界值,传感器试图传输,只有当能源和数据均值超过一定阈值的临界值值值值值,然后将展示一个可实现的AI的模型显示一个可实现的多位性平均值的图像值的模型。