In this study, we investigate the optimal transmission policies within an energy harvesting status update system, where the demand for status updates depends on the state of the source. The system monitors a two-state Markovian source that characterizes a stochastic process, which can be in either a normal state or an alarm state, with a higher demand for fresh updates when the source is in the alarm state. We propose a metric to capture the freshness of status updates for each state of the stochastic process by introducing two Age of Information (AoI) variables, extending the definition of AoI to account for the state changes of the stochastic process. We formulate the problem as a Markov Decision Process (MDP), utilizing a transition cost function that applies linear and non-linear penalties based on AoI and the state of the stochastic process. Through analytical investigation, we delve into the structure of the optimal transmission policy for the resulting MDP problem. Furthermore, we evaluate the derived policies via numerical results and demonstrate their effectiveness in reserving energy in anticipation of forthcoming alarm states.

翻译：在本研究中，我们探讨了能量收集状态更新系统中的最优传输策略，其中状态更新的需求取决于源的状态。该系统监测一个描述随机过程的两状态马尔可夫源，该源可处于正常状态或报警状态，当源处于报警状态时，对新鲜更新具有更高需求。我们提出了一种度量标准，通过引入两个信息年龄变量来捕捉随机过程每个状态下状态更新的新鲜度，从而将信息年龄的定义扩展到考虑随机过程的状态变化。我们将问题建模为马尔可夫决策过程，利用基于信息年龄和随机过程状态应用线性和非线性惩罚的转移成本函数。通过理论分析，我们深入研究了所得马尔可夫决策过程问题的最优传输策略结构。此外，我们通过数值结果评估了所推导策略，并证明了其在预判即将到来的报警状态时储备能量的有效性。