We consider a multi-source status update system in which status updates are transmitted as packets containing the measured value of the monitored process and a time stamp representing the time when the sample was generated. The packets of each source are generated according to the Poisson process and the packets are served according to an exponentially distributed service time. We assume that the received status update packets needs further processing before being used (hence, computation-intensive). This is mathematically modeled by introducing an additional server at the sink node. The sink server serves the packets according to an exponentially distributed service time. We introduce two packet management policies, namely, i) a preemptive policy and ii) a blocking policy and derive the moment generating function (MGF) of the AoI of each source under both policies. In the preemptive policy, a new arriving packet preempts any possible packet that is currently under service regardless of the packet's source index. In the blocking policy, when a server is busy at the arrival instant of a packet the arriving packet is blocked and cleared. We assume that the same preemptive/blocking policy is employed in both transmitter and sink servers. Numerical results are provided to assess the results.
翻译:我们考虑一个多源状态更新系统,在该系统中,状态更新是作为包含监测过程的测量值的包件传送的,时间戳是样本生成的时间。每个源的包包是根据 Poisson 程序生成的,而包包则根据指数分布的服务时间提供服务。我们假设收到的状态更新包在使用之前需要进一步处理(因此,计算密集程度),这是通过在水槽节点引入一个额外的服务器而数学模型化的。汇服务器根据指数分布的服务时间为包件服务。我们引入了两个包管理政策,即:i)先发制人政策;ii)封存政策,并根据两种政策推导出每个源的AoI 的瞬时生成功能(MGF)。在先发货政策中,新到达的包在使用之前需要进一步处理,而不论包包的源索引为何。在封件政策中,当服务器在包裹到达时忙于包裹到达时,包裹被阻塞并被清除。我们假设在发机和水槽服务器中都使用同样的先发制/封政策。Numerical的结果是用来评估结果。