多信息源场景下信息年龄的离散时间排队模型
Discrete-time Queueing Model of Age of Information with Multiple Information Sources
AI总结：
针对多源物联网状态更新系统的信息新鲜度问题，提出基于QBD型离散时间马尔可夫链的矩阵分析算法，求解三种排队规则下各源的AoI和PAoI精确分布，并验证模型有效性、探讨参数优化。
摘要：
基于物联网的状态更新系统中的信息新鲜度近来已通过信息年龄（Age of Information, AoI）和峰值信息年龄（Peak AoI, PAoI）性能指标得到研究。本文研究多源物联网系统中出现的一种离散时间服务器，该服务器接收来自多个信息源的传入信息分组，再将其转发至远程监控端以实现状态更新。在伯努利信息分组到达、所有源共用几何服务时间分布的假设下，我们针对三种不同排队规则——i）非抢占无缓冲（Non-Preemptive Bufferless, NPB）、ii）抢占无缓冲（Preemptive Bufferless, PB）、iii）带替换的非抢占单缓冲（Non-Preemptive Single Buffer with Replacement, NPSBR），以矩阵几何形式数值求解得到了每个源的AoI和PAoI的精确分布。所提出的数值算法采用拟生灭（Quasi-Birth-Death, QBD）型离散时间马尔可夫链（Discrete-Time Markov Chains, DTMC）理论，属于矩阵分析方法，即该算法基于数值稳定且高效的向量-矩阵运算。我们通过数值算例验证了所提排队模型的准确性与有效性，还给出了一个数值算例，探讨在具有不同AoI需求的双源实际物联网系统中伯努利参数的最优选择问题。
英文摘要：
Information freshness in IoT-based status update systems has recently been studied through the Age of Information (AoI) and Peak AoI (PAoI) performance metrics. In this paper, we study a discrete-time server arising in multi-source IoT systems which accepts incoming information packets from multiple information sources so as to be forwarded to a remote monitor for status update purposes. Under the assumption of Bernoulli information packet arrivals and a common geometric service time distribution across all the sources, we numerically obtain the exact per-source distributions of AoI and PAoI in matrix-geometric form for three different queueing disciplines: i) Non-Preemptive Bufferless (NPB) ii) Preemptive Bufferless (PB) iii) Non-Preemptive Single Buffer with Replacement (NPSBR). The proposed numerical algorithm employs the theory of Discrete-Time Markov Chains (DTMC) of Quasi-Birth-Death (QBD) type and is matrix analytical, i.e, the algorithm is based on numerically stable and efficient vector-matrix operations.Numerical examples are provided to validate the accuracy and effectiveness of the proposed queueing model. We also present a numerical example on the optimum choice of the Bernoulli parameters in a practical IoT system with two sources with diverse AoI requirements.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
