We consider a status information updating system where a fusion center collects the status information from a large number of sources and each of them has its own age of information (AoI) constraints. A novel grouping-based scheduler is proposed to solve this complex large-scale problem by dividing the sources into different scheduling groups. The problem is then transformed into deriving the optimal grouping scheme. A two-step grouping algorithm (TGA) is proposed: 1) Given AoI constraints, we first identify the sources with harmonic AoI constraints, then design a fast grouping method and an optimal scheduler for these sources. Under harmonic AoI constraints, each constraint is divisible by the smallest one and the sum of reciprocals of the constraints with the same value is divisible by the reciprocal of the smallest one. 2) For the other sources without such a special property, we pack the sources which can be scheduled together with minimum update rates into the same group. Simulations show the channel usage of the proposed TGA is significantly reduced as compared to a recent work and is 0.42% larger than a derived lower bound when the number of sources is large.

翻译：考虑一个状态信息更新系统，其中融合中心从大量源收集状态信息，每个源都有其自身的信息时效（AoI）约束。提出了一种新颖的基于分组的调度器，通过将源划分为不同的调度组来解决这一复杂的大规模问题，进而将问题转化为推导最优分组方案。提出了一种两步分组算法（TGA）：1）在给定AoI约束下，首先识别具有谐波AoI约束的源，然后为这些源设计快速分组方法和最优调度器。在谐波AoI约束下，每个约束可被最小约束整除，且相同约束值的倒数之和可被最小约束的倒数整除。2）对于其他不具有该特殊属性的源，将能以最小更新速率共同调度的源打包到同一组中。仿真结果表明，与近期工作相比，所提出的TGA的信道使用率显著降低，且在源数量较大时仅比推导的下界高出0.42%。