AoI与样本挤压感知的通信调度算法仿真

Communication Scheduling Algorithm of AoI and Sample Extrusion Aware

AoI(Age of Information)是衡量数据新鲜度的性能指标。针对现有的AoI感知调度算法大多以最小化AoI为目标,而忽略了可能存在的样本挤压问题,提出一种基于贪心策略的算法。采用对于信息传输时间敏感的物联网系统,进行周期性采样。通过建立AoI及样本挤压模型,分析调度算法对它们的影响的基础上,设计算法同时兼顾长期平均AoI及样本挤压两个目标。仿真分析表明,与现有算法相比,在带宽受限时,上述算法可以有效缓解样本挤压现象,也能获得更好的长期平均AoI。

AoI is a performance indicator that measures the freshness of data. Most of the existing AoI-aware scheduling algorithms aimed at minimizing AoI, while ignoring the possible sample extrusion problem. An algorithm based on greedy strategy was proposed. The Internet of things(IoT) system, which was sensitive to information transmission time, was used for periodic sampling. Based on the establishment of AoI and sample extrusion models and the analysis of the impact of scheduling algorithm on them, an algorithm was designed, which took the two objectives of long-term average AoI and sample extrusion into account. Simulation experiment analysis shows that, compared with the existing algorithm, when the bandwidth is limited, the algorithm can effectively alleviate the sample extrusion phenomenon, and also obtain a better long-term average AoI.