信息年龄敏感的稀疏移动群智感知机制  

Age-of-information-aware Sparse Mobile Crowdsensing Mechanism

作　　者：赵雅馨 肖明军[1,2] ZHAO Ya-Xin;XIAO Ming-Jun(School of Computer Science and Technology,University of Science and Technology of China,Hefei 230027,China;Suzhou Institute for Advanced Research,University of Science and Technology of China,Suzhou 215004,China)

机构地区：[1]中国科学技术大学计算机科学与技术学院,合肥230027 [2]中国科学技术大学苏州高等研究院,苏州215004

出　　处：《计算机系统应用》2024年第8期115-122,共8页Computer Systems & Applications

基　　金：国家自然科学基金面上项目(62172386,61872330);江苏省自然科学基金面上项目(BK20231212)。

摘　　要：稀疏移动群智感知是一种新兴的模式,它从感知区域的子集收集数据,然后推理其他区域的数据.然而,在实际应用中,工人不足或分布不均的情况广泛存在.因此,在有限的预算下,必须优先选择相对更重要的工人收集数据.此外,许多稀疏移动群智感知应用对数据的时效性要求较高.因此本文将考虑数据的新鲜度,并使用信息年龄作为新鲜度指标.为了解决这些挑战,本文提出了一种轻量级年龄敏感的数据感知和推理框架.该框架旨在预算约束下,选择合适的工人收集数据,并通过准确捕捉感知数据时空关系进行数据推理,以优化信息年龄和推理的准确性.由于预算和工人有限,可能会导致数据量较少的情况.因此,本文还提出了精简数据推理模型的方法,以提高推理效率.通过广泛的实验进一步论证了该框架在实际应用中的优越性.Sparse mobile crowdsensing(MCS)is an emerging paradigm that collects data from a subset of sensing areas and then infers data from other areas.However,there is a shortage or uneven distribution of workers when sparse MCS is applied.Therefore,with a limited budget,it is important to prioritize the involvement of the more important workers in data collection.Additionally,many sparse MCS applications require timely data.Consequently,this study considers data freshness,with age of information(AoI)serving as a freshness metric.To address these challenges,a simplified AoIaware sensing and inference(SASI)framework is proposed in this study.This framework aims to optimize AoI and inference accuracy by selecting suitable workers for data collection under budget constraints and accurately capturing spatiotemporal relationships in sensed data for inference.Moreover,limited budgets and worker availability may result in a reduced volume of data.Thus,methods for streamlining data inference models are also proposed to enhance inference efficiency.Experiments have substantiated the superiority of this framework in practice.

关 键 词：稀疏移动群智感知 信息年龄 强化学习 工人选择 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]