论文标题
及时的组更新
Timely Group Updating
论文作者
论文摘要
我们考虑两个密切相关的问题：传感器网络中的异常检测以及对人类种群感染的测试。在这两个问题上，我们都有$ n $ nodes（传感器，人类），每个节点都会表现出感兴趣的事件（异常，感染），概率$ p $。我们希望跟踪中心位置所有节点的异常/感染状态。我们开发了一个$ group $ $更新$方案，类似于小组测试，该方案通过适当地分组其个人身份来更新有关每个人群状态的中心位置。与使用预期的测试数量作为度量的组测试不同，在组更新中，我们将中央位置的预期信息年龄作为度量。我们确定最佳群体规模，以最大程度地减少信息年龄。我们表明，当$ p $很小时，与顺序更新策略相比，建议的组更新策略的年龄较小。
We consider two closely related problems: anomaly detection in sensor networks and testing for infections in human populations. In both problems, we have $n$ nodes (sensors, humans), and each node exhibits an event of interest (anomaly, infection) with probability $p$. We want to keep track of the anomaly/infection status of all nodes at a central location. We develop a $group$ $updating$ scheme, akin to group testing, which updates a central location about the status of each member of the population by appropriately grouping their individual status. Unlike group testing, which uses the expected number of tests as a metric, in group updating, we use the expected age of information at the central location as a metric. We determine the optimal group size to minimize the age of information. We show that, when $p$ is small, the proposed group updating policy yields smaller age compared to a sequential updating policy.
