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• W3157788954 abstract "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." @default.
• W3157788954 created "2021-05-10" @default.
• W3157788954 creator A5000544057 @default.
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• W3157788954 date "2021-03-24" @default.
• W3157788954 modified "2023-09-24" @default.
• W3157788954 title "Timely Group Updating" @default.
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• W3157788954 doi "https://doi.org/10.1109/ciss50987.2021.9400248" @default.
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