Iterated Piecewise-Stationary Random Functions

Ghosh, Ramen; Marecek, Jakub; Shorten, Robert

doi:10.48550/arxiv.1909.10093

Cited by 1 publication

(1 citation statement)

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“…When we cannot rely on the probabilities and the transformations in the iterated function system being invariant over time, or perfectly known to us, there are still at least two options. Either we can consider the notion of piece-wise stationary measures [36] for a time-varying iterated function system [36], or we can consider perturbation analysis, also known as sensitivity analysis. There, it is of interest to know whether a perturbation in the states causes a large difference in the behavior of the corresponding stochastic process.…”

Section: Problem Statementmentioning

confidence: 99%

Predictability and Fairness in Social Sensing

Ghosh,

Marecek,

Griggs

et al. 2020

Preprint

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In many applications, one may benefit from the collaborative collection of data for sensing a physical phenomenon, which is known as social sensing. We show how to make social sensing (1) predictable, in the sense of guaranteeing that the number of queries per participant will be independent of the initial state, in expectation, even when the population of participants varies over time, and (2) fair, in the sense of guaranteeing that the number of queries per participant will be equalised among the participants, in expectation, even when the population of participants varies over time.In a use case, we consider a large, high-density network of participating parked vehicles. When awoken by an administrative centre, this network proceeds to search for moving, missing entities of interest using RFID-based techniques. We regulate what vehicles are actively searching for the moving entity of interest at any point in time. In doing so, we seek to equalise vehicular energy consumption across the network. This is illustrated with simulations of the search for a missing Alzheimer's patient in Melbourne, Australia.

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Section: Problem Statementmentioning

confidence: 99%