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arXiv · 1902.03594

Max-Min Fair Sensor Scheduling: Game-theoretic Perspective and Algorithmic Solution

Shuang Wu·Xiaoqiang Ren·Yiguang Hong·Ling Shi
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Abstract

We consider the design of a fair sensor schedule for a number of sensors monitoring different linear time-invariant processes. The largest average remote estimation error among all processes is to be minimized. We first consider a general setup for the max-min fair allocation problem. By reformulating the problem as its equivalent form, we transform the fair resource allocation problem into a zero-sum game between a "judge" and a resource allocator. We propose an equilibrium seeking procedure and show that there exists a unique Nash equilibrium in pure strategy for this game. We then apply the result to the sensor scheduling problem and show that the max-min fair sensor scheduling policy can be achieved.

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Shuang Wu, Xiaoqiang Ren, Yiguang Hong, Ling Shi. 2019-02-10. Max-Min Fair Sensor Scheduling: Game-theoretic Perspective and Algorithmic Solution. https://doi.org/10.1109/tac.2020.3007400

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