A Markov Game of Age of Information From Strategic Sources With Full Online Information
Abstract
We investigate the performance of concurrent remote sensing from independent strategic sources, whose goal is to minimize a linear combination of the freshness of information and the updating cost. In the literature, this is often investigated from a static perspective of setting the update rate of the sources a priori, either in a centralized optimal way or with a distributed game-theoretic approach. However, we argue that truly rational sources would better make such a decision with full awareness of the current age of information, resulting in a more efficient implementation of the updating policies. To this end, we investigate the scenario where sources independently perform a stateful optimization of their objective. Their strategic character leads to the formalization of this problem as a Markov game, for which we find the resulting Nash equilibrium. This can be translated into practical smooth threshold policies for their update. The results are eventually tested in a sample scenario, comparing a centralized optimal approach with two distributed approaches with different objectives for the players.
- Publication:
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arXiv e-prints
- Pub Date:
- February 2023
- DOI:
- 10.48550/arXiv.2302.12596
- arXiv:
- arXiv:2302.12596
- Bibcode:
- 2023arXiv230212596P
- Keywords:
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- Computer Science - Computer Science and Game Theory;
- Computer Science - Networking and Internet Architecture