How to Make Money From Fresh Data: Subscription Strategies in Age-Based Systems

TL;DR

This paper models a game-theoretic framework for a server and users in a data update system, optimizing subscription and sampling strategies to balance profit, costs, and information freshness in age-based systems.

Contribution

It introduces a Stackelberg game model for subscription strategies in age-based information systems, analyzing equilibrium strategies in directed networks.

Findings

Optimal equilibrium strategies for server and users identified.

Simulation confirms theoretical predictions and offers system insights.

Server can maximize profit while maintaining data freshness constraints.

Abstract

We consider a communication system consisting of a server that tracks and publishes updates about a time-varying data source or event, and a gossip network of users interested in closely tracking the event. The timeliness of the information is measured through the version age of information. The users wish to have their expected version ages remain below a threshold, and have the option to either rely on gossip from their neighbors or subscribe to the server directly to follow updates about the event if the former option does not meet the timeliness requirements. The server wishes to maximize its profit by increasing the number of subscribers and reducing costs associated with the frequent sampling of the event. We model the problem setup as a Stackelberg game between the server and the users, where the server commits to a frequency of sampling the event, and the users make decisions on whether to subscribe or not. As an initial work, we focus on directed networks with unidirectional flow of information and obtain the optimal equilibrium strategies for all the players. We provide simulation results to confirm the theoretical findings and provide additional insights.