Cost and Correlation in Strategic Wireless Sensing Driven by Age of Information

Abstract:
We extend available analytical studies that leverage queueing theory to compute closed-form expressions for the average AoI in queueing systems with multiple sources. Specifically, we consider the following original aspects. First, we assume that multiple sensors are producing interconnected measurements and therefore their status updates correlate with one another. We also consider a cost associated with the measurements and we finally apply non-cooperative game theory to derive the Nash equilibria of the resulting system. Differently from the standard multiple source system, which is analyzed in the literature from the only game theoretic standpoint of competing sources, we show that our system showcases collaborative-like behaviors thanks to correlation among the source transmissions. Moreover, the impact of a sensing cost is to decrease even further the aggressiveness of strategic users, which may lead to the opposite problem, a lower than optimal offered traffic to avoid costs.