Submitted to ICC 2024, IEEE International Conference on Communications, 9-13 June 2024, Denver, USA / Submitted to ArXiV, 10 November 2023
We study a pull-based communication system where a sensing agent updates an actuation agent using a query control policy, which is adjusted in the evolution of an observed information source and the usefulness of each update for achieving a specific goal. For that, a controller decides whether to pull an update at each slot, predicting what is probably occurring at the source and how much effective impact that update could have at
the endpoint. Thus, temporal changes in the source evolution could modify the query arrivals so as to capture important updates. The amount of impact is determined by a grade of effectiveness (GoE) metric, which incorporates both freshness and usefulness
attributes of the communicated updates. Applying an iterative algorithm, we derive query decisions that maximize the longterm average GoE for the communicated packets, subject to cost constraints. Our analytical and numerical results show that the proposed query policy exhibits higher effectiveness than existing periodic and probabilistic query policies for a wide range of query arrival rates.
© 2023 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.