Reliability- and Connectivity-Constrained Age-of-Information Optimization for UAV Swarm IoT Data Collection

Abstract

Uncrewed aerial vehicle~(UAV) swarms provide a flexible platform for Internet of Things~(IoT) data collection by gathering delay-sensitive measurements from distributed sensor clusters and relaying them to a fusion center~(FC). Between successive updates, the FC estimates the current value of each monitored quantity; however, the estimation accuracy degrades as the last update ages. Such missions require jointly optimizing estimation accuracy, short-packet communication reliability, and swarm connectivity, yet existing approaches typically prioritize freshness while neglecting its impact on connectivity. This paper proposes a topology-coupled urgency~(TCU) scheduler that minimizes the FC's accumulated estimation error while incorporating the swarm's expected algebraic connectivity into the scheduling objective. The resulting connectivity reward encourages idle UAVs to reposition so as to preserve swarm connectivity. For each time slot, the resulting problem is a mixed-integer nonconvex program, which we solve by successive convex approximation. Specifically, the binary assignments are relaxed, while the connectivity reward is represented through a linear matrix inequality on the expected Laplacian. The finite-blocklength rate and the inter-UAV link reliability are linearized in the same convex subproblem, thereby preserving their coupling rather than separating them into alternating blocks. The integer assignments are subsequently recovered by Hungarian matching and verified against the original nonconvex constraints, while a deficit mechanism ensures long-term cluster coverage without requiring explicit long-horizon planning...