Our two papers have recently been accepted for publication in prestigious conferences!!
1-) MobiHoc 2025
Authors: Adem Utku Atasayar, Aimin Li, Çağrı Arı, Elif Uysal
Title: Fresh Data Delivery: Joint Sampling and Routing for Minimizing the Age of Information
Abstract: In this paper, we extend the freshness-oriented sampling problem by incorporating controlled delay statistics through heterogeneous routing options, where the Age of Information (AoI) serves as the metric for data freshness. Our objective is to jointly optimize sampling and routing policies to minimize the long-term average AoI, where the sender can choose to forward each status update over one of the available routes, which have distinct delay statistics. This problem is an infinite-horizon Semi-Markov Decision Process (SMDP) with an uncountable state space and a hybrid action space, consisting of discrete routing choices and continuous waiting times. We develop an efficient algorithm to solve this problem and theoretically establish that the optimal policy exhibits a threshold structure, characterized by: (i) a threshold-based monotonic handover mechanism for optimal routing, where the switching order aligns with the decreasing order of mean delays; and (ii) a multi-threshold piecewise linear waiting mechanism for optimal sampling, where the total number of thresholds is upper bounded by 2N-1, given N selectable routes. We implement the proposed algorithm in a satellite-terrestrial integrated routing scenario, and simulation results reveal an intriguing insight: routes with higher average delay or variance can still contribute to minimizing AoI.
2-) Allerton 2025
Authors: Aimin Li, Elif Uysal
Title: Optimal Sampling and Scheduling for Remote Fusion Estimation of Correlated Wiener Processes
Abstract: In distributed sensor networks, sensors often observe a dynamic process within overlapping regions. Due to random delays, these correlated observations arrive at the fusion center asynchronously, raising a central question: How can one fuse asynchronous yet correlated information for accurate remote fusion estimation? This paper addresses this challenge by studying the joint design of sampling, scheduling, and estimation policies for monitoring a correlated Wiener process. Though this problem is coupled, we establish a separation principle and identify the joint optimal policy: the optimal fusion estimator is a weighted-sum fusion estimator conditioned on Age of Information (AoI), the optimal scheduler is a Maximum Age First (MAF) scheduler that prioritizes the most stale source, and the optimal sampling can be designed given the optimal estimator and the MAF scheduler. To design the optimal sampling, we show that, under the infinite-horizon average-cost criterion, optimizing AoI is equivalent to optimizing MSE under pull-based communications, despite the presence of strong inter-sensor correlations. This structural equivalence allows us to identify the MSE-optimal sampler as one that is AoI-optimal. This result underscores an insight: information freshness can serve as a design surrogate for optimal estimation in correlated sensing environments.