Age Optimal Sampling and Routing under Intermittent Links and Energy Constraints

2025-11-30

AI Summary

In satellite-terrestrial integrated networks, heterogeneous link delays, intermittent connectivity, and energy constraints jointly impede Age of Information (AoI) optimization. Method: We jointly optimize sampling instants and routing decisions to minimize a monotonic nonlinear AoI cost function, formulating the problem as an infinite-horizon constrained semi-Markov decision process (SMDP) with hybrid state-action spaces. Contribution/Results: We establish, for the first time, the structural properties of the optimal joint policy: routing follows a monotone switching policy based on link availability and delay, while sampling adopts a piecewise-linear waiting policy with finitely many breakpoints. Leveraging this structure, we propose an efficient nested algorithm, Bisec-ReaVI. Experiments demonstrate that our approach significantly reduces AoI while preserving energy efficiency; notably, high-delay or low-availability links are shown to play a critical role in AoI optimization under specific conditions.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Links in practical systems, such as satellite-terrestrial integrated networks, exhibit distinct delay distributions, intermittent availability, and heterogeneous energy costs. These characteristics pose significant challenges to maintaining timely and energy-efficient status updates. While link availability restricts feasible transmission routes, routing decisions determine the actual delay and energy expenditure. This paper tackles these challenges by jointly optimizing sampling and routing decisions to minimize monotonic, nonlinear Age of Information (AoI). The proposed formulation incorporates key system features, including multiple routes with correlated random delays, stochastic link availability, and route-dependent energy consumption. We model the problem as an infinite-horizon constrained semi-Markov decision process (CSMDP) with a hybrid state-action space and develop an efficient nested algorithm, termed Bisec-ReaVI, to solve this problem. We reveal a well-defined jointly optimal policy structure: (i) the optimal routing policy is a monotonic handover policy that adapts to the availability of routes and their mean delays; and (ii) the optimal sampling policy is a piecewise linear waiting policy, with at most "N choose 2 + N" breakpoints given N routes. Numerical experiments in a satellite-terrestrial integrated routing scenario demonstrate that the proposed scheme efficiently balances energy usage and information freshness, and reveal a counter-intuitive insight: even routes with higher average delay, higher delay variance, or lower availability can still play a critical role in minimizing monotonic functions of AoI.

Problem

• Optimizes sampling and routing to minimize Age of Information under intermittent links.
• Addresses energy constraints and random delays in multi-route satellite-terrestrial networks.
• Develops a policy structure balancing energy use and information freshness efficiently.

Innovation

• Jointly optimizes sampling and routing to minimize AoI
• Models problem as constrained semi-Markov decision process
• Proposes Bisec-ReaVI algorithm for efficient nested solution