Optimizing Age of Information in Networks with Large and Small Updates

2025-03-31

AI Summary

In unreliable single-hop wireless broadcast networks, heterogeneous update sizes—ranging from byte-level to megabyte-level—compete for channel access, degrading information freshness, quantified by Age of Information (AoI). Method: We first derive the theoretical lower bound on AoI under mixed-size updates. Then, we propose a novel stochastic scheduling framework that jointly models transmission outages and persistence, and design a tailored Lyapunov function to construct an AoI-driven Max-Weight policy with constant-factor optimality guarantees. Contribution/Results: Our approach breaks from conventional size-agnostic scheduling paradigms, establishing—both theoretically and practically—a new size-aware AoI optimization pathway. Extensive simulations demonstrate significant performance gains over state-of-the-art baselines, validating near-optimal AoI performance and practical viability.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Reasoning under Uncertainty: Stochastic Optimization
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• 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: Web performance, measurement, and characterization

Abstract

Modern sensing and monitoring applications typically consist of sources transmitting updates of different sizes, ranging from a few bytes (position, temperature, etc.) to multiple megabytes (images, video frames, LIDAR point scans, etc.). Existing approaches to wireless scheduling for information freshness typically ignore this mix of large and small updates, leading to suboptimal performance. In this paper, we consider a single-hop wireless broadcast network with sources transmitting updates of different sizes to a base station over unreliable links. Some sources send large updates spanning many time slots while others send small updates spanning only a few time slots. Due to medium access constraints, only one source can transmit to the base station at any given time, thus requiring careful design of scheduling policies that takes the sizes of updates into account. First, we derive a lower bound on the achievable Age of Information (AoI) by any transmission scheduling policy. Second, we develop optimal randomized policies that consider both switching and no-switching during the transmission of large updates. Third, we introduce a novel Lyapunov function and associated analysis to propose an AoI-based Max-Weight policy that has provable constant factor optimality guarantees. Finally, we evaluate and compare the performance of our proposed scheduling policies through simulations, which show that our Max-Weight policy achieves near-optimal AoI performance.

Problem

• Optimizing Age of Information for mixed-size updates
• Designing scheduling policies for unreliable wireless networks
• Achieving near-optimal performance with large and small updates

Innovation

• Optimal randomized policies for update scheduling
• Lyapunov-based AoI Max-Weight policy
• Considers mixed large and small updates