Optimizing Age of Information in Networks with Large and Small Updates

TL;DR

The paper addresses AoI minimization in a single-hop wireless network where sources generate updates of varying sizes. It develops a universal lower bound and analyzes two classes of randomized policies (SRP and NSRP) with closed-form AoI expressions and constant-factor guarantees, plus a Lyapunov-based Max-Weight policy with a proven constant-factor bound. The Max-Weight policy, backed by a novel Lyapunov function that accounts for waiting, optimistic service time, and throughput debt, achieves near-optimal AoI across diverse network conditions, including unreliable channels and multi-packet updates. Through extensive simulations, the authors show that MW consistently outperforms switching/no-switching randomized policies and fixed MW baselines, particularly in non-symmetric update-length scenarios and larger networks. The work provides practical insights for age-sensitive scheduling in heterogeneous-update networks and introduces techniques with potential extensions to joint sampling and fairness considerations.

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.

Figures (10)

• Figure 1: Network with $N$ sources transmitting information updates to a base station (BS). Sources generate updates over time and keep only the freshest update. Updates from source $i\in\{1,\ldots,N\}$ are composed of $L_i$ data packets. The BS selects one source at every time slot $t$ to transmit a single packet via its unreliable wireless link.
• Figure 1: Average AoI associated with the plots in Fig. \ref{['fig:simple_non_sysmmetric']}.
• Figure 2: AoI evolution in a two-source network with reliable channels and sources 1 and 2 with update lengths $L_1=100$ and $L_2=2$, respectively. Each of the four plots are associated with a different scheduling policy: (a) no-switching; (b) switching twice during the update of source 1; (c) switching 10 times during the update of source 1; and (d) round robin. The average AoI is shown in Table \ref{['table:2sources']}
• Figure 3: Simulation results of two-source networks with varying weight $\alpha_1 \in \{1,2,\dots,10\}$ and update length $L_1 \in \{2,4,\dots,30\}$, while $\alpha_2 = 10$, $L_2 = 2$, and $p_1=p_2=0.5$ remain fixed.
• Figure 4: Simulation results for networks with varying channel reliabilities. The network comprises $N=10$ sources equally divided into Class 1 with $\alpha_i=5$ and $L_i=2$ and Class 2 with $\alpha_i=1$ and $L_i=50$. Channel reliabilities vary over $p_i \in \{0.2,\,0.15,\,\ldots,\,1\}$ for all sources.

Theorems & Definitions (27)

• Proposition 1
• proof
• Remark 2
• Theorem 3
• proof
• Proposition 4
• proof
• Theorem 5
• proof
• Proposition 6