Target Wake Time Scheduling for Time-sensitive and Energy-efficient Wi-Fi Networks

2025-09-30

AI Summary

To address the dual requirements of time-sensitive and energy-efficient communication in industrial IoT, this paper focuses on the Target Wake Time (TWT) mechanism in Wi-Fi 6/7 and formally introduces the TWT Admission and Scheduling Problem (TASP)—the first such formulation—establishing a joint optimization framework balancing throughput, energy efficiency, and information freshness (quantified by Age of Information, AoI). We propose TASPER, an efficient heuristic algorithm that schedules non-overlapping TWT service periods to eliminate channel contention and guarantee deterministic low-latency transmission. Evaluated on an ns-3-based TWT simulation platform, TASPER reduces average transmission rejection cost by 24.97% and improves energy efficiency by 14.86% over ShortestFirst; it further achieves 34% energy savings and a 26% reduction in rejection cost compared to HSA. Real-world validation on a 10-node testbed confirms end-to-end real-time performance guarantees.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Time Sensitive Networking (TSN) is fundamental for the reliable, low-latency networks that will enable the Industrial Internet of Things (IIoT). Wi-Fi has historically been considered unfit for TSN, as channel contention and collisions prevent deterministic transmission delays. However, this issue can be overcome by using Target Wake Time (TWT), which enables the access point to instruct Wi-Fi stations to wake up and transmit in non-overlapping TWT Service Periods (SPs), and sleep in the remaining time. In this paper, we first formulate the TWT Acceptance and Scheduling Problem (TASP), with the objective to schedule TWT SPs that maximize traffic throughput and energy efficiency while respecting Age of Information (AoI) constraints. Then, due to TASP being NP-hard, we propose the TASP Efficient Resolver (TASPER), a heuristic strategy to find near-optimal solutions efficiently. Using a TWT simulator based on ns-3, we compare TASPER to several baselines, including HSA, a state-of-the-art solution originally designed for WirelessHART networks. We demonstrate that TASPER obtains up to 24.97% lower mean transmission rejection cost and saves up to 14.86% more energy compared to the leading baseline, ShortestFirst, in a challenging, large-scale scenario. Additionally, when compared to HSA, TASPER also reduces the energy consumption by 34% and reduces the mean rejection cost by 26%. Furthermore, we validate TASPER on our IIoT testbed, which comprises 10 commercial TWT-compatible stations, observing that our solution admits more transmissions than the best baseline strategy, without violating any AoI deadline.

Problem

• Scheduling Wi-Fi transmissions for deterministic delays in industrial networks
• Maximizing throughput and energy efficiency with age constraints
• Solving NP-hard scheduling via heuristic approach for TWT optimization

Innovation

• Target Wake Time scheduling for deterministic Wi-Fi transmission
• Heuristic TASPER strategy solving NP-hard scheduling problem
• Energy-efficient scheduling with Age of Information constraints