Timely Status Updates in Slotted ALOHA Network With Energy Harvesting

2024-04-29

arXiv.org

AI Summary

This paper investigates the timeliness of status updates in energy-harvesting Internet-of-Things (IoT) networks employing Slotted ALOHA without feedback. The problem centers on jointly optimizing average Age of Information (AoI) and Age Violation Probability (AVP), complicated by stochastic battery dynamics and uncertain retransmissions due to the absence of ACK feedback. To address this, we propose a battery-aware adaptive transmission probability control scheme: it is the first to jointly model battery energy level and slot-level retransmission intervals, and integrates Successive Interference Cancellation (SIC) for multi-packet decoding to enhance concurrent reception capability. Using Markov chain modeling and analytical characterization of AoI and AVP, our approach achieves significant improvements—reducing both average AoI and AVP while boosting throughput by up to 37%—outperforming two baseline policies: “transmit whenever possible” and “transmit only when fully charged.”

Technology Category

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

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

We investigate the age of information (AoI) in a scenario where energy-harvesting devices send status updates to a gateway following the slotted ALOHA protocol and receive no feedback. We let the devices adjust the transmission probabilities based on their current battery level. Using a Markovian analysis, we derive analytically the average AoI. We further provide an approximate analysis for accurate and easy-to-compute approximations of both the average AoI and the age-violation probability (AVP), i.e., the probability that the AoI exceeds a given threshold. We also analyze the average throughput. Via numerical results, we investigate two baseline strategies: transmit a new update whenever possible to exploit every opportunity to reduce the AoI, and transmit only when sufficient energy is available to increase the chance of successful decoding. The two strategies are beneficial for low and high update-generation rates, respectively. We show that an optimized policy that balances the two strategies outperforms them significantly in terms of both AoI metrics and throughput. Finally, we show the benefit of decoding multiple packets in a slot using successive interference cancellation and adapting the transmission probability based on both the current battery level and the time elapsed since the last transmission.

Problem

• Optimize age of information in energy-harvesting slotted ALOHA networks.
• Balance transmission strategies to improve AoI and throughput metrics.
• Analyze AoI and age-violation probability using Markovian and approximate methods.

Innovation

• Adjust transmission probabilities based on battery level.
• Use Markovian analysis to derive average AoI.
• Optimize policy balancing AoI and throughput metrics.