Distributed Real-Time Control for Minimizing AoI in Random Access Networks
- Authors
- Xie, H.; Jeon, S.-W.; Jin, H.
- Issue Date
- Apr-2025
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Age of Information; distributed activation probability; online estimation; random access
- Citation
- IEEE Internet of Things Journal, v.12, no.8, pp 10524 - 10538
- Pages
- 15
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE Internet of Things Journal
- Volume
- 12
- Number
- 8
- Start Page
- 10524
- End Page
- 10538
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/125171
- DOI
- 10.1109/JIOT.2024.3513408
- ISSN
- 2372-2541
2327-4662
- Abstract
- The freshness of information is crucial for IoT applications such as remote sensing systems and real-time status updates. The overabundance of stale information at the destination can potentially compromise the accuracy and reliability of system decision-making processes. To address this concern, a new metric termed the age of information (AoI) has been proposed to capture the freshness of status updates. In this paper, we present an analytical framework to establish a dual-action guideline for minimizing the average AoI in random access networks. We then utilize this guideline to propose two online activation control protocols: the age-dependent activation control (ADAC) algorithm and the threshold-based ADAC (T-ADAC) algorithm. The former prioritizes the activation of devices with higher instantaneous AoI, while the latter enables a device to be active with a dynamic probability only when its instantaneous AoI is beyond a predetermined threshold. Extensive simulations demonstrate the effectiveness of the proposed ADAC and T-ADAC, showing that our proposed algorithms outperform the state-of-the-art approaches in random access networks. Specifically, the proposed methods can achieve maximum throughput and minimum average AoI, showcasing their superior performance in real-world scenarios. © 2014 IEEE.
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