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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.04281 |
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| _version_ | 1866917955418193920 |
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| author | He, Yuqiao Chen, Yuchao Wang, Jintao Song, Jian |
| author_facet | He, Yuqiao Chen, Yuchao Wang, Jintao Song, Jian |
| contents | This study considers a wireless network where multiple nodes transmit status updates to a base station (BS) via a shared, error-free channel with limited bandwidth. The status updates arrive at each node randomly. We use the Age of Synchronization (AoS) as a metric to measure the information freshness of the updates. The AoS of each node has a timely-varying importance which follows a Markov chain. Our objective is to minimize the weighted sum AoS of the system. The optimization problem is relaxed and formulated as a constrained Markov decision process (CMDP). Solving the relaxed CMDP by a linear programming algorithm yields a stationary policy, which helps us propose a near-stationary policy for the original problem. Numerical simulations show that in most configurations, the AoS performance of our policy outperforms the policy choosing the maximum AoS regardless of weight variations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_04281 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Age of Synchronization Minimization in Wireless Networks with Random Updates and Time-Varying Timeliness Requirement He, Yuqiao Chen, Yuchao Wang, Jintao Song, Jian Information Theory This study considers a wireless network where multiple nodes transmit status updates to a base station (BS) via a shared, error-free channel with limited bandwidth. The status updates arrive at each node randomly. We use the Age of Synchronization (AoS) as a metric to measure the information freshness of the updates. The AoS of each node has a timely-varying importance which follows a Markov chain. Our objective is to minimize the weighted sum AoS of the system. The optimization problem is relaxed and formulated as a constrained Markov decision process (CMDP). Solving the relaxed CMDP by a linear programming algorithm yields a stationary policy, which helps us propose a near-stationary policy for the original problem. Numerical simulations show that in most configurations, the AoS performance of our policy outperforms the policy choosing the maximum AoS regardless of weight variations. |
| title | Age of Synchronization Minimization in Wireless Networks with Random Updates and Time-Varying Timeliness Requirement |
| topic | Information Theory |
| url | https://arxiv.org/abs/2410.04281 |