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This paper introduces a new theoretical framework for optimizing second-order behaviors of wireless networks. Unlike existing techniques for network utility maximization, which only consider first-order statistics, this framework models every random process by its mean and temporal variance. The inclusion of temporal variance makes this framework well-suited for modeling Markovian fading wireless channels and emerging network performance metrics such as age-of-information (AoI) and timely-throughput. Using this framework, we sharply characterize the second-order capacity region of wireless access networks. We also propose a simple scheduling policy and prove that it can achieve every interior point in the second-order capacity region. To demonstrate the utility of this framework, we apply it to an unsolved network optimization problem where some clients wish to minimize AoI while others wish to maximize timely-throughput. We show that this framework accurately characterizes AoI and timely-throughput. Moreover, it leads to a tractable scheduling policy that outperforms other existing work.
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Understanding the Fundamental Trade-Off Between Age of Information and Throughput in Unreliable Wireless Networks
This paper characterizes the fundamental trade-off between throughput and Age of Information (AoI) in wireless networks where multiple devices transmit status updates to a central base station over unreliable channels. To address the complexity introduced by stochastic transmission successes, we propose the throughput-AoI capacity region, which defines all feasible throughput-AoI pairs achievable under any scheduling policy. Using a second-order approximation that incorporates both mean and temporal variance, we derive an outer bound and a tight inner bound for the throughput-AoI capacity region. Furthermore, we propose a simple and low complexity scheduling policy and prove that it achieves every interior point within the tight inner bound. This establishes a systematic and theoretically grounded framework for the joint optimization of throughput and information freshness in practical wireless communication scenarios. To validate our theoretical framework and demonstrate the utility of the throughput-AoI capacity region, extensive simulations are implemented. Simulation results demonstrate that our proposed policy significantly outperforms conventional methods across various practical network optimization scenarios. The findings highlight our approach's effectiveness in optimizing both throughput and AoI, underscoring its applicability and robustness in practical wireless networks.
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- Award ID(s):
- 2332800
- PAR ID:
- 10680768
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400713538
- Page Range / eLocation ID:
- 281 to 290
- Format(s):
- Medium: X
- Location:
- Rice University Houston TX USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1145/3704413.3764415
