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Optimizing the Age-of-Information for Mobile Users in Adversarial and Stochastic Environments
arXiv - CS - Performance Pub Date : 2020-11-10 , DOI: arxiv-2011.05563
Abhishek Sinha, Rajarshi Bhattacharjee

We study a multi-user downlink scheduling problem for optimizing the freshness of information available to users roaming across multiple cells. We consider both adversarial and stochastic settings and design scheduling policies that optimize two distinct information freshness metrics, namely the average age-of-information and the peak age-of-information. We show that a natural greedy scheduling policy is competitive with the optimal offline policy in the adversarial setting. We also derive fundamental lower bounds to the competitive ratio achievable by any online policy. In the stochastic environment, we show that a Max-Weight scheduling policy that takes into account the channel statistics achieves an approximation factor of $2$ for minimizing the average age of information in two extreme mobility scenarios. We conclude the paper by establishing a large-deviation optimality result achieved by the greedy policy for minimizing the peak age of information for static users situated at a single cell.

中文翻译:

在对抗性和随机环境中优化移动用户的信息时代

我们研究了一个多用户下行链路调度问题,以优化跨多个小区漫游的用户可用信息的新鲜度。我们考虑了对抗性和随机性设置以及优化两个不同信息新鲜度指标的设计调度策略,即平均信息年龄和峰值信息年龄。我们表明,在对抗性设置中,自然贪婪调度策略与最佳离线策略具有竞争力。我们还推导出任何在线政策可实现的竞争比率的基本下限。在随机环境中,我们展示了考虑到信道统计信息的最大权重调度策略实现了 2 美元的近似因子,以最小化两个极端移动场景中信息的平均年龄。
更新日期:2020-11-12
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