We design efficient online scheduling policies to maximize the freshness of information delivered to the users in a cellular network under both adversarial and stochastic channel and mobility assumptions. The information freshness achieved by a policy is investigated through the lens of a recently proposed metric - Age-of-Information (AoI). We show that a natural greedy scheduling policy is competitive against any optimal offline policy in minimizing the AoI in the adversarial setting. We also derive universal lower bounds to the competitive ratio achievable by any online policy in the adversarial framework. In the stochastic setting, we show that a simple index policy is near-optimal for minimizing the average AoI in two different mobility scenarios. Further, we prove that the greedy scheduling policy minimizes the peak AoI for static users in the stochastic setting. Simulation results show that the proposed policies perform well under realistic conditions.

中文翻译：

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在对抗性和随机环境中优化信息时代


我们设计有效的在线调度策略，以在对抗性和随机信道和移动性假设下最大限度地提高蜂窝网络中向用户传递的信息的新鲜度。通过最近提出的指标——信息年龄（AoI）来调查政策所实现的信息新鲜度。我们证明，在对抗性环境中，自然贪婪调度策略在最小化 AoI 方面比任何最优离线策略都具有竞争力。我们还得出了对抗性框架中任何在线政策可实现的竞争率的普遍下限。在随机设置中，我们表明简单的索引策略对于最小化两种不同移动场景中的平均 AoI 来说是近乎最优的。此外，我们证明贪婪调度策略可以最小化随机设置中静态用户的峰值 AoI。模拟结果表明，所提出的政策在现实条件下表现良好。