论文标题
在对抗和随机环境中优化信息年龄
Optimizing Age-of-Information in Adversarial and Stochastic Environments
论文作者
论文摘要
我们设计有效的在线调度策略，以最大程度地提高在对抗和随机渠道和移动性假设下，在蜂窝网络中传达给用户的新鲜信息。通过最近提出的报告年龄（AOI）的镜头研究了政策获得的新鲜信息。我们表明，自然的贪婪调度政策与任何最佳离线政策具有竞争力，以最大程度地减少对抗环境中的AOI。我们还将在对抗性框架中任何在线政策中实现的竞争比率获得普遍的下限。在随机环境中，我们表明，在两种不同的移动性场景中，简单的索引策略几乎是最佳的，可以最大程度地减少平均AOI。此外，我们证明，贪婪的调度策略最小化了随机环境中静态用户的峰值AOI。仿真结果表明，所提出的政策在现实条件下表现良好。
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.
