arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2005.05873cs.ITcs.PFmath.IT
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最小化最大信息量的竞争算法

Competitive Algorithms for Minimizing the Maximum Age-of-Information

Rajarshi Bhattacharjee, Abhishek Sinha

摘要:

在这篇简短的论文中,我们考虑的问题,设计一个接近最优的竞争调度策略,$N$移动用户,最大限度地提高新鲜度的可用信息均匀地跨越所有用户。由于新兴的5G-mmWave信道对于高速用户的不可靠性和非平稳性,我们放弃了对无线信道和用户移动性的任何统计假设。相反,我们允许信道状态和移动模式由一个无所不知的对手决定。不难看出,在这种对抗模型中,对于相应的吞吐量最大化问题,不存在竞争性调度策略。令人惊讶的是,我们发现存在一个简单的在线分布式调度策略,具有有限的竞争比,以最大限度地提高信息的新鲜度,在这个对抗模型。此外,我们还证明了所提出的政策是竞争最优的$O(\ln N)$因素。

英文摘要:

In this short paper, we consider the problem of designing a near-optimal competitive scheduling policy for $N$ mobile users, to maximize the freshness of available information uniformly across all users. Prompted by the unreliability and non-stationarity of the emerging 5G-mmWave channels for high-speed users, we forego of any statistical assumptions of the wireless channels and user-mobility. Instead, we allow the channel states and the mobility patterns to be dictated by an omniscient adversary. It is not difficult to see that no competitive scheduling policy can exist for the corresponding throughput-maximization problem in this adversarial model. Surprisingly, we show that there exists a simple online distributed scheduling policy with a finite competitive ratio for maximizing the freshness of information in this adversarial model. Moreover, we also prove that the proposed policy is competitively optimal up to an $O(\ln N)$ factor.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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