English

Competitive Algorithms for Minimizing the Maximum Age-of-Information

Information Theory 2020-05-13 v1 Performance math.IT

Abstract

In this short paper, we consider the problem of designing a near-optimal competitive scheduling policy for NN 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(lnN)O(\ln N) factor.

Keywords

Cite

@article{arxiv.2005.05873,
  title  = {Competitive Algorithms for Minimizing the Maximum Age-of-Information},
  author = {Rajarshi Bhattacharjee and Abhishek Sinha},
  journal= {arXiv preprint arXiv:2005.05873},
  year   = {2020}
}

Comments

Submitted to the workshop Mathematical performance Modeling and Analysis (MAMA) 2020

R2 v1 2026-06-23T15:29:36.538Z