Timely Status Update in Massive IoT Systems: Decentralized Scheduling for Wireless Uplinks

TL;DR

This paper proposes a decentralized scheduling policy for massive IoT systems that minimizes age-of-information, demonstrating its optimality and asymptotic performance, with practical implementation considerations.

Contribution

It introduces the RR-ONE policy for decentralized AoI minimization and proves its optimality and asymptotic optimality in massive IoT scenarios.

Findings

RR-ONE is optimal among AIR policies for AoI minimization.

RR-ONE is asymptotically optimal in massive IoT regimes.

Decentralized implementation of RR-ONE accommodates dynamic terminals.

Abstract

In a typical Internet of Things (IoT) application where a central controller collects status updates from multiple terminals, e.g., sensors and monitors, through a wireless multiaccess uplink, an important problem is how to attain timely status updates autonomously. In this paper, the timeliness of the status is measured by the recently proposed age-of-information (AoI) metric; both the theoretical and practical aspects of the problem are investigated: we aim to obtain a scheduling policy with minimum AoI and, meanwhile, still suitable for decentralized implementation on account of signalling exchange overhead. Towards this end, we first consider the set of arrival-independent and renewal (AIR) policies; the optimal policy thereof to minimize the time-average AoI is proved to be a round-robin policy with one-packet (latest packet only and others are dropped) buffers (RR-ONE). The optimality is established based on a generalized Poisson-arrival-see-time-average (PASTA) theorem. It is further proved that RR-ONE is asymptotically optimal among all policies in the massive IoT regime. The AoI steady-state stationary distribution under RR-ONE is also derived. A fully decentralized implementation of RR-ONE is proposed which can accommodate dynamic terminal appearances. In addition, considering scenarios where packets cannot be dropped, the optimal AIR policy thereof is also found with parameters given by the solution to a convex problem.