Spatiotemporal Analysis for Age of Information in Random Access Networks under Last-Come First-Serve with Replacement Protocol

TL;DR

This paper develops an analytical framework combining queueing theory and stochastic geometry to analyze and optimize the age-of-information in random access networks with a last-come first-serve with replacement protocol, revealing how network density and access strategies impact AoI.

Contribution

It introduces a novel analytical model for AoI in spatiotemporal networks and proposes a decentralized channel access policy that adapts to network conditions to minimize AoI.

Findings

LCFS with replacement can optimize AoI depending on deployment density.

Slotted ALOHA reduces AoI at high packet arrival rates.

Proposed scheme adapts to network size, improving AoI performance.

Abstract

We investigate the age-of-information (AoI) in the context of random access networks, in which transmitters need to send a sequence of information packets to the intended receivers over a shared spectrum. Due to interference, the dynamics at the link pairs will interact with each other over both space and time, and the effects of these spatiotemporal interactions on the AoI are not well understood. In this paper, we straddle queueing theory and stochastic geometry to establish an analytical framework, that accounts for the interplay between the temporal traffic attributes and spatial network topology, for such a study. Specifically, we derive accurate and tractable expressions to quantify the network average AoI as well as the outage probability of peak AoI. Besides, we develop a decentralized channel access policy that exploits the local observation at each node to make transmission decisions that minimize the AoI. Our analysis reveals that when the packet transmissions are scheduled in a last-come first-serve (LCFS) order, whereas the newly incoming packets can replace the undelivered ones, depending on the deployment density, there may or may not exist a tradeoff on the packet arrival rate that minimizes the network average AoI. Moreover, the slotted ALOHA protocol is shown to be instrumental in reducing the AoI when the packet arrival rates are high, yet it cannot contribute to decreasing the AoI in the regime of infrequent packet arrivals. The numerical results also confirm the efficacy of the proposed scheme, where the gain is particularly pronounced when the network grows in size because our method is able to adapt the channel access probabilities with the change of ambient environment.