Predictive Wireless Based Status Update for Communication-Agnostic Sampling

TL;DR

This paper introduces a novel status-aware communication scheme for wireless sensor networks that enables sensors to operate independently of communication constraints by using online predictions to decide when to transmit status updates.

Contribution

It proposes a communication-agnostic scheme based on online status prediction, reducing channel occupancy while maintaining low error in status recovery.

Findings

Significantly reduces channel occupancy with online predictions.

Maintains low status recovery error.

Improves safety in vehicle platooning and flight control scenarios.

Abstract

In a wireless network that conveys status updates from sources (i.e., sensors) to destinations, one of the key issues studied by existing literature is how to design an optimal source sampling strategy on account of the communication constraints which are often modeled as queues. In this paper, an alternative perspective is presented -- a novel status-aware communication scheme, namely \emph{parallel communications}, is proposed which allows sensors to be communication-agnostic. Specifically, the proposed scheme can determine, based on an online prediction functionality, whether a status packet is worth transmitting considering both the network condition and status prediction, such that sensors can generate status packets without communication constraints. We evaluate the proposed scheme on a Software-Defined-Radio (SDR) test platform, which is integrated with a collaborative autonomous driving simulator, i.e., Simulation-of-Urban-Mobility (SUMO), to produce realistic vehicle control models and road conditions. The results show that with online status predictions, the channel occupancy is significantly reduced, while guaranteeing low status recovery error. Then the framework is applied to two scenarios: a multi-density platooning scenario, and a flight formation control scenario. Simulation results show that the scheme achieves better performance on the network level, in terms of keeping the minimum safe distance in both vehicle platooning and flight control.