Performance trade-offs in cyber-physical control applications with multi-connectivity

TL;DR

This paper explores how multi-interface wireless communication can improve cyber-physical control systems by balancing latency, reliability, and energy use, using a POMDP model based on real LTE and Wi-Fi data.

Contribution

It introduces a POMDP-based framework for optimizing interface diversity policies in cyber-physical systems, considering realistic error statistics from LTE and Wi-Fi.

Findings

POMDP approach achieves near-optimal performance, within 0.1% of the theoretical maximum.

Model effectively captures error burst behavior using Gilbert-Elliott parameters.

Interface diversity policies adapt well to changing link conditions.

Abstract

Modern communication devices are often equipped with multiple wireless communication interfaces with diverse characteristics. This enables exploiting a form of multi-connectivity known as interface diversity to provide path diversity with multiple communication interfaces. Interface diversity helps to combat the problems suffered by single-interface systems due to error bursts in the link, which are a consequence of temporal correlation in the wireless channel. The length of an error burst is an essential performance indicator for cyber-physical control applications with periodic traffic, as these define the period in which the control link is unavailable. However, the available interfaces must be correctly orchestrated to achieve an adequate trade-off between latency, reliability, and energy consumption. This work investigates how the packet error statistics from different interfaces impacts the overall latency-reliability characteristics and explores mechanisms to derive adequate interface diversity policies. For this, we model the optimization problem as a partially observable Markov Decision Process (POMDP), where the state of each interface is determined by a Gilbert-Elliott model whose parameters are estimated based on experimental measurement traces from LTE and Wi-Fi. Our results show that the POMDP approach provides an all-round adaptable solution, whose performance is only 0.1% below the absolute upper bound, dictated by the optimal policy under the impractical assumption of full observability.