Holistic link quality estimation-based routing metric for RPL networks in smart grids

Abstract

Wireless Sensor Networks (WSNs) have been recognized as a promising communication technology for smart grid monitoring and control applications. Unfortunately, environmental conditions in smart grids are complex and harsh (electromagnetic interference, obstructions, fading, etc.), which turns radio links extremely unreliable. Routing protocols play a crucial role to overcome low-power link unreliability in smart grid environments. Especially, RPL (IPv6 Routing Protocol for Low Power and Lossy Networks) is an IETF standard that is supposed to meet the requirements of WSN-based smart grid communications. RPL routing metric relies on link quality estimation through ETX (Expected Transmission Count) assessment, to identify high quality links for data delivery. However, ETX is not sufficiently accurate as it assesses a particular link aspect, number of packet retransmissions over the link, and ignores other important aspects such as channel quality. Consequently, as confirmed by recent experimental studies, RPL can fail to identify routing paths with high quality links leading to high packet loss rates. In this paper, we propose an alternative routing metric for RPL based on holistic link quality estimation, where several link metrics are combined. Based on COOJA simulations, we demonstrate that our proposed routing metric improves RPL performance over traditional routing metrics, including the RPL default metric, mainly in terms of packet loss ratio, end-to-end delay, energy efficiency, and topology stability.