Cross-Layer QoS Optimization of Wireless Sensor Network for Smart Grid

Abstract

Wireless Sensor Network (WSN) has been considered as a promising solution for Smart Grid due to the significant advantages over traditional communication technologies. However, as a necessary function for monitoring, diagnosing, and controlling of remote electrical equipment, Quality of Service (QoS) is still a challenging problem in applying WSN in Smart Grid. This paper presents a comprehensive experimental study on optimization of multiobject QoS in cross-layers of WSN protocol. In PHY layer, a Link Quality Estimator is studied for the purpose of evaluating link quality under harsh Smart Grid environments. In MAC layer, a QoS Enhanced MAC algorithm is used to prevent disorderly contentions among nodes and to allocate more channel resources for critical traffic; in NWK layer, a routing algorithm is introduced for multiobject QoS optimization. All the algorithms are cooperated with each other in cross-layer manner to improve end-to-end reliability and latency. In comparison with other counterparts, the proposed algorithms achieve preferable performances. Finally, field experiments were conducted, the result of which showed that the proposed algorithms outperform the ZigBee protocol and the original Distribution Grid wireless communication technology in terms of the QoS performance of critical traffic.

Wireless Sensor Network Based Smart Grid Communications: Challenges, Protocol Optimizations, and Validation Platforms

“…Link quality estimation is a prerequisite for higher layer protocols to improve the end-to-end data delivery and overcome low-power link unreliability in harsh smart grid environments. We notice that most approaches proposed for WSN-based smart grid applications leverage on simple link quality estimators, such as PRR, [54,60,67,66]. However, it is now well known that PRR is inaccurate as it is only able to provide one link aspect, link delivery, and ignores other important aspects such as link asymmetry [8].…”

“…QoS differentiation can be performed at different layers, including network [54,50] and MAC [2,3,60,4] layers. It can also be performed at several layers.…”

“…It can also be performed at several layers. It is thus referred to as a cross-layer QoS optimization scheme, such as in [60]. The proposed solution consists of a MAC and a routing algorithm with QoS support.…”

Wireless Sensor Network Optimization: Multi-Objective Paradigm

“…Optimal deployment of heterogeneous WSN has been considered in [ 106 ] to optimize the coverage, average number of hops and network reliability. Deployment of WSN for smart grid communication has been addressed in [ 107 ] by optimizing coverage and end-to-end latency. In [ 108 ], a technique for optimal deployment of sensor network has been proposed to optimize the coverage efficiency and lifetime of the network.…”