Modelling Software-Defined Wireless Sensor Network Architectures for Smart Grid Neighborhood Area Networks

Full text for this resource is not available from the Research Repository.

Nafi, NS, Ahmed, Khandakar ORCID: 0000-0003-1043-2029 and Gregory, MA (2017) Modelling Software-Defined Wireless Sensor Network Architectures for Smart Grid Neighborhood Area Networks. In: Security Solutions and Applied Cryptography in Smart Grid Communications. Ferrag, M and Ahmim, A, eds. IGI Global, Hershey, PA, pp. 267-286.

Abstract

In a smart grid machine to machine communication environment, the separation of the control and data planes in the Software Defined Networking (SDN) paradigm increases flexibility, controllability and manageability of the network. A fully integrated SDN based WSN network can play a more prominent role by providing ‘last mile' connectivity while serving various Smart Grid applications and offer improved security, guaranteed Quality of Service and flexible interworking capabilities. Hence, more efforts are required to explore the potential role of SDN in Smart Grid communications and thereby ensure its optimum utilization. In this chapter we provide a description of how SDN technology can be used in WSN with an emphasis on its end-to-end network architecture. We then present its novel application to Advanced Metering Infrastructure, Substation Automation, Distributed Energy Resources, Wide Area Measurement Systems, and Roaming of Electric Vehicles in Smart Grids.

Dimensions Badge

Altmetric Badge

Item type Book Section
URI https://vuir.vu.edu.au/id/eprint/32704
DOI 10.4018/978-1-5225-1829-7.ch014
Official URL https://www.igi-global.com/gateway/chapter/172684
ISBN 9781522518297
Subjects Historical > FOR Classification > 0805 Distributed Computing
Current > Division/Research > College of Science and Engineering
Keywords Software Defined Networking (SDN); Network architecture; Wireless Sensor Networks
Citations in Scopus 1 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login