Abstract
The successful realization of smart energy management relies on ubiquitous and reliable information exchange among millions of sensors and actuators deployed in the field with little or no human intervention. This motivates us to introduce a unified communication framework for smart energy management by exploring the integration of software-defined networking (SDN) with M2M communication. In this chapter, the overall design of the software-defined M2M (SD-M2M) framework is presented, with an emphasis on its technical contributions to cost reduction, fine granularity resource allocation, and end-to-end QoS guarantee. Then, a case study is conducted for a electric vehicle energy management system to validate the introduced SD-M2M framework.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Zhou, Z., Sun, C., Shi, R., Chang, Z., Zhou, S., Li, Y.: Robust energy scheduling in vehicle-to-grid networks. IEEE Netw. 31(2), 30–37 (2017)
Zhou, Z., Xiong, F., Huang, B., Xu, C., Jiao, R., Liao, B., Yin, Z., Li, J.: Game-theoretical energy management for energy Internet with big data-based renewable power forecasting. IEEE Access. 5, 1–14 (2017)
Gong, J., Zhou, S., Zhou, Z., Niu, Z.: Policy optimization for content push via energy harvesting small cells in heterogeneous networks. IEEE Trans. Wireless Commun. 16(2), 717–729 (2016)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Zhou, Z., Chang, Z., Liao, H. (2021). Software Defined Machine-to-Machine Communication for Smart Energy Management in Power Grids. In: Green Internet of Things (IoT): Energy Efficiency Perspective. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-64054-5_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-64054-5_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-64053-8
Online ISBN: 978-3-030-64054-5
eBook Packages: Computer ScienceComputer Science (R0)