DocumentCode
1485957
Title
Machine-to-machine communications for home energy management system in smart grid
Author
Niyato, Dusit ; Xiao, Lu ; Wang, Ping
Author_Institution
Nanyang Technol. Univ., Singapore, Singapore
Volume
49
Issue
4
fYear
2011
fDate
4/1/2011 12:00:00 AM
Firstpage
53
Lastpage
59
Abstract
Machine-to-machine (M2M) communications have emerged as a cutting edge technology for next-generation communications, and are undergoing rapid development and inspiring numerous applications. This article presents an investigation of the application of M2M communications in the smart grid. First, an overview of M2M communications is given. The enabling technologies and open research issues of M2M communications are also discussed. Then we address the network design issue of M2M communications for a home energy management system (HEMS) in the smart grid. The network architecture for HEMS to collect status and power consumption demand from home appliances is introduced. Then the optimal HEMS traffic concentration is presented and formulated as the optimal cluster formation. A dynamic programming algorithm is applied to obtain the optimal solution. The numerical results show that the proposed optimal traffic concentration can minimize the cost of HEMS.
Keywords
domestic appliances; dynamic programming; energy management systems; next generation networks; power consumption; power engineering computing; smart power grids; cutting edge technology; dynamic programming; home appliances; home energy management system; machine-to-machine communications; network architecture; network design issue; next-generation communications; optimal HEMS traffic concentration; optimal cluster formation; power consumption demand; smart grid; Ad hoc networks; Base stations; Home appliances; Machine learning; Power demand; Smart grids; Wide area networks; Wireless communication;
fLanguage
English
Journal_Title
Communications Magazine, IEEE
Publisher
ieee
ISSN
0163-6804
Type
jour
DOI
10.1109/MCOM.2011.5741146
Filename
5741146
Link To Document