4.7 Article

An energy-efficient SDN based sleep scheduling algorithm for WSNs

Journal

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
Volume 59, Issue -, Pages 39-45

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jnca.2015.05.002

Keywords

Energy efficiency; WSNs; Sleep scheduling; SDN-ECCKN; EC-CKN

Funding

  1. Pearl River S&T Nova Program of Guangzhou [2014J2200023]
  2. Natural Science Foundation of Guangdong Province [2014A030313685]
  3. Guangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis [GDUPTKLAB201304]
  4. Shenzhen City Knowledge Innovation Program Project [JCYJ20140417113430604]
  5. Open Project Foundation of Information Technology Research Base of Civil Aviation Administration of China [CAAC-ITRB-201406]
  6. Foshan Science and Technology Project [2014HK100103]
  7. National Natural Science Foundation of China [61401107]
  8. Special Fund of Guangdong Higher School Talent Recruitment
  9. Educational Commission of Guangdong Province, China [2013KJCX0131]
  10. special funds of Guangdong high-tech development project [2013B010401035]
  11. Guangdong University of Petrochemical Technology [2012RC0106]

Ask authors/readers for more resources

Energy efficiency in Wireless Sensor Networks (WSNs) has always been a hot issue and has been studied for many years. Sleep Scheduling (SS) mechanism is an efficient method to manage energy of each node and is capable to prolong the lifetime of the entire network. In this paper a Software-defined Network (SDN) based Sleep Scheduling algorithm SDN-ECCKN is proposed to manage the energy of the network. EC-CKN is adopted as the fundamental algorithm when implementing our algorithm. In the proposed SDN-ECCKN algorithm, every computation is completed in the controller rather than the sensors themselves and there is no broadcasting between each two nodes, which are the main features of the traditional EC-CKN technique. The results of our SDN-ECCKN show its advantages in energy management, such as network lifetime, the number of live nodes and the number of solo nodes in the network. (C) 2015 Elsevier Ltd. All rights reserved.

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