Software Defined Wireless Sensor Network (SDWSN) is realised by infusing Software Defined Network (SDN) model in Wireless Sensor Network (WSN), Reason for that is to overcome the challenges of WSN. Artificial Intelligence (AI) and machine learning play an important role in our society, give rise to systems that can manage themselves. WSNs have been used in various industrial applications, where reliability and network performance are critical success factors. Many advanced AI techniques can be utilised to improve the performance and reliability of these applications. Investigating the AI algorithms applied to SDN may bring improved network management, security or routing in SDWSN which may result in a more reliable network. We look at machine learning algorithms applied in SDN and discuss the possibility of using these AI in SDWSN to address the WSN challenges and improve its performance and reliability.
Reference:
Matlou, O.G. and Abu-Mahfouz, A.M.I. 2017. Utilising artificial intelligence in software defined wireless sensor network. The 43rd Annual Conference of the IEEE on Industrial Electronics Society, IECON 2017, 29 October to 1 November 2017, Beijing, China
Matlou, O., & Abu-Mahfouz, A. M. (2017). Utilising artificial intelligence in software defined wireless sensor network. IEEE. http://hdl.handle.net/10204/10115
Matlou, OG, and Adnan MI Abu-Mahfouz. "Utilising artificial intelligence in software defined wireless sensor network." (2017): http://hdl.handle.net/10204/10115
Matlou O, Abu-Mahfouz AM, Utilising artificial intelligence in software defined wireless sensor network; IEEE; 2017. http://hdl.handle.net/10204/10115 .
Copyright: 2017 IEEE. Due to copyright restrictions, the attached PDF file contains the accepted version of the published paper. For access to the published version, please consult the publisher's website.