A Survey on Machine Learning Software-Defined Wireless Sensor Networks (ML-SDWSNs): Current Status and Major Challenges

Wireless Sensor Network (WSN), which are enablers of the Internet Things (IoT) technology, typically used en-masse in widely physically distributed applications to monitor dynamic conditions environment. They collect raw sensor data that is processed centralised. With current traditional techniques state-of-art WSN programmed for specific tasks, it hard react any change environment beyond scope intended task. To solve this problem, a synergy between Software-Defined Networking (SDN) and has been proposed. This paper aims present status (SDWSN) proposals introduce readers emerging research topic combines Machine Learning (ML) SDWSN concepts, also called ML-SDWSNs. ML-SDWSN grants an intelligent, centralised resource-aware architecture achieve improved network performance challenges currently found practical implementation SDWSNs. survey provides helpful information insights scientific industrial communities, professional organisations interested SDWSN, mainly state-of-art, ML techniques, open issues.