Wireless Sensor and Actor Networks (WSANs) is becoming an important part of our technological reality as an autonomous systems, due to the advances of new technologies, such as 5G, Internet of Things (IoT) and ArtificialIntelligence (AI). One of the main challenges in autonomous systems is power management. Self-healing is a key feature of WSAN, which improves network connectivity and lifetime, by assigning actors tasks such as to connect separated network components, or recharge the sensors whose battery power is exhausted. In this paper, we propose a framework for actor selection in WSAN, which consists mainly of an adaptive neuro-fuzzy inference system. It considers network conditions when selecting actors for different tasks regarding network's connectivity restoration.
['Elis Kulla', 'Donald Elmazi', 'Leonard Barolli']
Neuro-Adaptive Learning Fuzzy-Based System for Actor Selection inWireless Sensor and Actor Networks