Description: Resilient networks have the ability to provide the desired level of service, despite challenges such as malicious attacks and misconﬁgurations. The primary goal of this dissertation is to be able to provide uninterrupted network services in the face of an attack or any failures. This dissertation attempts to apply control system theory techniques with a focus on system identiﬁcation and closed-loop feedback control. It explores the benefits of system identification technique in designing and validating the model for the complex and dynamic networks. Further, this dissertation focuses on designing robust feedback control mechanisms that are both scalable and eﬀective in real-time. It focuses on employing dynamic and predictive control approaches to reduce the impact of an attack on network services. The closed-loop feedback control mechanisms tackle this issue by degrading the network services gracefully to an acceptable level and then stabilizing the network in real-time (less than 50 seconds). Employing these feedback mechanisms also provide the ability to automatically conﬁgure the settings such that the QoS metrics of the network is consistent with those speciﬁed in the service level agreements.
Date: December 2018
Creator: Vempati, Jagannadh Ambareesh
Partner: UNT Libraries