Alex Mavromatis

TL;DR: An SDN based network planning framework utilizing machine-learning techniques and a network-scale monitoring database is implemented over an optical field-trial testbed comprised of 436.4km fibre to demonstrate the spectral efficiency utilising probabilistic-shaping BVT based on link performance prediction.

TL;DR: This framework can dynamically provision the IoT devices to enable machine-to-machine (M2M) communication as well as continuous operational fault detection for WSNs and reduces control operations time up to 27, posing a powerful feature for use cases with time-critical control requirements.

TL;DR: The proposed decentralised guard time adaptation can reduce the energy consumption by up to 40%, without compromising network reliability, in the TSCH network in single hop topology and multi-hop network.

TL;DR: Investigation of the effect of the guard time duration on energy consumption and performance evaluation results show that an efficient configuration of guard time may reduce energy consumption by up to 30%, without compromising network reliability.

TL;DR: A novel architecture and implementation based on Software Defined Networking (SDN) principles is presented aiming to solve scalability issues within large IoT deployments, capable of reducing the latency, improving reliability and the User Experience (UX) within the IoT infrastructure.