Advanced Resource Management for Next Generation Networks

Abstract

With the booming deployment of Internet of Things (IoT) -exceeding 22 billion by the end of 2021-, the connectivity and management of IoT devices seem as a titanic task. By leveraging emerging concepts like network function virtualization, slicing, and fog/edge computing, Zero Touch Networks (ZTN) are expected to provide a wide range of autonomous services, infrastructure and functionalities that involve closed-loop life cycle operations, called self-X (e.g., self-configuration, self-optimization, and self-healing). ZTN management targets fully automating operational tasks without human intervention. Specifically, cost-effective resource allocation and service provisioning tasks in next generation networks require novel proactive and intelligent approaches. In this context, we propose to leverage innovative approaches to dynamically optimize network operations and adapt to environmental changes. To do so, we illustrate in this presentation two networking scenarios. In the first scenario, automated market-driven resources allocation in multi-domain cloud networks is proposed to support the resources’ buying/selling operations. In the second scenario, we aim to optimize the flying trajectories of a swarm of unmanned aerial vehicles (UAVs), a.k.a. drones, to timely collect data from IoT devices. Both examples demonstrate the significant contribution into achieving self-X of future ZTN.