Network Tomography for Efficient Monitoring in SDN-Enabled 5G Networks and Beyond: Challenges and Opportunities

Abstract

Efficient monitoring plays a vital role in software-defined networking (SDN)-enabled 5G networks, involving the monitoring of performance metrics for both physical and virtual networks and considering the requirements of a variety of traffic types originating from different applications. However, conventional network monitoring tools based on traditional IP-based mechanisms may not be able to keep up with the dynamic nature of 5G networks. Network tomography (NT) is an emerging monitoring approach that estimates network performance based on measurements realized at a limited subset of network elements, presenting benefits over traditional monitoring techniques, but susceptible to identifiability issues. In this article, we demonstrate how NT can respond to current monitoring challenges, complementing and working together with SDN, yielding accurate estimations with low overhead, while exploiting SDN capabilities such as the centralized view of the entire network, direct flow-level measurements, and controllable routing. Furthermore, we present the spectrum of applications of NT-based solutions in 5G networks and beyond, ranging from virtual to vehicular networks.