Adaptive Telemetry for Software-Defined Mobile Networks

Abstract

The forthcoming set of 5G standards will bring programmability and flexibility to levels never seen before. This has required introducing changes in the architecture of mobile networks, enabling different features such as the split of control and data planes, as required to support the rapid programming of heterogeneous data planes. Software Defined Networking (SDN) has emerged as a basic toolset for operators to manage their infrastructure, as it opens up the possibility of running a multitude of intelligent and advanced applications for network optimization purposes in a centralized network controller. However, the very basic nature that makes possible this efficient management and operation in a flexible way—the logical centralization—poses important challenges due to the lack of proper monitoring tools, suited for SDN-based architectures. In order to take timely and right decisions while operating a network, centralized intelligence applications need to be fed with a continuous stream of up-to-date network statistics. However, this is not feasible with current SDN solutions due to scalability and accuracy issues. This article first analyzes the monitoring issues in current SDN solutions and then proposes a telemetry framework for software defined mobile networks capable of adapting to the various 5G services. Finally, it presents an experimental validation that shows the benefits of the proposed solution at alleviating the load on the control and data planes, improving the reactiveness to network events, and providing better accuracy for network measurements.