Eagle: Vulnerability and Congestion Aware Software Update Synthesis in Softwarized Networks with a 5G Network Case Study

Effective scheduling of software updates is a significant challenge in network operations and management, particularly when considering specific performance and security requirements. This paper focuses on the synthesis of such software updates in the context of emerging virtualized and softwarized networks, such as 5G network infrastructures, with the objective of ensuring vulnerability avoidance and congestion freedom at any time during the updates. We formalize the update synthesis problem and propose an algorithmic solution, called Eagle, that exploits formal methods and mixed integer linear programming, to achieve optimal solutions. We then complement it with a greedy algorithm to support faster computation. We exemplify our framework considering an implementation of a 5G architecture, as the one described in the ETSI 5123 standard, and which relies on kubernetes. Finally, we evaluate our approach through a large range of realistic ISP topologies from the Topology Zoo dataset, and we also perform extensive experiments on our kubernetes cluster, where we execute the software update sequences generated by our tool. This allows us to discuss the scalability of our approach along with its practical applicability.