Discovery of Flow Splitting Ratios in ISP Networks with Measurement Noise

Network telemetry and analytics is essential for providing highly dependable services in modern computer networks. In particular, network flow analytics for ISP networks allows operators to inspect and reason about traffic patterns in their networks in order to react to anomalies. High performance network analytics systems are designed with scalability in mind, and can consequently only observe partial information about the network traffic. Still, they need to provide a holistic view of the traffic, including the distribution of different traffic flows on each link. It is impractical to monitor such fine-grained telemetry, and in large, heterogeneous networks it is often too complex and error-prone, if not impossible, to access and maintain all technical specifications and router-specific configurations needed to determine e.g. the load balancing weights used when traffic is split onto multiple paths. The ratios by which flows are split on the possible paths must be derived indirectly from the measured flow demands and link utilizations. Motivated by a case study provided by a major European ISP, we suggest an efficient method to estimate the flow splitting ratios. Our approach, based on quadratic linear programming, is scalable and robust to the measurement noise found in a typical network analytics deployment. Finally, we implement an automated tool for estimating the flow splitting ratios and document its applicability on real data from the ISP

AllSynth: A BDD-Based Approach for Network Update Synthesis

The increasingly stringent dependability requirements on communication networks as well as the need to render these networks more adaptive to improve performance, demand for more automated approaches to operate networks. We present AllSynth, a symbolic synthesis tool for updating communication networks in a provably correct and efficient manner. AllSynth automatically synthesizes network update schedules which transiently ensure a wide range of policy properties expressed using linear temporal logic (LTL). In particular, in contrast to existing approaches, AllSynth symbolically computes and compactly represents all feasible and cost-optimal solutions. At its heart, AllSynth relies on a novel parameterized use of binary decision diagrams (BDDs) which greatly improves performance. Indeed, AllSynth not only provides formal correctness guarantees and outperforms existing state-of-the-art tools in terms of generality, but also in terms of runtime as documented by experiments on a benchmark of real-world network topologies

Polynomial Time Decidability of Weighted Synchronization under Partial Observability

We consider weighted automata with both positive and negative integer weights on edges and study the problem of synchronization using adaptive strategies that may only observe whether the current weight-level is negative or nonnegative. We show that the synchronization problem is decidable in polynomial time for deterministic weighted automata