IntOpt: In-Band Network Telemetry Optimization for NFV Service Chain Monitoring
Deval Bhamare, Andreas Kassler, Jonathan Vestin, Mohammad Ali Khoshkholghi, Javid Taheri · 2019
Managing and scaling virtual network function (VNF) service chains require the collection and analysis of network statistics and states in real time. Existing network function virtualization (NFV) monitoring frameworks either do not have the capabilities to express the range of telemetry items needed to perform management or do not scale to large traffic volumes and rates. We present IntOpt, a scalable and expressive telemetry system designed for flexible VNF service chain network monitoring using active probing. IntOpt allows to specify monitoring requirements for individual service chain, which are mapped to telemetry item collection jobs that fetch the required telemetry items from P4 (programming protocol-independent packet processors) programmable dataplane elements. In our approach, the SDN controller creates the minimal number of monitoring flows to monitor the deployed service chains as per their telemetry demands in the network. We propose a simulated annealing based random greedy metaheuristic (SARG) to minimize the overhead due to active probing and collection of telemetry items. Using P4-FPGA, we benchmark the overhead for telemetry collection and compare our simulated annealing based approach with a naïve approach while optimally deploying telemetry collection probes. Our numerical evaluation shows that the proposed approach can reduce the monitoring overhead by 39% and the total delays by 57%. Such optimization may as well enable existing expressive monitoring frameworks to scale for larger real-time networks.