Network Configuration and Management via Two-Phase Online Optimization
Automated configuration and management of highly dynamic networks is a challenging problem for network practitioners. Such online optimization of systems can be performed in two ways: using a separate model of the system for experimenting new configurations and using the system itself for experimentation without a separate system model. The former approach fails for dynamic networks with high failure rates or variable demand profile. In this paper, the authors take the latter approach and perform in-situ trials in a network to find better configurations of IGP link weights giving result to higher network throughput. Their approach follows a two-phase model where the online optimization process periodically goes into a "Search" phase followed by network operation with the parameters found in the latest search phase.