Abstract—As the Internet infrastructure grows to support a variety of services, its legacy protocols are being overloaded with new functions such as traffic engineering. Today, operators engineer such capabilities through clever, but manual parameter tuning. In this paper, we propose a back-end support tool for large-scale parameter configuration that is based on efficient parameter state space search techniques and on-line simulation. The framework is useful when the network protocol performance is sensitive to its parameter settings, and its performance can be reasonably modeled in simulation. In particular, our system imports the network topology, relevant protocol models and latest monitored traffic patterns into a simulation that runs on-line in a network operations center (NOC). Each simulation evaluates the network performance for a particular setting of protocol parameters. We propose an efficient large-dimensional parameter state space search technique called “recursive random search (RRS).” Each sample point chosen by RRS results in a single simulation. An important feature of this framework is its flexibility: it allows arbitrary choices in terms of the simulation engines used (e.g., ns-2, SSFnet), network protocols to be simulated (e.g., OSPF, BGP), and in the specification of the optimization objectives. We demonstrate the flexibility and relevance of this framework in three scenarios: joint tuning of the RED buffer management parameters at multiple bottlenecks, traffic engineering using OSPF link weight tuning, and outbound load-balancing of traffic at peering/transit points using BGP LOCAL_PREF parameter. Index Terms—Black-box optimization, network performance management, network protocol configuration, on-line simulation
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