A recursive random search algorithm for large-scale network parameter configuration

  • Authors:

  • Tao Ye;Shivkumar Kalyanaraman

  • Affiliations:

  • Rensselaer Polytechnic Institute, Troy, New York;Rensselaer Polytechnic Institute, Troy, New York

  • Venue:
  • SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
  • Year:
  • 2003

Quantified Score

Hi-index 0.00

Visualization

Abstract

Parameter configuration is a common procedure used in large-scale network protocols to support multiple operational goals. It can be formulated as a black-box optimization problem and solved with an efficient search algorithm. This paper proposes a new heuristic search algorithm, Recursive Random Search(RRS), for large-scale network parameter optimization. The RRS algorithm is based on the initial high-efficiency feature of random sampling and it attempts to maintain this high efficiency by constantly "restarting" random sampling with adjusted sample spaces. Besides the high efficiency, the RRS algorithm is robust to the effect of random noise and trivial parameters in the objective function because of its root in random sampling. These features are very important for the efficient optimization of network protocol configuration. The performance of RRS is demonstrated with the tests on a suite of benchmark functions. The algorithm has been applied to the configuration of several network protocols, such as RED, OSPF and BGP. One example application in OSPF routing algorithm is presented.