Date Added: Mar 2010
Online configuration of large-scale systems such as networks requires parameter optimization to be done within a limited amount of time. This time limit is even more pressing when configuration is needed as a recovery response to a failure in the system. To quickly configure such systems in an online manner, the authors propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. Essentially, PTAS applies a search algorithm to find out how to best distribute available experiment budget among multiple optimization search algorithms. Specifically, PTAS allocates experiment budget to each available search algorithm and observes each algorithm's performance on the system-at-hand.