Approximate parallel simulation of web search engines

Abstract

Large scale Web search engines are complex and highly optimized systems devised to operate on dedicated clusters of processors. Any, even a small, gain in performance is beneficial to economical operation given the large amount of hardware resources deployed in the respective data centers. Performance is fully dependent on users behavior which is featured by unpredictable and drastic variations in trending topics and arrival rate intensity. In this context, discrete-event simulation is a powerful tool either to predict performance of new optimizations introduced in search engine components or to evaluate different scenarios under which alternative component configurations are able to process demanding workloads. These simulators must be fast, memory efficient and parallel to cope with the execution of millions of events in small running time on few processors. In this paper we propose achieving this objective at the expense of performing approximate parallel simulation.