
doi: 10.1109/mcse.2017.8
A simulation methodology is proposed to evaluate the performance of large-scale Web search engines hosted by datacenters. The salient features of the methodology are the use of models of parallel computing to overcome the complexities associated with the simulation of hardware and system software details; a circulating tokens approach to represent sequences of operations that compete for search engine resources; benchmark programs to measure the cost of relevant operations; and simulations driven by real user traces to consider the dynamics of user behavior. An experimental evaluation of the methodology, which ranges from clusters of processors to single multithreaded processors, shows that it can generate respective simulation programs capable of predicting performance in a precise and efficient manner.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 11 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
