Energy-efficient Query Processing in Web Search Engines - 2017 PROJECT TITLE : Energy-efficient Query Processing in Web Search Engines - 2017 ABSTRACT: Web search engines are composed by thousands of question processing nodes, i.e., servers dedicated to process user queries. Such several servers consume a important amount of energy, largely accountable to their CPUs, however they are necessary to ensure low latencies, since users expect sub-second response times (e.g., five hundred ms). However, users will hardly notice response times that are faster than their expectations. Hence, we have a tendency to propose the Predictive Energy Saving Online Scheduling Algorithm (\sfPESOS ) to pick out the most appropriate CPU frequency to method a question on a per-core basis. \sfPESOS aims at method queries by their deadlines, and leverage high-level scheduling info to scale back the CPU energy consumption of a question processing node. \sfPESOS bases its decision on query potency predictors, estimating the processing volume and processing time of a question. We experimentally evaluate \sfPESOS upon the TREC ClueWeb09B assortment and therefore the MSN2006 question log. Results show that \sfPESOS can reduce the CPU energy consumption of a question processing node up to \sim 48 p.c compared to a system running at maximum CPU core frequency. \sfPESOS outperforms conjointly the simplest state-of-the-art competitor with a \sim 20 p.c energy saving, whereas the competitor requires a fine parameter tuning and it could incurs in uncontrollable latency violations. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Genetic Improvement of Software: a Comprehensive Survey - 2017 Mining the Most Influential k-Location Set From Massive Trajectories - 2017