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@article{145730,
        author = {K M SANTHOSH REDDY and Dr M.Padmavathamma and P. SWATHI},
        title = {Energy-efficient Query Processing  in Web Search Engines},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {11},
        pages = {244-246},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145730},
        abstract = {Web search engines are composed by thousands of query processing nodes, i.e., servers dedicated to process user queries.Such many servers consume a significant amount of energy, mostly accountable to their CPUs, but they are necessary to ensure lowlatencies, since users expect sub-second response times. However, users can hardly notice response times that are fasterthan their expectations. Hence, we propose the Predictive Energy Saving Online Scheduling Algorithm (PESOS) to select the mostappropriate CPU frequency to process a query on a per-core basis. PESOS aims at process queries by their deadlines, and leveragehigh-level scheduling information to reduce the CPU energy consumption of a query processing node. PESOS bases its decision onquery efficiency predictors, estimating the processing volume and processing time of a query. We experimentally evaluate PESOS uponthe TREC ClueWeb09B collection and the MSN2006 query log. Results show that PESOS can reduce the CPU energy consumptionof a query processing node up to _48% compared to a system running at maximum CPU core frequency. PESOS outperforms alsothe best state-of-the-art competitor with a _20% energy saving, while the competitor requires a fine parameter tuning and it mayincurs in uncontrollable latency violations.},
        keywords = {},
        month = {},
        }