Energy-efficient Query Processing in Web Search Engines
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 low latencies, since users expect sub-second response times . However, users can hardly notice response times that are faster than their expectations. Hence, we propose the Predictive Energy Saving Online Scheduling Algorithm (PESOS ) to select the most appropriate CPU frequency to process a query on a per-core basis. PESOS aims at process queries by their deadlines, and leverage high-level scheduling information to reduce the CPU energy consumption of a query processing node.
Web mining technique involved
- Specific query is given and search through Google API for mining we pages
- Get relevant query results from web mining
- Energy efficient query processing is handled to reduce energy consumption and query latency