Energy-price-driven query processing in multi-center web search engines
buir.contributor.author | Aykanat, Cevdet | |
dc.citation.epage | 992 | en_US |
dc.citation.spage | 983 | en_US |
dc.contributor.author | Kayaaslan, Enver | en_US |
dc.contributor.author | Cambazoglu, B. B. | en_US |
dc.contributor.author | Blanco, R. | en_US |
dc.contributor.author | Junqueira, F. P. | en_US |
dc.contributor.author | Aykanat, Cevdet | en_US |
dc.coverage.spatial | Beijing, China | |
dc.date.accessioned | 2016-02-08T12:18:38Z | |
dc.date.available | 2016-02-08T12:18:38Z | |
dc.date.issued | 2011-07 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description | Date of Conference: 24-28 July, 2011 | |
dc.description | Conference name: SIGIR '11 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval | |
dc.description.abstract | Concurrently processing thousands of web queries, each with a response time under a fraction of a second, necessitates maintaining and operating massive data centers. For large-scale web search engines, this translates into high energy consumption and a huge electric bill. This work takes the challenge to reduce the electric bill of commercial web search engines operating on data centers that are geographically far apart. Based on the observation that energy prices and query workloads show high spatio-temporal variation, we propose a technique that dynamically shifts the query workload of a search engine between its data centers to reduce the electric bill. Experiments on real-life query workloads obtained from a commercial search engine show that significant financial savings can be achieved by this technique. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T12:18:38Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2011 | en |
dc.identifier.doi | 10.1145/2009916.2010047 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/28367 | en_US |
dc.language.iso | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | https://doi.org/10.1145/2009916.2010047 | en_US |
dc.source.title | SIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval | en_US |
dc.subject | Data center | en_US |
dc.subject | Energy | en_US |
dc.subject | Query processing | en_US |
dc.subject | Web search engine | en_US |
dc.subject | Electric bills | en_US |
dc.subject | Energy prices | en_US |
dc.subject | Financial savings | en_US |
dc.subject | High energy consumption | en_US |
dc.subject | ITS data | en_US |
dc.subject | Massive data | en_US |
dc.subject | Spatio-temporal variation | en_US |
dc.subject | Energy utilization | en_US |
dc.subject | Information retrieval | en_US |
dc.subject | Satellite communication systems | en_US |
dc.subject | Search engines | en_US |
dc.subject | User interfaces | en_US |
dc.subject | World Wide Web | en_US |
dc.title | Energy-price-driven query processing in multi-center web search engines | en_US |
dc.type | Conference Paper | en_US |
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