Name
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2009916.2010047 | SIGIR |
Keywords | Field | DocType |
massive data center,large-scale web search engine,multi-center web search engine,query workloads,energy-price-driven query processing,data center,commercial web search engine,electric bill,huge electric bill,search engine,commercial search engine show,query workload,web search engine,energy | Web search engine,Web search query,Metasearch engine,Search engine,Query expansion,Information retrieval,Computer science,Sargable,Search-oriented architecture,Search analytics,Database | Conference |
Citations | PageRank | References |
23 | 1.09 | 18 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Enver Kayaaslan | 1 | 83 | 7.38 |
| B. Barla Cambazoglu | 2 | 735 | 38.87 |
| Roi Blanco | 3 | 872 | 57.42 |
| Flavio P. Junqueira | 4 | 1037 | 49.96 |
| Cevdet Aykanat | 5 | 996 | 84.08 |