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 largescale 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.
Kayaaslan et al. REF investigated the possibility of dynamically shifting the query workload between data centers in order to minimize total energy cost incurred by the search engine.
Energy-price-driven query processing in multi-center web search engines
SIGIR '11
Computer Science