Web search companies distribute their infrastructures and operations across several, geographically distant data centers. This distributed architecture facilitates high performance query processing, which is fundamental for the success of a Web search engine. At the same time, data centers require an huge amount of electricity to operate their computing resources. In this extended abstract, we briefly discuss our recent works for improving the energy effciency of query processing systems. Firstly, we introduce a novel query forwarding algorithm which exploits green energy sources to reduce the electricity expenditure and carbon footprint of Web search engines. Then, we propose to delegate the CPU power management from a server' operative system directly to the query processing application, to reduce the energy consumption of a search engine's servers. Finally, we introduce PESOS, a scheduling algorithm which manages the CPU power consumption on a per-query basis while considering query latency constraints.

Recent advances in energy efficient query processing

Catena M;Tonellotto N
2017

Abstract

Web search companies distribute their infrastructures and operations across several, geographically distant data centers. This distributed architecture facilitates high performance query processing, which is fundamental for the success of a Web search engine. At the same time, data centers require an huge amount of electricity to operate their computing resources. In this extended abstract, we briefly discuss our recent works for improving the energy effciency of query processing systems. Firstly, we introduce a novel query forwarding algorithm which exploits green energy sources to reduce the electricity expenditure and carbon footprint of Web search engines. Then, we propose to delegate the CPU power management from a server' operative system directly to the query processing application, to reduce the energy consumption of a search engine's servers. Finally, we introduce PESOS, a scheduling algorithm which manages the CPU power consumption on a per-query basis while considering query latency constraints.
2017
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Information retrieval
Energy efficiency
File in questo prodotto:
File Dimensione Formato  
prod_385573-doc_132927.pdf

accesso aperto

Descrizione: Recent advances in energy efficient query processing
Tipologia: Versione Editoriale (PDF)
Dimensione 115.41 kB
Formato Adobe PDF
115.41 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/348937
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact