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Published October 24, 2018 | Version v1
Conference paper Open

Efficient Energy Management in Distributed Web Search

  • 1. CNR
  • 2. Georgetown University Washington

Description

Distributed Web search engines (WSEs) require warehouse-scale computers to deal with the ever-increasing size of the Web and the large amount of user queries they daily receive. The energy consumption of this infrastructure has a major impact on the economic profitability of WSEs. Recently several approaches to reduce the energy consumption of WSEs have been proposed. Such solutions leverage dynamic voltage and frequency scaling techniques in modern CPUs to adapt the WSEs’ query processing to the incoming query traffic without negative impacts on latencies.
A state-of-the-art research approach is the PESOS (Predictive Energy Saving Online Scheduling) algorithm, which can reduce
the energy consumption of a WSE’ single server by up to 50%. We evaluate PESOS on a simulated distributed WSE composed of
a thousand of servers, and we compare its performance w.r.t. an industry-level baseline, called PEGASUS. Our results show that
PESOS can reduce the CPU energy consumption of a distributed WSE by up to 18% with respect to PEGASUS, while providing query response times which are in line with user expectations.

Files

Efficient energy management in distributed web search.pdf

Files (1.7 MB)

Additional details

Funding

BigDataGrapes – Big Data to Enable Global Disruption of the Grapevine-powered Industries 780751
European Commission