Efficient energy management in distributed web search

Catena M., Frieder O., Tonellotto N.

Web search engines  PESOS  energy efficiency  distributed search  Information retrieval  energy consumption 

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.

Source: 27th ACM International Conference on Information and Knowledge Management, pp. 1555–1558, Torino, Italia, 22-26/10/2018

Publisher: ACM - Association for Computing Machinery, New York, USA

Metrics