Energy-Efficient Computing Using Agent-Based Multi-objective Dynamic Optimization View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Alexandru-Adrian Tantar , Grégoire Danoy , Pascal Bouvry , Samee U. Khan

ABSTRACT

Nowadays distributed systems face a new challenge, almost nonexistent a decade ago: energy-efficient computing. Due to the rising environmental and economical concerns and with trends driving operational costs beyond the acquisition ones, green computing is of more actuality than never before. The aspects to deal with, e.g. dynamic systems, stochastic models or time-dependent factors, call nonetheless for paradigms combining the expertise of multiple research areas. An agent-based dynamic multi-objective evolutionary algorithm relying on simulation and anticipation mechanisms is presented in this chapter. A first aim consists in addressing several difficult energy-efficiency optimization issues, in a second phase, different open questions being outlined for future research. More... »

PAGES

267-287

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-22179-8_14

DOI

http://dx.doi.org/10.1007/978-3-642-22179-8_14

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009308736


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