Energy-Efficient Computing Using Agent-Based Multi-Objective Dynamic Optimization
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 paper.