The paper presents an approach aimed to reduce the overall power consumption of a backbone network by exploiting the power behavior of green network devices. This approach is based on the solution of an optimization problem that has a Mixed Integer NonLinear Programming (MINLP) formulation. Given that the problem is NP-hard, exact methods for finding optimal solutions can be used only for scenarios of limited size. To cope with the case of complex networks, the paper proposes two variations of the Fast Greedy Heuristic (FGH), denoted as Time Limited PAR Heuristic (TLPH) and PAR Meta Heuristic (PMH). The simulation study highlights the capability of the proposed heuristics to obtain solutions near the optimum and to outperform the other approaches in terms of power savings and CPU times needed to find a solution in complex network scenarios.
Energy saving heuristics in Backbone Networks
GARROPPO, ROSARIO GIUSEPPE;GIORDANO, STEFANO;NENCIONI, GIANFRANCO;PAGANO, MICHELE;SCUTELLA', MARIA GRAZIA
2012-01-01
Abstract
The paper presents an approach aimed to reduce the overall power consumption of a backbone network by exploiting the power behavior of green network devices. This approach is based on the solution of an optimization problem that has a Mixed Integer NonLinear Programming (MINLP) formulation. Given that the problem is NP-hard, exact methods for finding optimal solutions can be used only for scenarios of limited size. To cope with the case of complex networks, the paper proposes two variations of the Fast Greedy Heuristic (FGH), denoted as Time Limited PAR Heuristic (TLPH) and PAR Meta Heuristic (PMH). The simulation study highlights the capability of the proposed heuristics to obtain solutions near the optimum and to outperform the other approaches in terms of power savings and CPU times needed to find a solution in complex network scenarios.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.