Performance Evaluation of an Energy Efficient Virtual Network Mapping Method - In the case of load-dependent power consumption model -
Proceeding: The International Conference on Electronics and Software Science (ICESS2015)Publication Date: 2015-07-20
Authors : Hiromichi Sugiyama; Yukinobu Fukushima; Tokumi Yokohira;
Page : 134-144
Keywords : Virtual network; Virtual network mapping problem; Energy efficiency; load-dependent power consumption model; heuristic algorithm;
Abstract
This paper tackles an energy efficient virtual network mapping problem where virtual nodes and links in a given virtual network have to be assigned (mapped) to physical nodes and paths in the physical network so that the total power consumption associated with the mapping is minimized. Under a load-independent power consumption model where power consumption of a physical node is constant regardless of it load, the conventional mapping method successfully reduces the total power consumption by preferentially assigning virtual nodes and links to the active (used) physical nodes and the paths passing the active physical nodes. However, another load-dependent power consumption model will be dominant in the near future, and the conventional method may not reduce the total power consumption because the active-node-first policy can cause large additional power consumption under the new model. In this paper, we try to minimize the total power consumption under the the load-dependent power consumption model. In order to achieve this, we modify the conventional method so that it adopts the minimum additional power consumption first policy. The modified method calculates the actual additional power consumption associated with node and link mapping, and preferentially assigns virtual nodes and links to physical nodes and paths so that the actual additional power consumption is minimized. Simulation results clarify that the modified method can '13','40',% lower total power consumption than the conventional method under the load-dependent power consumption model.
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Last modified: 2015-07-26 22:34:20