Energy consumption of the Internet is already substantial and it is likely to increase as operators deploy faster equipment to handle popular bandwidthintensive services, such as streaming and video-on-demand. Existing work on energy saving considers local adaptation relying primarily on hardwarebased techniques, such as sleeping and rate adaptation. We argue that a complete solution requires a network-wide approach that works in conjunction with local measures. However, traditional traffic engineering objectives do not include energy. This paper presents Energy-Aware Traffic engineering (EATe), a technique that takes energy consumption into account while achieving the same traffic rates as the energy-oblivious approaches. EATe uses a scalable, online technique to spread the load among multiple paths so as to increase energy savings. Our extensive ns-2 simulations over realistic topologies show that EATe succeeds in moving 21% of the links to the sleep state, while keeping the same sending rates and being close to the optimal energy-aware solution. Further, we demonstrate that EATe successfully handles changes in traffic load and quickly restores a low overall energy state. Alternatively, EATe can move links to lower energy levels, resulting in energy savings of 8%. Finally, EATe can succeed in making 16% of active routers sleep.
In Energy-Aware Traffic Engineering (EATe) REF , the edge routers run a complex TE component that tries to aggregate traffic over predetermined routing paths.
Energy-aware traffic engineering
e-Energy
Engineering Computer Science