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On the Energy Efficiency of Sleeping and Rate Adaptation for Network Devices

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Algorithms and Architectures for Parallel Processing (ICA3PP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10393))

Abstract

The ever-growing appetite of Internet applications for network resources has led to an unprecedented electricity bill for these telecommunication infrastructures. Several techniques have been developed to improve the energy consumption of network devices. As their utilization highly varies over time, the two main techniques for saving energy, namely sleeping and rate adaptation, exploits the lower workload periods to either put to sleep some hardware elements or adapt the network rate to the actual traffic level. In this paper, we compare two emblematic approaches of these energy-efficient techniques: Low Power Idle and Adaptive Link Rate. Our simulation-based study quantifies the reachable energy savings of these two approaches depending on the traffic characteristics. We show that, with little impact on the Quality of Service and consequent energy savings, Low Power Idle has a clear advantage. On the contrary, ALR is almost always consuming more than LPI and can reach unacceptable QoS levels. We also show that they can be combined to achieve better energy-efficiency, but at the cost of important QoS degradation.

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Acknowledgments

Experiments presented in this paper were carried out using the Grid’5000 experimental test-bed, being developed under the Inria ALADDIN development action with support from CNRS, RENATER and several Universities as well as other funding bodies (see https://www.grid5000.fr).

The authors would like to thank the reviewers for their valuable comments.

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Correspondence to Anne-Cécile Orgerie .

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Haudebourg, T., Orgerie, AC. (2017). On the Energy Efficiency of Sleeping and Rate Adaptation for Network Devices. In: Ibrahim, S., Choo, KK., Yan, Z., Pedrycz, W. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2017. Lecture Notes in Computer Science(), vol 10393. Springer, Cham. https://doi.org/10.1007/978-3-319-65482-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-65482-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65481-2

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