A frequency adjustment architecture for energy efficient router

Fu, Wenliang; Song, Tian

doi:10.1145/2377677.2377704

Cited by 7 publications

(6 citation statements)

References 3 publications

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“…In this section, we compare the performance of the proposed approach with the existing static approach [6] [7] which makes the EAS selection decision based on the observed average traffic load of previous time-slot. The traffic load is quantized into six levels according to the packet processing capacity of the frequency scaled router under different EASs, and the traffic state can be R 1 (if the average packet arrival rate in one time-slot, r p (t), is zero), R 2 (if r p (t) < 6784000pps), R 3 (when 6784000pps ≤ r p (t) < 8106667pps), R 4 (when 8106667pps ≤ r p (t) < 10176000pps), R 5 (when 10176000pps ≤ r p (t) < 13589333pps), R 6 (if r p (t) ≥ The x-axis shows the packet arrival rate in (×10 6 pps), whereas the y-axis shows the power consumption in Watts.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Energy saving local control policy for Green Reconfigurable Routers

Wei

Wang

Feng

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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Energy efficiency is now a significant concern for network infrastructure and next-generation network devices are expected to embed advanced power management capabilities. However, the effective exploitation of advanced power management capabilities in network devices which adaptively meet network load and operational constraints is still a considerable challenge due to the stochastic properties of the actual traffic load. In this paper, a statistical optimal local control policy for dynamic control of power state configurations according to the actual traffic load is proposed to minimize the power consumption while meeting the performance constraints. The packet-level statistical features of network traffic load is modeled as a first-order Markov chain and the dynamic power state selection problem is formulated as a Markov decision process, which can be solved using dynamic programming. In addition, we discuss the possibility of implementing the proposed scheme in real network devices, and design a case study in an NetFPGA frequency scaled router. Simulation results are presented to show the effectiveness of the proposed scheme.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Energy saving local control policy for Green Reconfigurable Routers

Wei

Wang

Feng

et al. 2015

2015 IEEE International Conference on Communications (ICC)

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“…In the real system, referring to our prototype implementation [4] [5], the frequency switching needs only 160 ns. For 10 Gbps real traffic, there are only one to three packets arrived within 1 µs on average.…”

Section: Design Space For Energy Efficient Routersmentioning

confidence: 99%

“…Our previous work [4] [5] [6] implemented a proof-of-concept prototype, an energy efficient reference router with frequency scaling, on NetFPGA platform [7], showing the feasibility and stability of the design. This prototype can adapt its frequency dynamically on five stages, from 125MHz to 42MHz.…”

Section: Introductionmentioning

confidence: 99%

Fine-grained power scaling algorithms for energy efficient routers

Song

Shi

2014

Proceedings of the Tenth ACM/IEEE Symposium on Architectures for Networking and Communications Systems

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Energy efficient router is one of the most important and promising devices in the roadmap towards green communication and networking. In recent years, automatical power scaling adapting with real-time network traffic in a router has been proved to be practical on real hardware, which is an implementation under the traffic aware philosophy. In this paper, we further explore this direction, and present four real-time power scaling algorithms for the fine-grained energy management within a router. These algorithms are all based on the traffic aware philosophy. We first classify the traffic characteristics into three categories of the core router, access router and home router and analyze the differences among them. Then, we propose two design methodologies, periodical scaling and threshold scaling, and address four algorithms in details. Finally, we use real network traffic to evaluate these algorithms and draw the conclusions. The experiments on real traffic show that more than 40% of the energy in a router can be saved by using proposed system-level power scaling methods. Based on those evaluations, we also find that three status modes with two working frequencies and a sleep in a router are enough to achieve near-optimal energy efficiency by using our algorithms, which indicates an easy and practical hardware modification.

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“…Fu et al proposed the method for reducing power consumption of router by controlling clock frequency of router's components [5]. However, in general, frequency adjustment in LSIs is complicated, and delay in the control is not negligible.…”

Section: Related Workmentioning

confidence: 99%

A study on micro level traffic prediction for energy-aware routers

Koyano

Ata

Iwamoto

et al. 2013

SIGOPS Oper. Syst. Rev.

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For green networking, Sliced Router Architecture was proposed, which controls the power consumption of routers by adjusting the routers' performance on the basis of the volume of traffic. In this architecture, traffic prediction is used for appropriate power control of router. For obtaining the efficient gain of power reduction, we need to consider the impact of overestimation or underestimation. In this paper, we propose a traffic prediction method by considering the impact of overestimate and underestimate on power efficiency and processing performance of Sliced Router Architecture. We evaluate our method by trace-driven simulations with real traffic, we show that our approach can control the power consumption of Sliced Router without significant performance degradation.

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A frequency adjustment architecture for energy efficient router

Cited by 7 publications

References 3 publications

Energy saving local control policy for Green Reconfigurable Routers

Energy saving local control policy for Green Reconfigurable Routers

Fine-grained power scaling algorithms for energy efficient routers

A study on micro level traffic prediction for energy-aware routers

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