4.7 Article

Power optimization with less state transition for green software defined networking

Publisher

ELSEVIER
DOI: 10.1016/j.future.2020.07.027

Keywords

SDN; Power-saving; Device state transition; Network monitoring; Link congestion

Funding

  1. National Key R&D Program of China [2019YFB1802800]
  2. National Natural Science Foundation of China [61872073]
  3. LiaoNing Revitalization Talents Program, China [XLYC1902010]
  4. Major International (Regional) Joint Research Project of NSFC, China [71620107003]

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The power consumption in the internet industry has been growing rapidly, leading to concerns about high energy consumption. To address this issue, a POLST framework based on SDN is proposed, aiming to achieve high-accuracy real-time network monitoring with low overhead and power optimization with fewer device state transitions. Simulation results demonstrate that POLST outperforms benchmarks in both network monitoring and power optimization.
The power consumed by the Internet industry has been growing sharply in recent years, which accounts for a considerable proportion of the overall power consumption. To reduce high power consumption in the network, numerous proposals on power-saving are proposed. However, they usually reduce power consumption by dynamically sleeping and awakening the network device according to the current traffic fluctuation. When the traffic fluctuate sharply, the network device will swing between sleep and active state frequently, which consumes a considerable power and causes a series of side effects, such as packet losses, short sustainable device service life and synchronization among devices. In this paper, based on Software Defined Networking (SDN), we propose a Power Optimization with Less State Transition (POLST) framework, which mainly achieves the following two functions: (1) Real-time network monitoring with high accuracy and low overhead; (2) Power optimization with less device state transition. Then, we formulate optimization problem of minimizing the network power consumption, while considering power consumed by device state transition. To solve it, we propose a Power Aware Routing with Less State Transition (PARLST) algorithm. Finally, simulation results show that compared with the benchmarks, POLST has excellent performance in both network monitoring and network power optimization. More specifically, in the network monitoring, POLST can achieve up to 97.2% measurement accuracy with low monitoring overhead. In the power optimization, in comparison to the benchmarks, POLST can achieve up to 72.2% energy efficiency, 56.6% decrease in Switch State Transition (SST), 53.5% decrease in Link State Transition (LST). (C) 2020 Elsevier B.V. All rights reserved.

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