Greening Reliability of Virtual Network Functions via Online Optimization
Greening Reliability of Virtual Network Functions via Online Optimization
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DOI：
10.1109/iwqos49365.2020.9212998
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发表时间：
2020-06
期刊：
影响因子：
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通讯作者：
Xiaojun Shang;Yu Liu;Yingling Mao;Zhenhua Liu;Yuanyuan Yang
中科院分区：
文献类型：
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作者：
Xiaojun Shang;Yu Liu;Yingling Mao;Zhenhua Liu;Yuanyuan Yang
虚拟网络功能（VNF）的快速发展给可靠性带来了新的挑战。广泛采用的部署备份方法会产生财务成本和环境影响。另一方面，将可再生能源纳入计算系统的最新趋势提供了巨大的潜力，但可再生能源发电的波动性带来了重大的运营挑战。在本文中，我们使用动态策略 GVB 在有限的备用预算和可再生能源下优化 VNF 的可用性。 GVB 应用一种新颖的在线算法来解决具有非平稳发电和 VNF 故障的 VNF 可靠性优化问题。理论界限和广泛的模拟结果都强调，与现有基线相比，GVB 提供了更高的可靠性。
The fast development of virtual network functions (VNFs) brings new challenges to providing reliability. The widely adopted approach of deploying backups incurs financial costs and environmental impacts. On the other hand, the recent trend of incorporating renewable energy into computing systems provides great potentials, yet the volatility of renewable energy generation presents significant operational challenges. In this paper, we optimize availability of VNFs under a limited backup budget and renewable energy using a dynamic strategy GVB. GVB applies a novel online algorithm to solve the VNF reliability optimization problem with non-stationary energy generation and VNF failures. Both theoretical bound and extensive simulation results highlight that GVB provides higher reliability compared with existing baselines.