节能网络中绿色管道、绿色软管和绿色软管-矩形模型的性能比较

B. Das, E. Oki, M. Muramatsu
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引用次数: 2

摘要

本文针对网络功耗最小化问题,提出了一种绿色鲁棒优化模型,该模型能够处理不确定性的网络流量需求。如果我们知道确切的流量需求,绿色管道模型在最小化网络功耗方面排名第一。然而,在现实中,交通需求因各种情况而波动。软管模型是根据每个节点进出流量的总和来计算的,可以允许流量需求的误差,但其功耗高于绿色管道模型。我们提出的方案是基于绿色管道模型的。为了实现鲁棒优化,我们使用了一个不确定性集,它是软管和矩形不确定性集的交集。矩形不确定性集通过增加网络中每个源-目的对的上界和下界来缩小由软管模型定义的流量条件的范围。在交通流的最坏情况下,我们考虑了一个子问题,并以混合整数线性规划(MILP)的形式建立了绿色软管-矩形模型(green HR)。数值结果表明,与绿色软管模型相比,绿色人力资源模型所得到的问题可以通过优化软件得到解决,并且降低了网络功耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Performance of Green Pipe, Green Hose and Green Hose-Rectangle Models in Power Efficient Network
In this paper, a green and robust optimization model is proposed to the problem of minimizing network power consumption which can deal with uncertainty in traffic demands. The green pipe model achieves the first position in terms of minimizing network power consumption if we know the exact traffic demand. However, in reality, traffic demands fluctuate due to various situation. The hose model, which is formulated from the total outgoing/incoming amount of traffic from/to each node can allows errors in the traffic demands but its power consumption is higher than that of the green pipe model. Our proposed scheme is based on the green pipe model. For robust optimization, we use an uncertainty set which is the intersection of the hose and rectangle uncertainty set. The rectangle uncertainty set narrows the range of traffic conditions defined by the hose model by adding the upper and lower bounds for each source-destination pair in the network. In the worst case of traffic flow, we consider a subproblem and formulate the green hose-rectangle model (green HR) in the form of mixed-integer linear programming (MILP). Numerical results demonstrate that the problems obtained by the proposed green HR model can be solved by optimization software and reduce the network power consumption compare to the green hose model.
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