Based on the analysis of the space vector modulation strategies for three-level inverters, the duration assignment of the two redundant switching states and the selection of different switching sequences can be considered as two degrees of freedom. The impacts of these two degrees of freedom on the quality of output current are evaluated by using the mathematical model of current ripple established in this study. Moreover, according to the principle of minimum rms value of output current ripple, the optimal assignment of the two redundant states and the optimal distribution of switching sequences are determined. Thus, the optimisation of the output current waveform is realised. The simulation and experimental results show that, for the proposed strategy, the total harmonic distortion (THD) of output current and the weighted THD of output voltage are both lower than that of the conventional strategies.

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The performance of more and more cloud-based applications critically depends on the performance of the interconnecting datacenter network. Emerging reconfigurable datacenter networks have the potential to provide an unprecedented throughput by dynamically reconfiguring their topology in a demand-aware manner. This paper studies the algorithmic problem of how to design low-degree and hence scalable datacenter networks optimized toward the current traffic they serve. Our main contribution is a novel network design which provides asymptotically minimal route lengths and congestion. In comparison to prior work, we reduce the degree requirements by a factor of four for sparse demand matrices. We further show the problem to be already NP-hard for tree-shaped demands, but permits a 2-approximation on the route lengths and a 6-approximation for congestion. We further report on a small empirical study on Facebook traces.

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