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It’s a hot issue to improve the ac-curacy of network coordinate systems (NCS). By analyzing the error source of NCSes, it’s emphasized that guaranteeing the low dimensionality of embedding datasets is the principle on the designing of NCSes. Based on this observation, a PCA based Intet de-lay space dividing algorithm (IDSD-PCA) is proposed. Beginning at choosing an optimized sub dataset randomly, IDSD-PCA partitions the Intet delay dataset into several sub datasets with low dimensionality by iterations. After the partition, the whole delay dataset and sub datasets are embedded into a hierar-chical NCS. The experimental results show that with this framework both the metric space based models and the non-metric space based models can predict the end-to-end delays more accurately.