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Localization is one of the most important issues in wireless sensor networks, especially for the applications requiring the accurate position of the sensed information. As one of the well known range-free localization algorithms DV-Hop can be simply implemented in real wireless sensor networks without any range measurement tools, but it has bad localization accuracy in asymmetry distributed wireless sensor networks. Thereby, a novel algorithm DDV-Hop based on differential knowledge is proposed in this paper for asymmetry distributed wireless sensor networks. In the research, the differential knowledge is used to improve the average hop-size which is applied by each locating node for estimating itself location through weighting the N received average hop-sizes from anchor nodes. The simulation results show that under the same conditions, this algorithm compared to DV-Hop algorithm and Hop-count method algorithm has higher localization accuracy.