Virtual Simulation Management of Data Traffic Optimization of Big Data Cloud Platform considering Multipoint Mapping Algorithm

With the continuous development of Internet, cloud computing, and other technologies, build a cloud platform based on Cloud Computing Center, but how to effectively carry out operation and maintenance and face users to ensure the continuity and effectiveness of the platform is extremely important. In view of these needs and limitations, this paper introduces the multipoint mapping algorithm, combs the statistical methods of platform cloud traffic, carries out platform data traffic by classification, constructs the data traffic optimization management model, analyzes the relevant data samples, carries out statistical calculation for data diversion tasks, analyzes and processes the priority indicators, and forms the final results through continuous iteration, realizing the management of data flow optimization virtual simulation of big data cloud platform. Simulation results show that the multipoint mapping algorithm is effective and can effectively support the data flow of big data cloud platform and optimize virtual simulation management.

A comment on Xie and Xu: ‘Mapping quantitative trait loci in tetraploid species’

Xie & Xu (2000) present a model for mapping quantitative trait loci in an autotetraploid population. However, one aspect of their model, namely gamete formation, does not properly represent the biological process in autotetraploid species. This paper gives a more realistic formulation for this part of the model, and discusses the consequences for multipoint mapping.