Review of Ubiquitous Computing Based on Markov Chain and High Complexity Data Streaming Model

Review of tourism informationization based on the Markov Chain and the high complexity data streaming model is studied in this manuscript. Most of the recommendation systems are poor in scalability due to their own defects. Although some optimization strategies have been adopted to improve them, most of them are further optimized and mainly run on a single server. Hence, this paper has some modifications. First, the choice of cache node location can be attributed to the resource allocation problem, which is also focus of research in doud environment, we construct the efficient data center for preparing. Second, the grid resource discovery method must be able to adapt to the grid environment circle with characteristics of some large scale, heterogeneity, distribution, dynamic, openness and so on. We find the optimal model to avoid the time delay. The experiment results compared with the latest methods have been presented.