| Medical data processing system based on cloud computing is an important part of WIT120. It has played a key role in the wisdom of total medical architecture soft services. The main research content is the key technology of data collection, data mining and the data access of the system.In order to solve the problem of data collection and storage, a distributed message queue log collection system was proposed. The system realized the high concurrency of log collection by the way of subscribing – released, designed a main line of data which had high throughput to store data. The main line accepted a variety of data, and stored data which were imported into distributed file system by batch and real-time strategies. In order to solve the problem of how to efficiently mine and analyze the characteristics of data which were collected, a distributed framework of K item the most frequent closed item sets mining algorithm was put forward. The traditional FP- Growth algorithm was improved. It had high computing performance. The distributed implementation of algorithm provided processing ability of high fault tolerance under large-scale data, so the characteristics of the data could be analyzed. In order to enhance the performance of user access to data platform, a distributed cache cluster framework was proposed. This framework supported reliable storage of large-scale data, had high concurrent data access ability, and had management interface with easy management. Framework solved high concurrent requests of a large number of users, and returned the user concerns under a millisecond. Backup redundancy mechanism of framework provided guarantee for nondestructive completeness of data storage, and extensibility of framework is also very good.Experiment based on the above research shows that the three directions are the basic guarantee of high concurrency, low latency, mass storage of medical data processing system based on cloud computing. |
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