The Application of Mobile Cloud in Heterogeneous Data Storage in Web of Things System

With the further development of Internet of Things technology, due to the increasing data and poor expansibility of the traditional storage architecture, it will become increasingly complex and lead to high energy consumption. Different from the traditional storage system, the distributed cloud storage system can realize the storage of massive information, the management of files with large scale, and provide high query efficiency. This paper firstly presents the current problems lying in the heterogeneous data processing, Then the cloud storage architecture and MapReduce programming model are introduced for the Classify MapReduce algorithm proposition. Finally, considering the processing methods of distributed computing and cloud computing models, advantages and disadvantages of MapReduce programming model, and the characteristics of heterogeneous data in IoT system, this paper proposes a parallel storage algorithm, Classify MapReduce, which is composed of three systemic functions: Classify function, Map function and Reduce function. Our experiment shows that it classifies the original heterogeneous data flow according to the data type to realize parallel processing, which greatly improves the storage and access efficiency.