Research On Heterogeneous Data Storage Of The Things Of Internet

With further development of the things of Internet technology, and the face ofthe growing data storage architecture, due to poor scalability, and increased usercapacity and performance requirements can only blindly add high-end storage devices.Over time, the storage environment becomes increasingly complex and causesexcessive energy consumption. Unlike traditional storage systems, distributed cloudstorage system can achieve massive data storage systems to efficiently manage files,and file query efficiency. Distributed cloud storage system is based on Internettechnology, a small picture stream, streaming video and other data users for theInternet industry, as the main storage in the Internet of Things, the need for vastamounts of picture stream as well as video streaming and other data storage and useof repeated. The things of Internet you need to collect the sound, light, heat,electricity, chemistry, location information to differ materially from the informationcontent captured by the different types of sensors and information receivers.Therefore, data formats, including in the Internet of Things is far more complexthan the Internet types. Video monitoring and Timely warning industry, needs morestringent performance requirements for real-time heterogeneous data access. So wecarried out research on the Internet of things within the data center storage algorithm,combined with the advantage of distributed cloud storage system architecture for theInternet of Things heterogeneous mass of data and real-time characteristics, comparedto objects based on networked real-time heterogeneous data access features, thispaper presents the Internet of Things heterogeneous data storage algorithms, mainlyin the following two work:1. Distributed storage algorithm based on the Internet of things. This algorithmby using the design of system storage level indicators within the data centerclassification of massive data storage mechanism, to solve the allocation problem ofdata consistency between the data center; send communication packets between datacenters through the Internet of Things, in a timely manner the receiver of the communication message to solve the communication problems of mutualunderstanding between the data center storage state; the concept of "full storage"storage, to achieve complete local storage of each data stream, to solve the originaldata stream unusually large-scale data storage allocation problem. Cluster-basedthree-tier storage architecture constitutes a framework architecture based ondistributed heterogeneous data in the Internet of Things data center storage toheterogeneous data between the Internet of Things data center marginalized throughthe Things of Internet Distributed data storage algorithms storage, and ultimately toachieve load balancing of storage resources.2. Parallel storage algorithm based on the classification of Things. Thisalgorithm is cluster-based three-tier storage architecture for the Internet of Things,described, including three nodes resources, which the Monitor node is responsible formonitoring the health of the entire system, as well as dealing with the Internet ofThings terminal storage request; Server, node directly Storer, the node is responsiblefor all data resources in the actual storage of Things Internet of Things, businessprocessing and information services; the ClassifyMapReduce classification of parallelstorage algorithm, based on the three-tier storage the framework of the architecturedesign of the data analysis algorithms, data mapping algorithms and data mergingalgorithm, and joined the process migration and super-pipelined technology, with ahigh degree of real-time and effectiveness of Things heterogeneous data classificationparallel storage functions.Finally, the above two design algorithms are experimental. The experimentalresults show that changes in the status of the adaptive data center storage can bebetter distributed storage algorithm based on the Internet of things between the datacenter, smooth data center’s storage capacity to ensure that the marginalization of thevast amounts of data stored in the Internet of Things. Parallel storage algorithm,based on the classification of Things data center and high concurrent access to hugeamounts of data in the Internet of Things, can effectively improve real-timeheterogeneous data storage, to ensure the efficiency of mass data storage.