scholarly journals Big Data Storage Technology suitable for the Operation and Maintenance of New Generation Power Grid Dispatching Control System Operation

Author(s):  
Yin Zhang ◽  
Yansheng Lang ◽  
Song Yang ◽  
Kun Zhao ◽  
Peng Liu ◽  
...  
Author(s):  
Anupama C. Raman

Unstructured data is growing exponentially. Present day storage infrastructures like Storage Area Networks and Network Attached Storage are not very suitable for storing huge volumes of unstructured data. This has led to the development of new types of storage technologies like object-based storage. Huge amounts of both structured and unstructured data that needs to be made available in real time for analytical insights is referred to as Big Data. On account of the distinct nature of big data, the storage infrastructures for storing big data should possess some specific features. In this chapter, the authors examine the various storage technology options that are available nowadays and their suitability for storing big data. This chapter also provides a bird's eye view of cloud storage technology, which is used widely for big data storage.


2019 ◽  
Vol 479 ◽  
pp. 567-592 ◽  
Author(s):  
Yang Yang ◽  
Xianghan Zheng ◽  
Wenzhong Guo ◽  
Ximeng Liu ◽  
Victor Chang

Author(s):  
Ming Yang ◽  
Wenchun He ◽  
Zhiqiang Zhang ◽  
Yongjun Xu ◽  
Heping Yang ◽  
...  

Abstract With the development of the meteorological IoT (Internet of Things) and meteorological sensing network, the collected multi-source meteorological data have the characteristics of large amount of information, multidimensional and high accuracy. Cloud computing technology has been applied to the storage and service of meteorological big data. Although the constant evolution of big data storage technology is improving the storage and access of meteorological data, storage and service efficiency is still far from meeting multi-source big data requirements. Traditional methods have been used for the storage and service of meteorological data, and a number of problems still persist, such as a lack of unified storage structure, poor scalability, and poor service performance. In this study, an efficient storage and service method for multidimensional meteorological data is designed based on NoSQL big data storage technology and the multidimensional characteristics of meteorological data. In the process of data storage, multidimensional block compression technology and data structures are applied to store and transmit meteorological data. In service, heterogeneous NoSQL common components are designed to improve the heterogeneity of the NoSQL database. The results show that the proposed method has good storage transmission efficiency and versatility, and can effectively improve the efficiency of meteorological data storage and service in meteorological applications.


2015 ◽  
Vol 12 (6) ◽  
pp. 106-115 ◽  
Author(s):  
Hongbing Cheng ◽  
Chunming Rong ◽  
Kai Hwang ◽  
Weihong Wang ◽  
Yanyan Li

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