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He is also interested in "big data" applications in environmental and climate studies, social science, and recommender systems.
Future datacenters infrastructure including interconnection network, storage, and servers should be able to handle big data applications in an energy-efficient way.
However, topical studies tend to deal largely with the IoT and related big data applications in connection with economic growth and the quality of life in the realm of smart cities, and largely ignore their role in improving environmental sustainability in the context of smart sustainable cities of the future.
In terms of originality, no study has been conducted on the IoT and related big data applications in the context of smart sustainable cities, and this paper provides a basis for urban researchers to draw on this analytical framework in future research.
In order to compare and evaluate these multi-stage compression techniques and to design more efficient compression methods for big data applications, in this paper the effectiveness of each of these compression stages on the total performance of the algorithm is analyzed.
"We aim to become the platform businesses come to in order to buy big data applications in the cloud".
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Focusing on behavior big data mining and big data application in urban studies and planning practices, the review is proposed from four parts, involving behavior data acquisition & analysis, spatial analysis, plan making & management application and new methodologies with big data.
Efficient collection of big data such as equipment status, maintenance and grid operation in power systems, and data mining are the important research topics for big data application in smart grid.
A new generation of big data applications have blossomed in this ecosystem, which in turn has put pressure on enterprise vendors to modify existing software suites.
Many "big data" applications must act on data in realtime.
I am working on developing efficient networking solutions to handle the amount of data and computation involved in big data applications," he says.
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