Abstract:Cloud computing, often referred to as simply 'the cloud', is the delivery of on-demand computing resources-everything from applications to data centers-over the Internet on a pay-for-use basis [3]. Cloud computing also promises to accommodate a huge volume of data that is regarded as a promising methodology to deal with efficient big data processing. Integration of cloud and big data ecosystems thereby not only allows improved cloud resource utilization and efficiency but also brings optimized performance for … Show more
“…Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze [1]. Massive data from social media, mobile application, the Internet of things, and more has result to the hot research in big data.…”
Abstract. Big data has become the hottest topic with the cloud computing and massive data generation. Based on Hadoop, MapReduce and their ecosystem, there are number of improved and optimized big data dealing and analysis platforms. Extensive applications in the Internet of Things, social network, transport, medical, education, and etc. have attracted huge interests and attentions of researchers and industries. To form a hostile profile view, it is necessary to explore big data architecture, platform, application and trend. Abstract architecture and workflow graph of big data is presented, some hot platforms are reviewed and illustrated, and big data application and trend are proposed. The main contribution is to provide detailed and systematic survey and discussion to form a whole technology framework and overview of big data.
“…Big data refers to datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze [1]. Massive data from social media, mobile application, the Internet of things, and more has result to the hot research in big data.…”
Abstract. Big data has become the hottest topic with the cloud computing and massive data generation. Based on Hadoop, MapReduce and their ecosystem, there are number of improved and optimized big data dealing and analysis platforms. Extensive applications in the Internet of Things, social network, transport, medical, education, and etc. have attracted huge interests and attentions of researchers and industries. To form a hostile profile view, it is necessary to explore big data architecture, platform, application and trend. Abstract architecture and workflow graph of big data is presented, some hot platforms are reviewed and illustrated, and big data application and trend are proposed. The main contribution is to provide detailed and systematic survey and discussion to form a whole technology framework and overview of big data.
In GNSS (Global Navigation Satellite System) Distributed Simulation Environment (GDSE), the simulation task could be designed with the sharing models on the Internet. However, too much information and relation of model need to be managed in GDSE. Especially if there is a large quantity of sharing models, the model retrieval would be an extremely complex project. For meeting management demand of GDSE and improving the model retrieval efficiency, the characteristics of service simulation model are analysed firstly. A semantic management method of simulation model is proposed, and a model management architecture is designed. Compared with traditional retrieval way, it takes less retrieval time and has a higher accuracy result. The simulation results show that retrieval in the semantic management module has a good ability on understanding user needs, and helps user obtain appropriate model rapidly. It improves the efficiency of simulation tasks design.
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