Research on data pre-deployment in information service flow of digital ocean cloud computing

Data pre-deployment in the HDFS （Hadoop distributed file systems） is more complicated than that in traditional file systems. There are many key issues need to be addressed, such as determining the target location of the data prefetching, the amount of data to be prefetched, the balance between data prefetching services and normal data accesses. Aiming to solve these problems, we employ the characteristics of digital ocean information service flows and propose a deployment scheme which combines input data prefetching with output data oriented storage strategies. The method achieves the parallelism of data preparation and data processing, thereby massively reducing I/O time cost of digital ocean cloud computing platforms when processing multi-source information synergistic tasks. The experimental results show that the scheme has a higher degree of parallelism than traditional Hadoop mechanisms, shortens the waiting time of a running service node, and significantly reduces data access conflicts.

“Digital earth” in support of an online oceanic educational public service and popularization

According to the initial vision of ＂digital earth＂ （DE）, the public should constitute a significant proportion of its users. However, to date, most of the studies and applications have focused on science, the private sec- tor and government. A DE-supported online oceanic educational public service and popularization system, iOcean, is studied. First, the vision for the public＇s engagement with ＂digital ocean＂ is described： an analysis is presented from four aspects, i.e., the space dimension, the time dimension, the state dimension and its relationship with human beings. Second, the technical framework of iOcean is discussed, including data updating and model computing, the data, the function, and the application layers. Third, two key technolo- gies are studied in detail that will enable the construction of iOcean. More than half a million public viewers have used the current version＇s website. Practical demonstrations show that iOcean can bring virtual oceans to web browsers and desktops and construct a bridge between government departments and the general public.

China Digital Ocean Prototype System

Digital Ocean is a new research domain of Digital Earth.Because of the spatiotemporal,three-dimensional(3D)and intrinsically dynamic nature of ocean data,it is more difficult to make a breakthrough in this domain.The construction of the China Digital Ocean Prototype System(CDOPS)pushes Digital Ocean a step forward from its operation as a mere concept to its achievement as a realistic system.In this paper,the technical framework of the CDOPS is discussed,including its data,function,and application layers.Then,two key technologies are studied in detail that will enable the construction of the 3D ocean environment and the visualization of the ocean model output data.Practical demonstrations show that the CDOPS provides a technical reference for the development of Digital Ocean.This paper is based on an ongoing research project of the development of CDOPS that aims at the facilitation,integration,sharing,accessing,visualization,and use of the ocean data and model computing data from the Digital Earth perspective.

New insight into smart ocean:how is it different from digital ocean?

Oceans occupy approximately seventy-one percent of the earth’s surface,and vast regions of oceans are virtually unexplored,especially the deep parts where humans have never been.Therefore,it is urgent to understand our oceans from a number of perspectives.In this paper,the concept of Smart Ocean(SO)is constructed from the perspectives of environmental protection,sustainable development of the blue economy and marine disaster prevention and mitigation.First,a doublefunnel structure concept model of SO,including ocean observation infrastructure,data,information,application,knowledge and decision support layers,is put forward.Second,the differences between SO and Digital Ocean(DO)are analyzed.Third,taking the Decision Support System for Emergency at Taiwan Strait as an example,a case study,which has assisted in saving more than 200 people,is introduced.Finally,future research agenda is summarized into seven aspects,including new instrumentation and sensor technologies,ocean big data mining and knowledge discovering,prediction,forecast and uncertainty analysis,ocean environment protection technologies and policy,sustainable use of ocean energy and resource,the influence and response to global changes in the ocean,and interdisciplinary collaboration and public service.