In this article, the sinh-Gordon equations are coped with by contemplating the semidiscretization method and then, the resulting ordinary differential equations at the discretized spaces are numerically integrated tow...
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Earthquake is a violent and irregular ground motion that can severely damage structures. In this paper we subject a single-degree-of-freedom system, consisting of spring and damper, to an earthquake excitation, and me...
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Earthquake is a violent and irregular ground motion that can severely damage structures. In this paper we subject a single-degree-of-freedom system, consisting of spring and damper, to an earthquake excitation, and meanwhile investigate the response behavior from a novel theory about the dynamical system, by viewing the time-varying signum function of It can reflect the characteristic property of each earthquake through and the second component of f, where is a time-sampling record of the acceleration of a ground motion. The barcode is formed by plotting with respect to time. We analyze the complex jumping behavior in a barcode and an essential property of a high percentage occupation of the first set of dis-connectivity in the barcode from four strong earthquake records: 1940 El Centro earthquake, 1989 Loma earthquake, and two records of 1999 Chi-Chi earthquake. Through the comparisons of four earthquakes, we can observe that strong earthquake leads to large percentage of the first set of dis-connectivity.
The present study utilizes VirtualBox virtual environment technology to develop the personal and compact size of multi-node big data VM platform with Spark and Hadoop cluster that can effectively replicate and provide...
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The present study utilizes VirtualBox virtual environment technology to develop the Personal, small size, Big Data platform that can effectively replicate a VM Hadoop system and provides an environment for developers ...
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ISBN:
(纸本)9781467390064
The present study utilizes VirtualBox virtual environment technology to develop the Personal, small size, Big Data platform that can effectively replicate a VM Hadoop system and provides an environment for developers to easily design and implement Hadoop Map/Reduce programming. This study also performs the benchmark by using the VM Hadoop, small-cluster Hadoop, and NCHC's large-scale Hadoop cluster, Braavos. The benchmark results show that the VM Hadoop is an ideal platform for the Map/Reduce code development and testing purpose, and the Braavos Hadoop cluster is the most appropriate for production runs. Moreover, based on the standard WordCount example, the computing time of Braavos Hadoop cluster is 232 times faster than the small-cluster Hadoop. In addition, an engineering example, the image recognition of flow monitoring, is given to illustrate the way of big image data analytics in the Hadoop system. Finally, the VM Hadoop, in term of a Big Data development platform, is ready for users to download. The first author of this paper would like to give a demonstration for the proposed VM Hadoop system as well as an engineering application.
The present study utilizes VirtualBox virtual environment technology to develop the personal and compact size of multi-node big data VM platform with Spark and Hadoop cluster that can effectively replicate and provide...
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ISBN:
(纸本)9781538633038
The present study utilizes VirtualBox virtual environment technology to develop the personal and compact size of multi-node big data VM platform with Spark and Hadoop cluster that can effectively replicate and provides an environment for developers to easily design and implement Spark and Hadoop Map/Reduce programming. By using the multi-node Hadoop VM system, developers can conduct Map/Reduce programing completely the same as that in the real multi-node Hadoop cluster. To demonstrate its capability and applicability, this study performs the benchmark by using the big data VM platform and a physical Multi-Node Hadoop Cluster. Based on the standard WordCount benchmarking, the computing time of the physical multi-node Hadoop cluster is 3.7 times faster than that of VM Hadoop cluster. The benchmark results show that the big data VM platform is an ideal platform for the portal and Map/Reduce programming, Spark programming and testing purposes, and the physical Hadoop cluster is the most appropriate for production runs. In addition, the big data VM platform contains a web portal development module designed to support applications that implement big data computing services for the engineering and science users. Such applications are inherently complex, potentially accessing data from a variety of sources and distributing applications to a variety of clients. This portal development module can act as multiple roles in many projects such as personal portals, small business portals, enterprise portals, educational portal, infrastructure portal, and other types of portals. Finally, the big data VM platform, in term of a big data development platform, is ready for users to download. The first author of this paper would like to give a demonstration for the proposed multi-node big data VM platform.
This paper introduces research and development results of extended functions on our network virtualization infrastructure which achieve advanced network virtualization. Our results achieved to meet five requirements w...
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This paper introduces research and development results of extended functions on our network virtualization infrastructure which achieve advanced network virtualization. Our results achieved to meet five requirements which are resource abstraction, resource isolation, resource elasticity, deep programmability and authentication. In addition, we proposed evolvable architecture and extended network virtualization for edge network and terminals. We also deployed our system on JGN-X testbed.
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