Theoretical analysis of constructing wavelet synopsis on partitioned data sets

Kim, Chulyun

doi:10.1007/s11042-014-1908-3

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…MapReduce also has become a primary choice for cloud providers to deliver data analytical services (Zhao et al 2014). Many traditional algorithms and data processing in a single machine environment are transferred to the MapReduce platform (Kim 2014;Cosulschi, Cuzzocrea, and De Virgilio 2013). For example, Kim (2014) analyzed an algorithm to generate wavelet synopses on the distributed MapReduce framework.…”

Section: Mapreduce (Hadoop) Systemmentioning

confidence: 99%

Big Data and cloud computing: innovation opportunities and challenges

Yang

Huang

et al. 2016

International Journal of Digital Earth

645

289

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Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers-Big Data and cloud computingand reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.

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Section: Mapreduce (Hadoop) Systemmentioning

confidence: 99%

Big Data and cloud computing: innovation opportunities and challenges

Yang

Huang

et al. 2016

International Journal of Digital Earth

645

289

View full text Add to dashboard Cite

show abstract

“…The receiver-centric approach achieves a better level of spatial reuse with a degree of interference prevention. The paper by Chulyun Kim [14] introduces and analyzes the MAVELET algorithm, which constructs a whole wavelet synopsis on distributed data sets. Wavelet synopsis is one of the most popular dimensionality reduction methods, and MapReduce is the most popular distributed platform, with good scalability and fault tolerance.…”

mentioning

confidence: 99%

Guest Editorial: Convergence and Advanced Technology

Ghose

Ryu

2015

Multimed Tools Appl

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Convergence and advanced technologies spring forth as a result of lateral entry by firms in different markets, and today, there is a synergistic combination of traditional industries and state-of-the-art technologies, such as information technology. The main goal of this issue is to bring researchers from academia together with professionals from different industries to share algorithms, solutions, and architectures as well as their experiences. We expect this special issue to be viewed as a continuum of products and as the lateral entry of research from different technological perspectives on digital management. The effort diffuses technological competencies and values within existing technologies' base information systems. The convergence process blurs traditional technological and sectorial boundaries and thus opens new avenues of technological innovation in ubiquitous technologies [1,4,6,10,15]. This issue challenges processing overhead in convergence and advanced technologies.The paper by Kim et al. [5] introduces an efficient mobility management scheme for convergence of mobile media multicast services in next-generation networks. The proposed scheme applies a method to quickly rejoin a relevant multicast stream by enabling the AIMS-MM system to collect multicast group information through a multicast group information handler located in the multicast router. The paper by Oh et al. [2] presents the development of a one-source multi-use cross-platform based on zero coding. This method is to research and develop a native application-based development tool that can perfectly satisfy both onesource-multi-use and cross-platform, and secure stable hardware control and execution speed.The paper by presents low-cost image indexing for a massive database. The proposed method is an identifier generation for indexing that is efficient and effective from the perspective of cost and indexing performance, in order to compose identifiers with high cardinality. The paper by Jo et al. [9] presents an access control system for secure extensible markup language (XML) telemedicine documents. This Multimed Tools Appl (2015) 74:2195-2200

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Domain Application of High Performance Computing in Earth Science: An Example of Dust Storm Modeling and Visualization

Huang

Zhang

2020

Geotechnologies and the Environment

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Theoretical analysis of constructing wavelet synopsis on partitioned data sets

Cited by 5 publications

References 15 publications

Big Data and cloud computing: innovation opportunities and challenges

Big Data and cloud computing: innovation opportunities and challenges

Guest Editorial: Convergence and Advanced Technology

Domain Application of High Performance Computing in Earth Science: An Example of Dust Storm Modeling and Visualization

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