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A note on resource management techniques and systems for big data workflow processing
2018
Computing
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Hence, elasticity management of various resources for such big data analytics workflow is both difficult and challenging. ...
A typical streaming data analytics workflow consists of three layers: data ingestion, analytics, and storage, each of which is backed by different data processing platforms (e.g. ...
The first paper titled "A parallel online trajectory compression approach for supporting big data workflow" by authors W. Han, Z. Deng, J. Chu, J. Zhu, P. Gao and T. ...
doi:10.1007/s00607-018-0586-9
fatcat:qtlrtyouffffxghaefep6wjkji
A Survey on Trajectory Big Data Processing
2018
International Journal of Performability Engineering
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As the massive trajectory data processing exceeds the power of centralized approaches used previously, in this paper, we survey various existing tools used to process large-scale trajectory data in a distributed ...
Further, a wide spectrum of application domains can benefit from trajectory data mining including trajectory organization as well as queries. ...
Acknowledgements This paper was partially supported by NSFC grant U1509216,61472099, National Sci-Tech Support Plan 2015BAH10F01, the Scientific Research Foundation for the Returned Overseas Chinese Scholars ...
doi:10.23940/ijpe.18.02.p13.320333
fatcat:m74w3cfajrbzpamzpghfyrm6am
ICDE conference 2015 detailed author index
2015
2015 IEEE 31st International Conference on Data Engineering
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Alfons
1280
Supporting Hierarchical Data in SAP HANA
Kersten, Martin
1119
The DBMS -Your Big Data Sommelier
Khan, Hina A.
327
Progressive Diversification for Column-Based Data Exploration ...
for Research Documents
Huang, Jiamin
963
Making Sense of Trajectory Data: A Partition-and-Summarization Approach
Huang, Jianbin
1561
StreamCube: Hierarchical Spatio-Temporal Hashtag Clustering ...
doi:10.1109/icde.2015.7113260
fatcat:ep7pomkm55f45j33tkpoc5asim
Increasing Maritime Situation Awareness via Trajectory Detection, Enrichment and Recognition of Events
[chapter]
2018
Lecture Notes in Computer Science
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Acknowledgments This work was supported by project datACRON, which has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 687591. ...
While consuming this data, statistics (min/max/avg) are computed over properties, such as speed and acceleration, in an online fashion; online data cleaning of erroneous data, and trajectory compression ...
Due to the immense data volume, parallel data processing is performed over RDF data stored in a distributed way. ...
doi:10.1007/978-3-319-90053-7_13
fatcat:mwpj6jpozfdmxmtbde3t3qqknq
ICDE conference 2015 table of contents
2015
2015 IEEE 31st International Conference on Data Engineering
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Anti-Caching"-based Elastic Memory Management for Big Data (Hao Zhang, Gang Chen, Beng Chin Ooi, Weng-Fai Wong, Shensen Wu, Yubin Xia) 1280 Supporting Hierarchical Data in SAP HANA (Robert Brunel, Jan ...
Singh)
[Search]
ICDE Conference 2015 Table of Contents
[Page 11 / 20]
Research Session 21: Trajectories
963
Making Sense of Trajectory Data: A Partition-and-Summarization Approach
(Han Su, ...
Industry Session 3: Big Data 1304 Accelerating Big Data Analytics with Collaborative Planning in Teradata Aster 6 (Aditi Pandit, Derrick Kondo, David Simmen, Anjali Norwood, Tongxin Bai) [Search] ...
doi:10.1109/icde.2015.7113258
fatcat:yvim4gc5rfhevoehwfvl35nqji
D6.1 Data Synopses Generator V1
2019
Zenodo
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For the reasons argued in this deliverable, the SDE has been developed on Apache Flink Big Data platform, one of the most prominent frameworks designed to operate as a true streaming engine and to com ...
as well as synopses destined to support INFORE use case workflows. ...
Moreover, INFORE workflows may engage operators implemented in a variety of Big Data platforms. ...
doi:10.5281/zenodo.4034117
fatcat:mpmokdqud5dxpauxhffuuy2qge
Big data and extreme-scale computing
2018
The international journal of high performance computing applications
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in a scalable manner to meet the highly diverse requirements for processing, communication, and buffering/storage of massive data workflows of many different scientific domains. ...
Over the past four years, the Big Data and Exascale Computing (BDEC) project organized a series of five international workshops that aimed to explore the ways in which the new forms of data-centric discovery ...
They would also gratefully acknowledge all the following sponsors who supported the big data and exascale computing workshop series: Government Sponsors: US Department of Energy, the National Science Foundation ...
doi:10.1177/1094342018778123
fatcat:vwrrxmad4rhtppq6ioaz4h5q7a
Online Long-Term Trajectory Prediction Based on Mined Route Patterns
[chapter]
2020
Lecture Notes in Computer Science
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In this paper, we present a Big data framework for the prediction of streaming trajectory data by exploiting mined patterns of trajectories, allowing accurate long-term predictions with low latency. ...
In particular, to meet this goal we follow a two-step methodology. First, we efficiently identify the hidden mobility patterns in an offline manner. ...
This work was partially supported by projects datACRON (grant agreement No 687591), Track&Know (grant agreement No 780754) and MAS-TER (Marie Sklowdoska-Curie agreement N. 777695), which have received ...
doi:10.1007/978-3-030-38081-6_4
fatcat:6n5heoumwfguln3chpcp35uifm
Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales
2017
2017 IEEE 24th International Conference on High Performance Computing (HiPC)
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Instead, applications must analyze and reduce data online so as to output only those results needed to answer target scientific question(s). ...
A growing disparity between supercomputer computation speeds and I/O rates makes it increasingly infeasible for applications to save all results for offline analysis. ...
To tackle this unprecedented data flow, the Alice project has defined a new combined offline-online framework called O2 that supports data flows and processing. ...
doi:10.1109/hipc.2017.00042
dblp:conf/hipc/Foster17
fatcat:li6yvnrkqbe6blhn72mqv64sre
2020 Index IEEE Transactions on Knowledge and Data Engineering Vol. 32
2021
IEEE Transactions on Knowledge and Data Engineering
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., +, TKDE Aug. 2020 1625-1638
VA-Store: A Virtual Approximate Store Approach to Supporting Repetitive
Big Data in Genome Sequence Analyses. ...
., +, TKDE Oct. 2020 2040-2059
VA-Store: A Virtual Approximate Store Approach to Supporting Repetitive
Big Data in Genome Sequence Analyses. ...
doi:10.1109/tkde.2020.3038549
fatcat:75f5fmdrpjcwrasjylewyivtmu
EHR Big Data Deep Phenotyping
2014
IMIA Yearbook of Medical Informatics
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The use of big data approaches are described that enable scalable markup of EHR events that can be used for semantic and temporal similarity analysis to support the identification of phenotype and genotype ...
The big data solution, using flexible markup, provides a route to improved utilization of processing power for organizing patient records in genotype and phenotype research. ...
Acknowledgments The authors LJF and LL were supported by the grant 1R01GM108346-01: ...
doi:10.15265/iy-2014-0006
pmid:25123744
pmcid:PMC4287080
fatcat:oadqazqyqvbd5fv7acuw3vzgxq
A Synopses Data Engine for Interactive Extreme-Scale Analytics
[article]
2020
arXiv
pre-print
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data summarization facilities even for cross-(Big Data) platform workflows, (d) pluggability of new synopses on-the-fly, (e) increased potential for workflow execution optimization. ...
In this work, we detail the design and structure of a Synopses Data Engine (SDE) which combines the virtues of parallel processing and stream summarization towards delivering interactive analytics at extreme ...
Therefore, a SDEaaS design does not allow for using the native windowing support provided by the Big Data platform because the various windows are not known in advance. ...
arXiv:2003.09541v2
fatcat:kq4c433dlngn3faq3467lxc3dy
Big Data and cloud computing: innovation opportunities and challenges
2016
International Journal of Digital Earth
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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 ...
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 ...
Acknowledgements We thank the anonymous reviewers for their insightful comments and reviews. Dr George Taylor reviewed a previous version of this manuscript. ...
doi:10.1080/17538947.2016.1239771
fatcat:qbcgqj2pcvbgja6dnnakoj2saa
Managing scientific data
2010
Communications of the ACM
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, and ultimately a grand theory to explain all physical phenomena. ...
Proposed solutions also promise to achieve efficient management for almost any other kind of data. ...
Therefore, the data sets would benefit from a generic DBMS customizable procedure supporting compression. ...
doi:10.1145/1743546.1743568
fatcat:vw57d23aorchtntng6jlrccs6y
Managing scientific data
2011
Proceedings of the 2011 international conference on Management of data - SIGMOD '11
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, and ultimately a grand theory to explain all physical phenomena. ...
Proposed solutions also promise to achieve efficient management for almost any other kind of data. ...
Therefore, the data sets would benefit from a generic DBMS customizable procedure supporting compression. ...
doi:10.1145/1989323.1989433
dblp:conf/sigmod/Ailamaki11
fatcat:3cxviarugnfoldnqz3csgjczqu
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