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Cloud Computing and Grid Computing 360-Degree Compared [article]

Ian Foster, Yong Zhao, Ioan Raicu, Shiyong Lu
2008 arXiv   pre-print
systems in general.  ...  However, there are dozens of different definitions for Cloud Computing and there seems to be no consensus on what a Cloud is.  ...  We add yet another definition to the already saturated list of definitions for Cloud Computing: A large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted  ... 
arXiv:0901.0131v1 fatcat:ybwx6z62k5fnpcyicyxvxsydou

Complete Decentralization of Distributed Data Storages Based on Blockchain Technology [article]

Andrey Demichev, Alexander Kryukov
2021 arXiv   pre-print
The work presents a solution for completely decentralized data management systems in geographically distributed environments with administratively unrelated or loosely related user groups and in conditions  ...  management in collaborative distributed computing systems.  ...  can be found in the work [5]. 2 Decentralized collaborative distributed sys- tems In the case of large-scale projects related to data handling and involving participants from different administrative  ... 
arXiv:2112.10693v1 fatcat:ngmys2isvngsboxjdxsvyphope

Big Data Storage [chapter]

Martin Strohbach, Jörg Daubert, Herman Ravkin, Mario Lischka
2016 New Horizons for a Data-Driven Economy  
Following are differing types of storage systems: • Distributed File Systems: File systems such as the Hadoop File System (HDFS) (Shvachko et al. 2010) offer the capability to store large amounts of  ...  In all of these areas, NoSQL storage technologies prove a key enabler to efficiently analyse large amounts of data and create additional business value.  ... 
doi:10.1007/978-3-319-21569-3_7 fatcat:r7huxlg35fdulovdvoo2t2tfna

Opportunities and Challenges in Running Scientific Workflows on the Cloud

Yong Zhao, Xubo Fei, Ioan Raicu, Shiyong Lu
2011 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery  
The application of Cloud computing, however, has mostly focused on Web applications and business applications; while the recognition of using Cloud computing to support large-scale workflows, especially  ...  We coin the term "Cloud Workflow", to refer to the specification, execution, provenance tracking of large-scale scientific workflows, as well as the management of data and computing resources to enable  ...  We define Cloud computing as a large-scale distributed computing paradigm that is driven by economies of scale, in which a pool of abstracted, virtualized, dynamically-scalable, managed computing power  ... 
doi:10.1109/cyberc.2011.80 dblp:conf/cyberc/ZhaoFRL11 fatcat:zlpe7p73lnh2jksgtnstvkafn4

Research Progress of Stream Data Query in Network Space

Yi Wu, Jianjun Zhou
2015 International Journal of Database Theory and Application  
38] reduced response time that restricts Skyline query procedure in large scale distributed environment by reinforcing the collateral processing between node groups.  ...  There are a lot of questions waiting for scientists to explore. For example, the problem of Skyline query under the communication restriction in distributed concurrent environment.  ...  The author would like to thank for their support. International Journal of Database Theory and Application Vol. 8, No.5 (2015)  ... 
doi:10.14257/ijdta.2015.8.5.14 fatcat:2jfxpbvlgfctxe7rl24gd2hxom

Collaborative scientific workflows supporting collaborative science

Shiyong Lu, Jia Zhang
2011 International Journal of Business Process Integration and Management  
Recently, scientific workflows have emerged for scientists to integrate distributed computations, datasets, and analysis tools to enable and accelerate scientific discovery.  ...  This paper presents a disciplinary definition of this term, discusses the opportunities, requirements, and challenges of collaborative scientific workflows for the enablement of scientific collaboration  ...  A second challenge is to capture, manage, and utilize large amounts of distributed, heterogeneous, multi-level, and collaborative provenance data for the reproducibility of scientific results produced  ... 
doi:10.1504/ijbpim.2011.040209 fatcat:5op5on2xgffhjabh7wgjrfuhai

Maintaining Secure Cloud by Continuous Auditing

M. Kanimozhi, A. Aishwarya, S. Triumal
2018 International Journal of Trend in Scientific Research and Development  
The complexity resulting from large scale virtualization and data distribution carried out current clouds has revealed an urgent research agenda for cloud accountability, as has the shift in focus of customer  ...  capability means that individuals and organizations of all sizes have more capacity and agility to exercise shifts in computation and to disrupt industry in cyberspace than more traditional domains of business  ...  Secure provenance [28] and privacy-aware provenance [29] have also been proposed for cloud computing systems, as provenance information may contain or expose sensitive, confidential or proprietary information  ... 
doi:10.31142/ijtsrd10829 fatcat:qblqsdvq4rblzbjm2ygg3krely

Provenance-Aware Sensor Data Storage

J. Ledlie, Chaki Ng, D.A. Holland
2005 21st International Conference on Data Engineering Workshops (ICDEW'05)  
in a larger distributed system.  ...  We show how provenance addresses the naming and indexing issues and then present a research agenda for constructing distributed, indexed repositories of sensor data.  ...  Constructing a distributed provenance-aware storage system requires solving both of these problems.  ... 
doi:10.1109/icde.2005.270 dblp:conf/icde/LedlieNH05 fatcat:4utwyrkv4zgyxgwclyvn6cifpq

Special issue for data intensive eScience

Judy Qiu, Dennis Gannon
2012 Distributed and parallel databases  
We now live in the world of massive multi-core and GPU processing systems, very large main memory systems, fast networking components, fast solid state drive, and large data centers that consume massive  ...  Astronomy and the search for fundamental particles at the Large Hadron Collider drive mainstream aspects of data-intensive science with many petabytes of data derived from large advanced instruments.  ...  Finally we would like to thank the editors of Distributed and Parallel Databases for providing us an opportunity to bring this special issue to the research community.  ... 
doi:10.1007/s10619-012-7107-1 fatcat:s3yzixkgprfm5cbijcxzyziuem

Cloud computing in e-Science: research challenges and opportunities

Xiaoyu Yang, David Wallom, Simon Waddington, Jianwu Wang, Arif Shaon, Brian Matthews, Michael Wilson, Yike Guo, Li Guo, Jon D. Blower, Athanasios V. Vasilakos, Kecheng Liu (+1 others)
2014 Journal of Supercomputing  
While the emergence of Cloud computing as a new computing paradigm has provided new directions and opportunities for e-Science infrastructure development, it also presents some challenges.  ...  Such challenges demonstrate the need for a comprehensive analysis on using the above mentioned informatics techniques to develop appropriate e-Science infrastructure and platforms in the context of Cloud  ...  Acknowledgements We thank the anonymous reviewers for their constructive and insightful suggestions.  ... 
doi:10.1007/s11227-014-1251-5 fatcat:ribdemcam5coxmwoloszbc54ne

From distribution networks to smart distribution systems: Rethinking the regulation of European electricity DSOs

Sophia Ruester, Sebastian Schwenen, Carlos Batlle, Ignacio Pérez-Arriaga
2014 Utilities Policy  
Distributed energy resources allow for new business models that have the potential to substantially change today's power system functioning paradigm.  ...  In particular, these changes pose challenges for distribution system operators (DSOs) and their regulation alike.  ...  Emerging business models challenge DSO regulation The large-scale introduction of distributed energy resources will be made possible e and also reinforced e by new evolving business models.  ... 
doi:10.1016/j.jup.2014.03.007 fatcat:h3zbuhm6nngufdi2vjd3te3fpe

Flat-Land Large-Scale Electricity Storage (FLES)

J. Huynen, R. Schalij, T. Arts
2012 EPJ Web of Conferences  
Growth of renewable sources requires a smarter electricity grid, integrating multiple solutions for large scale storage. Pumped storage still is the most valid option.  ...  New locations for additional pumped storage capacity are scarce. Mountainous areas mostly are remote and do not allow construction of large facilities for ecological reasons.  ...  Introduction This paper introduces a new, innovative, large-scale electricity storage system, which is based on proven technology.  ... 
doi:10.1051/epjconf/20123304010 fatcat:hk5vp3j3ijfcbmuywmwjhefbbi

Collaborative Scientific Workflows

Shiyong Lu, Jia Zhang
2009 2009 IEEE International Conference on Web Services  
In recent years, a number of scientific workflow management systems (SWFMSs) have been developed to help domain scientists synergistically integrate distributed computations, datasets, and analysis tools  ...  the storage of workflow evolution provenance [5] .  ...  A second challenge is how to capture, manage, and utilize large amounts of distributed, heterogeneous, multi-level, and collaborative provenance data for the reproducibility of scientific results produced  ... 
doi:10.1109/icws.2009.150 dblp:conf/icws/LuZ09 fatcat:uixs7xfwond7ncnairul5yheje

Study of next-generation infrastructure: InfiniBand HPC grid computing for telecommunications data center

Gyankamal Chhajed, Santosh Shinde, Rahul Jagtap, Venkatesh Raskotwar
2010 2010 3rd International Conference on Computer Science and Information Technology  
Grid computing originates in e-Science and its early development was driven to a large extent by the requirements of large-scale computing and efficient sharing of huge datasets. e-Business requirements  ...  led to the adoption of emerging Web services technologies-initially developed for distributed business application integration.  ...  InfiniBand has proven the ideal interconnect to scale out industry standard servers to tackle business computing problems that demand high levels of performance, reliability, and cost-effectiveness [10  ... 
doi:10.1109/iccsit.2010.5564782 fatcat:oauugkslzfgsdlu2yzhjn4drde

The future of scientific workflows

Ewa Deelman, Tom Peterka, Ilkay Altintas, Christopher D Carothers, Kerstin Kleese van Dam, Kenneth Moreland, Manish Parashar, Lavanya Ramakrishnan, Michela Taufer, Jeffrey Vetter
2017 The international journal of high performance computing applications  
tool for extreme-scale science.  ...  We highlight use cases, computing systems, workflow needs and conclude by summarizing the remaining challenges this community sees that inhibit large-scale scientific workflows from becoming a mainstream  ...  Acknowledgments The authors would like to thank all workshop participants for their contributions: Greg Abram, Gagan Agrawal, James  ... 
doi:10.1177/1094342017704893 fatcat:wkqlq7kzlnfx7acppift6ot4u4
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