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Transactions on Computational Science XXIX pp 97–120Cite as

Processing Large Geometric Datasets in Distributed Environments

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Part of the book series: Lecture Notes in Computer Science ((TCOMPUTATSCIE,volume 10220))

Abstract

We describe an innovative Web-based platform to remotely perform complex geometry processing on large triangle meshes. A graphical user interface allows combining available algorithms to build complex pipelines that may also include conditional tasks and loops. The execution is managed by a central engine that delegates the computation to a distributed network of servers and handles the data transmission. The overall amount of data that is flowed through the net is kept within reasonable bounds thanks to an innovative mesh transfer protocol. A novel distributed divide-and-conquer approach enables parallel processing by partitioning the dataset into subparts to be delivered and handled by dedicated servers. Our approach can be used to process an arbitrarily large mesh represented either as a single large file or as a collection of files possibly stored on geographically scattered servers. To prove its effectiveness, we exploited our platform to implement a distributed simplification algorithm which exhibits a significant flexibility, scalability and speed.

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Acknowledgements

This work is partly supported by the EU FP7 Project no. ICT–2011-318787 (IQmulus) and by the international joint project on Mesh Repairing for 3D Printing Applications funded by Software Architects Inc (WA, USA). The authors are grateful to all the colleagues at IMATI for the helpful discussions.

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Authors and Affiliations

  1. CNR-IMATI, Genova, Italy

    Daniela Cabiddu & Marco Attene

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  1. Daniela Cabiddu
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  2. Marco Attene
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Correspondence to Daniela Cabiddu .

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Editors and Affiliations

  1. University of Calgary , Calgary, Alberta, Canada

    Marina L. Gavrilova

  2. Sardina Systems , Tallinn, Estonia

    C.J. Kenneth Tan

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Cabiddu, D., Attene, M. (2017). Processing Large Geometric Datasets in Distributed Environments. In: Gavrilova, M., Tan, C. (eds) Transactions on Computational Science XXIX. Lecture Notes in Computer Science(), vol 10220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54563-8_6

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  • DOI: https://doi.org/10.1007/978-3-662-54563-8_6

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  • Print ISBN: 978-3-662-54562-1

  • Online ISBN: 978-3-662-54563-8

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