1 / 14

Shrideep Pallickara, Jaliya Ekanayake, Geoffrey Fox Community Grids Lab Indiana University

Collaborative Analysis of Distributed Data Applied to Particle Physics Experiments. Shrideep Pallickara, Jaliya Ekanayake, Geoffrey Fox Community Grids Lab Indiana University. NaradaBrokering: Quick Summary. Content distribution infrastructure for data streams

hrankin
Download Presentation

Shrideep Pallickara, Jaliya Ekanayake, Geoffrey Fox Community Grids Lab Indiana University

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Collaborative Analysis of Distributed Data Applied to Particle Physics Experiments Shrideep Pallickara, Jaliya Ekanayake, Geoffrey Fox Community Grids Lab Indiana University

  2. NaradaBrokering: Quick Summary • Content distribution infrastructure for data streams • Framework for development of distributed systems • Funding Sources • Two grants from the National Science Foundation • Two grants from the United Kingdom’s OMII • Recent STTR grant from the Department of Energy • Code base specifics: Open Source, Version 3.1.2 • 300,000 lines, 1425 classes, 157 packages

  3. Stream dissemination: Highlights • Fine-grained selectivity within a stream • Regular Expressions, SQL, XQuery & XPath queries • Stream jitter reduction • Time-ordering of streams • Support for multiple transports • TCP, UDP, Multicast, SSL, HTTP, Parallel-TCP

  4. Information Assurance: Security • Restrict discovery of streams • Control who (and for how long) can generate & consume streams • Encrypt streams to prevent eavesdropping • Digitally sign streams to detect tampering • Cope with Denial of Service attacks

  5. Information Assurance: Fault Tolerance • Cope with node failures • Guaranteed delivery despite failures • Support for recovery from failures • Fine tune redundancy • Scalable tracking of resources within system

  6. Clarens • Secure, high-performance portal • Ubiquitous access to data & computational resources • Uses ROOT for analysis of particle physics data • Generated by the Compact Muon Solenoid (CMS) detector at CERN

  7. NB Clarens: Salient Features • Stand-alone application converted into a collaborative one • Participation predicated on authorization • No limits on number of participants • Data-driven distribution of computations

  8. Demo of Collaborative Analysis

  9. In the works • Dynamic real-time distribution and balancing of computation loads. • Incorporate monitoring services • Secure collaborative sessions • Streams within session will be encrypted • Streams will be digitally signed for tamper evidence

More Related