LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Sloper, John Erik
Languages: English
Types: Doctoral thesis
Subjects: QA76
This thesis is concerned with the use of intelligent system techniques (IST) within\ud a large distributed software system, specifically the ATLAS TDAQ system which\ud has been developed and is currently in use at the European Laboratory for Particle\ud Physics(CERN). The overall aim is to investigate and evaluate a range of ITS\ud techniques in order to improve the error management system (EMS) currently used\ud within the TDAQ system via error detection and classification. The thesis work\ud will provide a reference for future research and development of such methods in the\ud TDAQ system.\ud The thesis begins by describing the TDAQ system and the existing EMS, with a\ud focus on the underlying expert system approach, in order to identify areas where\ud improvements can be made using IST techniques. It then discusses measures of\ud evaluating error detection and classification techniques and the factors specific to\ud the TDAQ system.\ud Error conditions are then simulated in a controlled manner using an experimental\ud setup and datasets were gathered from two different sources. Analysis and processing\ud of the datasets using statistical and ITS techniques shows that clusters exists in\ud the data corresponding to the different simulated errors.\ud Different ITS techniques are applied to the gathered datasets in order to realise an\ud error detection model. These techniques include Artificial Neural Networks (ANNs),\ud Support Vector Machines (SVMs) and Cartesian Genetic Programming (CGP) and\ud a comparison of the respective advantages and disadvantages is made.\ud The principle conclusions from this work are that IST can be successfully used to\ud detect errors in the ATLAS TDAQ system and thus can provide a tool to improve\ud the overall error management system. It is of particular importance that the IST can\ud be used without having a detailed knowledge of the system, as the ATLAS TDAQ\ud is too complex for a single person to have complete understanding of. The results\ud of this research will benefit researchers developing and evaluating IST techniques in\ud similar large scale distributed systems.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [10] Khomoutnikov, V., Barriuso A., Burckhart H., Subdetector Control Interaction with TDAQ Controls, ATL-DQ-EN-0027, July 2006 [11] Barriuso A., “FSM Integration Guidelines”, ATL/DQ/ON/0010, December 2005 [1] ATLAS Collaboration, "ATLAS High-Level Trigger, Data Acquisition and Controls Technical Design Report", - 2003-022, June 2003 [2] G. Ambrosini et al., "The RD13 Data Acquisition System", proceedings of the Computing in High Energy Physics conference, San Francisco, California, USA, 1994 [3] G.Ambrosin, et al., "The ATLAS DAQ and Event Filter Prototype "-1" Project", Computer Physics Communications 110, 1998, pp.95-102 [4] Maria Skiadelli, "Object Oriented database system evaluation for the DAQ system", diploma thesis, Patras Polytechnic School, Greece, March 1994 [5] R.Jones, L. Mapelli, Yu.Ryabov, I.Soloviev, "The OKS Persistent Inmemory Object Manager", IEEE Transactions on Nuclear Science, vol 45, No 4, Part 1, August, 1998, pp. 1958 - 1964 [6] Rogue Wave Software, Inc., "Tools.h++ Foundation Class Library for C++ programming", March 1996, for more information see URL http://www.roguewave.com/products/tools/tools.html [7] CORAL - COmmon Relational Abstraction Layer, a package of CERN LHC Computing Grid Project, see http:Hpool.cern.ch/coral/ [8] I. Alexandrov, A. Amorim, E. Badescu, D. Burckhart, M. Caprini, M.
    • Pedro, Y. Ryabov, I. Soloviev, "Experience with CORBA communication middleware in the ATLAS DAQ", proceedings of the Computing in High Energy Physics conference, Interlaken, Switzerland, 2004 [9] I. Alexandrov, A. Amorim, E. Badescu, M. Barczyk, D.BurckhartChromek, M. Caprini, J. Da Silva Conceicao, J. Flammer, B. Di Girolamo, M. Dobson, R. Hart, R. Jones, A. Kazarov, S. Kolos, V.
    • Pedro, Y. Ryabov, I. Soloviev, H. Wolters , "Online Software for the ATLAS Test Beam Data Acquisition System", proceedings of the 13th IEEE - NPSS Real Time Conference, Montreal, Canada, 2003 [10] S. Gadomski et al., "Deployment and use of the ATLAS DAQ in the Combined Test Beam", proceedings of the 14th IEEE - NPSS Real Time Conference, Stockholm, Sweden, 2005 [11] D. Burckhart-Chromek et al., "Testing on a Large Scale: running the ATLAS Data Acquisition and High Level Trigger Software on 700 PC Nodes", proceedings of the Computing in High Energy Physics conference, Mumbai, India, 2006 [12] L. Lueking, S. Kosyakov, J. Kowalkowski, D. Litvintsev, M. Paterno, S.White, B. Blumenfeld, P. Maksimovic, M. Mathis, "FroNtier: High Performance Database Access Using Standard Web Components in a Scalable Multi-tier Architecture", proceedings of the Computing in High Energy Physics conference, Interlaken, Switzerland, 2004
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article