Advertisement

An Error Detection-Recovery Agent for Multimedia Distance System Based on Intelligent Context-Awareness: EDRA_RCSM

  • SoonGohn Kim
  • Eung Nam Ko
Part of the Communications in Computer and Information Science book series (CCIS, volume 199)

Abstract

The focus of multimedia education system has increased lately. In this paper, we will first explain an error detection-recovery agent for multimedia distance education system based on RCSM (Reconfigurable Context-Sensitive Middleware). DOORAE is a good example for developing multimedia distance education system based on RCSM between students and teachers during lecture. The development of multimedia computers and communication techniques has made it possible for a mind to be transmitted from a teacher to a student in distance environment. This method detects error by using process database periodically to find some error based on RCSM. If error is found, this paper took the first steps towards learning to coordinate actions in multi-agent systems based on RCSM for classifying the type of errors. If an error is to be recovered, this system uses the same method as it creates a session. EDRA_RCSM is a system that is suitable for detecting and recovering software error for multimedia distance education system based on RCSM by using software techniques.

Keywords

multimedia distance education system RCSM DOORAE detecting and recovering software error EDRA_RCSM 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Yau, S., Karim, F., Wang, Y., Wang, B., Gupta, S.: Reconfigurable Context-Sensitive Middleware for Pervasive Computing. IEEE Pervasive Computing 1(3), 33–40 (2002)CrossRefGoogle Scholar
  2. 2.
    Yau, S.S., Karim, F.: Adaptive Middleware for Ubiquitous Computing Environments. In: Design and Analysis of Distributed Embedded Systems, Proc. IFIP 17th WCC, August 2002, vol. 219, pp. 131–140 (2002)Google Scholar
  3. 3.
    Yau, S.S., Karim, F.: Contention-Sensitive Middleware for Real-time Software in Ubiquitous Computing Environments. In: Proc. 4th IEEE Int’l Symp. on Object-Oriented Real-time Distributed Computing (ISORC 2001), May 2001, pp. 163–170 (2001)Google Scholar
  4. 4.
    Ahn, J.Y., Lee, G.m., Park, G.C., Hwang, D.J.: An implementation of Multimedia Distance Education System Based on Advanced Multi-point Communication Service Infrastructure: DOORAE. In: Proceedings of the IASTED International Conference Parallel and Distributed Computing and Systems, Chicago, Illinois, USA, October 16-19 (1996)Google Scholar
  5. 5.
    Fluckiger, F.: Understanding Networked Multimedia-Application and Technology. Prentice Hall Inc., Herfordshire(UK) (1995)Google Scholar
  6. 6.
    Loftus, C.W., Sherratt, E.M., Gautier, R.J., Grandi, P.A.M., Price, D.E., Tedd, M.D.: Distributed Software Engineering-The Practitioner Series. Prentice Hall Inc., Herfordshire (1995)Google Scholar
  7. 7.
    ITU-T Recommendation T.122 Multipoint Communication Service for Audiographics and Audiovisual Conferencing Service Definition, ITU-T SG8 Interim Meeting (October 18, 1994), mertlesham, (issued March 14,1995) Google Scholar
  8. 8.
    Selfridge, O.G.: Pandemonium: a paradigm for learning. In: Proceedings of the Symposium on Mechanisation of Thought Processes, pp. 511–529. Her Majesty’s Stationary Office, London (1959)Google Scholar
  9. 9.
    Minsky, M.: The society theory of thinking. In: Artificial Intelligence: an MIT perspective, pp. 423–450. MIT Press, Redmond (1979)Google Scholar
  10. 10.
    Erman, L.D., Lesser, V.E.: A multi-level organization for problem-solving using many, diverse, cooperating sources of knowledge. In: Proceedings of the 1975 International Joint Conference on Artificial Intelligence, pp. 483–490 (1975)Google Scholar
  11. 11.
    Hewitt, C.E.: Viewing control structures as pattern of passing messages. In: Artificial intelligence, pp. 323–364 (1977)Google Scholar
  12. 12.
    Bond, A.H., Gasser, L. (eds.): Readings in distributed artificial intelligence. Morgan Kaufmann, San Francisco (1988)Google Scholar
  13. 13.
    Huhns, M.N. (ed.): Distributed artificial intelligence. Pitman (1987)Google Scholar
  14. 14.
    Weiβ, G.: Learning to Coordinate Actions in Multi-Agent Systems, pp. 481–486. Morgan Kaufmann Publishers, San Francisco (1998)Google Scholar
  15. 15.
    Agnew, P.W., Kellerman, A.S.: Distributed Multimedia. ACM Press, New York (1996)Google Scholar
  16. 16.
    Yau, S., Karim, F., Wang, Y., Wang, B., Gupta, S.: Reconfigurable Context-Sensitive Middleware for Pervasive Computing. IEEE Pervasive Computing 1(3), 33–40 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • SoonGohn Kim
    • 1
  • Eung Nam Ko
    • 2
  1. 1.Division of Computer and Game ScienceJoongbu UniversityGumsanGunKorea
  2. 2.Division of Information & CommunicationBaekseok UniversityCheonanKorea

Personalised recommendations