Advertisement

Self-organizing Monitoring Agents for Hierarchical Event Correlation

  • Bin Zhang
  • Ehab Al-Shaer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4785)

Abstract

Hierarchical event correlation is very important for distributed monitoring network and distributed system operations. In many large-scale distritbuted monitoring environments such as monitions senor networks for data aggregation, battlefield compact operations, and security events, an efficient hierarchical monitoring agent architecture must be constructed to facilitate event reporting and correlation utilizing the spacial relation between events and agents with minimum delay and cost in the network. However, due to the significant agent communication and management overhead in organzine agents in distributed monitoring, many of the existing approaching become inefficient or hard to deploy. In this paper, we propose a topology-aware hierarchical agent architecture construction technique that minimizes the monitoring cost while considering the underlying network topology and agent capabilities. The agent architecture construction is performed in a purely decentralized fashion based on the agents’ local knowledge with minimal communication and no central node support.

Keywords

Agent Architecture Beacon Message Enterprise Network Monitoring Agent Leader Candidate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Al-Shaer, E., Abdel-Wahab, H., Maly, K.: HiFi: A New Monitoring Architecture for Distributed System Management. In: ICDCS 1999. Proceedings of International Conference on Distributed Computing Systems, Austin, TX, pp. 171–178 (May 1999)Google Scholar
  2. 2.
    Zhang, B., Al-Shaer, E.: Self-Organizing Monitoring Agents for Hierarchical Monitoring Architecture. Technical Report, multimedia research lab, Depaul University (2007)Google Scholar
  3. 3.
    Carzaniga, A., Rosenblum, D.S., Wolf, A.L.: Design and evaluation of a wide-area event notification service. ACM Transactions on Computer Systems (TOCS) 19(3) (August 2001)Google Scholar
  4. 4.
    Baker, M., Smith, G.: GridRM: An Extensible Resource Monitoring System. In: CLUSTER 2003. Proceedings of the 5th IEEE Cluster Computing Conference, Hong Kong (December 2003)Google Scholar
  5. 5.
    Fei, A., Pei, G., Liu, R., Zhang, L.: Measurements on Delay and Hop-Count of the Internet. In: Proc. IEEE GLOBECOM 1998 Internet Mini-Conf., IEEE Computer Society Press, Los Alamitos (1998)Google Scholar
  6. 6.
    Gruber, R.E.: Balachander Krishnamurthy and Euthimios Panagos: High-level constructs in the READY event notification system. In: Proceedings of the 8th ACM SIGOPS European workshop on Support for composing distributed applications, Sintra, Portugal (1998)Google Scholar
  7. 7.
    Carzaniga, A., Rosenblum, D.S., Wolf, A.L.: Design and evaluation of a wide-area event notification service. ACM Transactions on Computer Systems (TOCS) 19(3) (August 2001)Google Scholar
  8. 8.
    Gruber, R.E., Krishnamurthy, B., Panagos, E.: High-level constructs in the READY event notification system. In: Proceedings of the 8th ACM SIGOPS European workshop on Support for composing distributed applications, Sintra, Portugal (1998)Google Scholar
  9. 9.
    Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: An Application-Specific Protocol Architecture for Wireless Microsensor Networks. IEEE Transactions on Wireless Communications 1(4), 660–670 (2002)CrossRefGoogle Scholar
  10. 10.
    Truong, H.-L., Fahringer, T.: SCALEA-G: a Unified Monitoring and Performance Analysis System for the Grid. Technical report, Institute for Software Science, University of Vienna (October 2003)Google Scholar
  11. 11.
    Ratnasamy, S., Handley, M., Karp, R., Shenker, S.: Topologically-aware Overlay Construction and Server Selection. In: INFOCOM (2002)Google Scholar
  12. 12.
    Korupolu, M.R., Plaxton, C.G., Rajaraman, R.: Analysis of a Local Search Heuristic for Facility Location Problems. In: Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1–10. ACM Press, New York (1998)Google Scholar
  13. 13.
    Osman, I.H., Christofides, N.: Capacitated clustering problems by hybrid simulated annealing and tabu search. Transactions in Operational Research 1, 317–336 (1994)CrossRefzbMATHGoogle Scholar
  14. 14.
    Jain, K., Vazirani, V.: Primal-dual approximation algorithms for metric facility location and k-median problems. In: Proceeding of the 40th Annual IEEE Symposium on Foundation of Computer Science, pp. 1–10. IEEE Computer Society Press, Los Alamitos (1999)Google Scholar
  15. 15.
    Yemini, S.A., Kliger, S., Mozes, E., Yemini, Y., Ohsie, D.: High Speed and Robust Event Correlation. IEEE Communication Magazine, 433–450 (May 1996)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2007

Authors and Affiliations

  • Bin Zhang
    • 1
  • Ehab Al-Shaer
    • 1
  1. 1.School of Computer Science, Telecommunications and Information Systems, DePaul UniversityUSA

Personalised recommendations