Lightweight Monitoring of the Progress of Remotely Executing Computations

  • Shuo Yang
  • Ali R. Butt
  • Y. Charlie Hu
  • Samuel P. Midkiff
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4339)


The increased popularity of grid systems and cycle sharing across organizations requires scalable systems that provide facilities to locate resources, to be fair in the use of those resources, and to monitor jobs executing on remote systems. This paper presents a novel and lightweight approach to monitoring the progress and correctness of a parallel computation on a remote, and potentially fraudulent, host system. We describe a monitoring system that uses a sequence of program counter values to monitor program progress, and compiler techniques that automatically generate the monitoring code. This approach improves on earlier work by omitting the need to duplicate computation, which both simplifies and reduces the overhead of monitoring. Our approach allows dynamic and accountable cycle-sharing across the Internet. Experimental results show that the overhead of our system is negligible and our monitoring approach is scalable.


Replay Attack Program Counter Host Machine Cycle Sharing Beacon Packet 
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.


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  1. 1.
    Genome@home: Genome at home (December 16, 2004),
  2. 2.
    SETI@home: Search for extraterrestrial intelligence at home (December 16, 2004),
  3. 3.
    David, A.P.: BOINC:A System for Public-Resource Computing and Storage. In: Proc. 5th IEEE/ACM International Workshop on Grid Computing (2004)Google Scholar
  4. 4.
    Litzkow, M., Livny, M., Mutka, M.: Condor - A Hunter of Idle Workstations. In: Proc. 8th International Conference on Distributed Computing Systems, ICDCS 1988 (1988)Google Scholar
  5. 5.
    Kannan, S., Roberts, M., Mayes, P., Brelsford, D., Skovira, J.F.: Workload Management with LoadLeveler. IBM International Technical Support Organization (2001), (December 17, 2004), publication number SG24-6038-00
  6. 6.
    Butt, A.R., Fang, X., Hu, Y.C., Midkiff, S.: Java, Peer-to-Peer, and Accountability: Building Blocks for Distributed Cycle Sharing. In: Proc. of VM 2004 (2004)Google Scholar
  7. 7.
    Castro, M., Druschel, P., Hu, Y.C., Rowstron, A.: Exploiting Network Proximity in Distributed Hash Tables. In: International Workshop on Future Directions in Distributed Computing (2002)Google Scholar
  8. 8.
    Lo, V., Zappala, D., Zhou, D., Liu, Y., Zhao, S.: Cluster Computing on the Fly: P2P Scheduling of Idle Cycles in the Internet. In: Proc. of IPTPS 2004 (2004)Google Scholar
  9. 9.
    Minchew, C.H., Tai, K.C.: Experience with Porting the Portable C Compiler. In: ACM 1982: Proceedings of the ACM 1982 conference, New York, NY, USA (1982)Google Scholar
  10. 10.
    PARISC-Linux: The PARISC-Linux Cross Compiler HOWTO (March 16, 2005),
  11. 11.
    Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the Art of Virtualization. In: Proc. of SOSP 2003 (2003)Google Scholar
  12. 12.
    Kamp, P.H., N.M. Watson, R.: Jails: Confining the Omnipotent Root. In: Proceedings of SANE 2000 Conference (2000)Google Scholar
  13. 13.
    Miller, B.P., Christodorescu, M., Iverson, R., Kosar, T., Mirgorodskii, A., Popovici, F.: Playing Inside the Black Box: Using Dynamic Instrumentation to Create Security Holes. In: Proceedings of 2nd Los Alamos Computer Science Institute Symposium (2001)Google Scholar
  14. 14.
    Yang, S., Butt, A.R., Hu, Y.C., Midkiff, S.P.: Trust but Verify: Monitoring Remotely Executing Programs for Progress and Correctness. In: Proc. of PPOPP 2005 (2005)Google Scholar
  15. 15.
    Linn, C., Debray, S.: Obfuscation of Executable Code to Improve Resistance to Static Disassembly. In: Proc. of CCS 2003 (2003)Google Scholar
  16. 16.
    Bailey, D., Barszcz, E., Barton, J., Browning, D., Carter, R., Dagum, L., Fatoohi, R., Fineberg, S., Frederickson, P., Lasinski, T., Schreiber, R., Simon, H., Venkatakrishnan, V., Weeratunga, S.: The NAS Parallel Benchmarks. Technical Report NAS Technical Report RNR-94-007, NASA Ames Center (1994)Google Scholar
  17. 17.
    Sarmenta, L.F.: Sabotage Tolerance Mechanism for Volunteer Computing Systems. In: CCGrid 2001 (2001)Google Scholar
  18. 18.
    Du, W., Jia, J., Mangal, M., Murugesan, M.: Uncheatable Grid Computing. In: Proceedings of the 24th International Conference on Distributed Computing Systems, ICDCS 2004 (2004)Google Scholar
  19. 19.
    Hofmeyr, S.A., Forrest, S., Somayaji, A.: Intrusion detection using sequences of system calls. Journal of Computer Security 6 (1998)Google Scholar
  20. 20.
    Chen, H., Wagner, D.: MOPS: an Infrastructure for Examining Security Properties of Software. In: Proc. of CCS 2002 (2002)Google Scholar
  21. 21.
    Foster, I., Roy, A., Sander, V.: A Quality of Service Architecture that Combines Resource Reservation and Application Adaptation. In: Proc. 8th International Workshop on Quality of Service (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shuo Yang
    • 1
  • Ali R. Butt
    • 1
  • Y. Charlie Hu
    • 1
  • Samuel P. Midkiff
    • 1
  1. 1.School of Electrical and Computer EngineeringPurdue UniversityWest LafayetteUSA

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