Skip to main content
SpringerLink
Log in
Book cover

Latin American High Performance Computing Conference

CARLA 2015: High Performance Computing pp 73–86Cite as

Improvements to Super-Peer Policy Communication Mechanisms

  • Conference paper
  • First Online:

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 565))

Abstract

The use of large distributed computing infrastructures has become a fundamental component in most of scientific and technological projects. Due to its highly distributed nature, one of the key topics to be addressed in large distributed systems (like Grids and Federation of Clouds) is the determination of the availability and state of resources. Having up-to-date information about resources in the system is extremely important as this is consumed by the scheduler for selecting the appropriate target in each job to be served.

The way in which this information is obtained and distributed is what is known as Resource Information Distribution Policy. A centralized organization presents several drawbacks, for example, a single point of failure. Notwithstanding, the static hierarchy has become the defacto implementation of grid information systems.

There is a growing interest in the interaction with the Peer to Peer (P2P) paradigm, pushing towards scalable solutions. Super Peer Policy (SP) is a decentralized policy which presents a notable improvement in terms of response time and expected number of results compared with decentralization one. While Hierarchical policy is valuable for small and medium-sized Grids, SP is more effective in very large systems and therefore is more scalable.

In this work, we analyze SP focusing on the communication between super-peers. An improvement to the standard protocol is proposed which leads to two new SP policies outperforming the standard implementation: N-SP and A2A-SP. These policies are analyzed in terms of obtained performance in Exponential and Barabási network topologies, network consumption and scalability.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Albert, R., Jeong, H., Barabási, A.L.: Internet: diameter of the world-wide web. Nature 401, 130–131 (1999). http://adsabs.harvard.edu/abs/1999Natur.401.130A

    Article  Google Scholar 

  2. Assunção, M.D., Calheiros, R.N., Bianchi, S., Netto, M.A., Buyya, R.: Big data computing and clouds: trends and future directions. J. Parallel Distrib. Comput. 79, 3–15 (2014). http://www.sciencedirect.com/science/article/pii/S0743731514001452, Special issue on Scalable Systems for Big Data Management and Analytics

    Google Scholar 

  3. Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  4. Casanova, H., Legrand, A., Quinson, M.: SimGrid: a generic framework for large-scale distributed experiments. In: 10th IEEE International Conference on Computer Modeling and Simulation, pp. 126–131. IEEE Computer Society, Los Alamitos, March 2008

    Google Scholar 

  5. Cesario, E., Mastroianni, C., Talia, D.: Distributed volunteer computing for solving ensemble learning problems. Future Gener. Comput. Syst. (2015, in press). http://www.sciencedirect.com/science/article/pii/S0167739X15002332

  6. Ergu, D., Kou, G., Peng, Y., Shi, Y., Shi, Y.: The analytic hierarchy process: task scheduling and resource allocation in cloud computing environment. J. Supercomput. 64(3), 835–848 (2013)

    Article  Google Scholar 

  7. Foster, I., Zhao, Y., Raicu, I., Lu, S.: Cloud computing and grid computing 360-degree compared. In: 2008 Grid Computing Environments Workshop, GCE 2008, pp. 1–10, November 2008

    Google Scholar 

  8. Foster, I., Kesselman, C.: The Grid 2: Blueprint for a New Computing Infrastructure. The Morgan Kaufmann Series in Computer Architecture and Design. Morgan Kaufmann Publishers Inc., San Francisco (2003)

    Google Scholar 

  9. Foster, I., Kesselman, C., Tuecke, S.: The anatomy of the grid: enabling scalable virtual organizations. Int. J. High Perform. Comput. Appl. 15(3), 200–222 (2001). http://portal.acm.org/citation.cfm?id=1080667

    Article  Google Scholar 

  10. Ghafarian, T., Deldari, H., Javadi, B., Yaghmaee, M.H., Buyya, R.: Cycloidgrid: a proximity-aware P2P-based resource discovery architecture in volunteer computing systems. J. Future Gener. Comput. Syst. 29(6), 1583–1595 (2013). http://www.sciencedirect.com/science/article/pii/S0167739X12001665, Including Special sections: High Performance Computing in the Cloud & Resource Discovery Mechanisms for P2P Systems

    Article  Google Scholar 

  11. Iamnitchi, A., Foster, I., Nurmi, D.: A peer-to-peer approach to resource discovery in grid environments. In: Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing HPDC-11 (HPDC 2002), p. 419. IEEE, Edinbourgh, July 2002

    Google Scholar 

  12. Iamnitchi, A., Foster, I.: A peer-to-peer approach to resource location in Grid environments. In: Grid Resource Management: State of the Art and Future Trends, pp. 413–429. Kluwer Academic Publishers, Norwell (2004)

    Google Scholar 

  13. Karypis, G., Kumar, V.: A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM J. Sci. Comput. 20(1), 359–392 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  14. Liu, W., Nishio, T., Shinkuma, R., Takahashi, T.: Adaptive resource discovery in mobile cloud computing. Comput. Commun. 50, 119–129 (2014). http://www.sciencedirect.com/science/article/pii/S0140366414000590, Green Networking

    Article  Google Scholar 

  15. Márquez, D.G., Mocskos, E.E., Slezak, D.F., Turjanski, P.G.: Simulation of resource monitoring and discovery in grids. In: Proceedings of HPC 2010 High-Performance Computing Symposium, pp. 3258–3270 (2010). http://www.39jaiio.org.ar/node/121

  16. Mastroianni, C., Talia, D., Verta, O.: A super-peer model for resource discovery services in large-scale Grids. Future Gener. Comput. Syst. 21(8), 1235–1248 (2005). http://www.sciencedirect.com/science/article/pii/S0167739X05000701

    Article  Google Scholar 

  17. Mastroianni, C., Talia, D., Verta, O.: Designing an information system for Grids: comparing hierarchical, decentralized P2P and super-peer models. Parallel Comput. 34(10), 593–611 (2008)

    Article  Google Scholar 

  18. Mattmann, C., Garcia, J., Krka, I., Popescu, D., Medvidovic, N.: Revisiting the anatomy and physiology of the grid. J. Grid Comput. 13(1), 19–34 (2015)

    Article  Google Scholar 

  19. Mocskos, E.E., Yabo, P., Turjanski, P.G., Fernandez Slezak, D.: Grid matrix: a grid simulation tool to focus on the propagation of resource and monitoring information. Simul-T Soc. Mod. Sim. 88(10), 1233–1246 (2012)

    Google Scholar 

  20. Pipan, G.: Use of the TRIPOD overlay network for resource discovery. Future Gener. Comput. Syst. 26(8), 1257–1270 (2010). http://www.sciencedirect.com/science/article/pii/S0167739X1000018X

    Article  Google Scholar 

  21. Plale, B., Jacobs, C., Jensen, S., Liu, Y., Moad, C., Parab, R., Vaidya, P.: Understanding Grid resource information management through a synthetic database benchmark/workload. In: CCGRID 2004: Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid, pp. 277–284. IEEE Computer Society, Washington, April 2004

    Google Scholar 

  22. Puppin, D., Moncelli, S., Baraglia, R., Tonellotto, N., Silvestri, F.: A grid information service based on peer-to-peer. In: Cunha, J.C., Medeiros, P.D. (eds.) Euro-Par 2005. LNCS, vol. 3648, pp. 454–464. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  23. Ranjan, R., Harwood, A., Buyya, R.: Peer-to-peer-based resource discovery in global grids: a tutorial. IEEE Commun. Surv. Tut. 10(2), 6–33 (2008)

    Article  Google Scholar 

  24. Ranjan, R., Zhao, L.: Peer-to-peer service provisioning in cloud computing environments. J Supercomput. 65(1), 154–184 (2013)

    Article  Google Scholar 

  25. Ripeanu, M.: Peer-to-peer architecture case study: Gnutella network. In: 2001 Proceedings of the First International Conference on Peer-to-Peer Computing, pp. 99–100, August 2001

    Google Scholar 

  26. Shiers, J.: The worldwide LHC computing grid (worldwide LCG). Comput. Phys. Commun. 177(1–2), 219–223 (2007)

    Article  Google Scholar 

  27. Trunfio, P., Talia, D., Papadakis, C., Fragopoulou, P., Mordacchini, M., Pennanen, M., Popov, K., Vlassov, V., Haridi, S.: Peer-to-Peer resource discovery in Grids: models and systems. Future Gener. Comput. Syst. 23(7), 864–878 (2007)

    Article  Google Scholar 

  28. Williams, D.N., Drach, R., Ananthakrishnan, R., Foster, I., Fraser, D., Siebenlist, F., Bernholdt, D., Chen, M., Schwidder, J., Bharathi, S., et al.: The earth system grid: enabling access to multimodel climate simulation data. Bull. Am. Meteorol. Soc. 90(2), 195–205 (2009)

    Article  Google Scholar 

Download references

Acknowledgments

E.M. is researcher of the CONICET. This work was partially supported by grants from Universidad de Buenos Aires (UBACyT 20020130200096BA) and CONICET (PIP 11220110100379).

Author information

Authors and Affiliations

  1. Laboratorio de Sistemas Complejos, Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, C1428EGA, Buenos Aires, Argentina

    Paula Verghelet & Esteban Mocskos

  2. Centro de Simulación Computacional p/Aplic. Tecnológicas/CSC-CONICET, Godoy Cruz 2390, C1425FQD, Buenos Aires, Argentina

    Esteban Mocskos

Authors
  1. Paula Verghelet
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Esteban Mocskos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Esteban Mocskos .

Editor information

Editors and Affiliations

  1. LNCC, National Laboratory for Scientific Computing, Rio de Janeiro, Brazil

    Carla Osthoff

  2. Instituto de Informática, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

    Philippe Olivier Alexandre Navaux

  3. High Performance and Scientific Computing Center, Universidad Industrial de Santander, Bucaramanga, Chile

    Carlos Jaime Barrios Hernandez

  4. LNCC, National Laboratory for Scientific Computing, Rio de Janeiro, Brazil

    Pedro L. Silva Dias

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Verghelet, P., Mocskos, E. (2015). Improvements to Super-Peer Policy Communication Mechanisms. In: Osthoff, C., Navaux, P., Barrios Hernandez, C., Silva Dias, P. (eds) High Performance Computing. CARLA 2015. Communications in Computer and Information Science, vol 565. Springer, Cham. https://doi.org/10.1007/978-3-319-26928-3_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-26928-3_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26927-6

  • Online ISBN: 978-3-319-26928-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation