Advertisement

Theory of Computing Systems

, Volume 57, Issue 2, pp 444–477 | Cite as

Enhancing the Computation of Distributed Shortest Paths on Power-law Networks in Dynamic Scenarios

  • Gianlorenzo D’Angelo
  • Mattia D’Emidio
  • Daniele Frigioni
  • Daniele Romano
Article

Abstract

The problem of finding and keeping updated shortest paths in distributed networks is considered crucial in today’s practical applications. In the recent past, there has been a renewed interest in devising new efficient distance-vector algorithms as an attractive alternative to link-state solutions for large-scale Ethernet networks, in which scalability and reliability are key issues or the nodes can have limited storage capabilities. In this paper, we present Distributed Computation Pruning (DCP), a new technique, which can be combined with every distance-vector routing algorithm based on shortest paths, allowing to reduce the total number of messages sent by that algorithm and its space occupancy per node. To check its effectiveness, we combined the new technique with DUAL (Diffuse Update ALgorithm), one of the most popular distance-vector algorithm in the literature, which is part of CISCO’s widely used EIGRP protocol, and with the recently introduced LFR (Loop Free Routing) which has been shown to have good performances on real networks. We give experimental evidence that these combinations lead to a significant gain both in terms of number of messages sent and of memory requirements per node.

Keywords

Design and analysis of algorithms Computer communication networks Distributed algorithms Dynamic algorithms Shortest paths Experimental analysis 

References

  1. 1.
    Albert, R., Barabási, A.-L.: Emergence of scaling in random networks. Science 286, 509–512 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Attiya, H., Welch, J.: Distributed Computing. Wiley, New York (2004)CrossRefGoogle Scholar
  3. 3.
    Awerbuch, B., Bar-Noy, A., Gopal, M.: Approximate distributed bellman-ford algorithms. IEEE Trans. Commun. 42(8), 2515–2517 (1994)CrossRefGoogle Scholar
  4. 4.
    Bertsekas, D., Gallager, R.: Data Networks. Prentice Hall International, Upper Saddle River (1992)zbMATHGoogle Scholar
  5. 5.
    Bu, T., Towsleym, D.: On distinguishing between internet power law topology generators. In: Proceedings 21st Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM2002) IEEE , pp 37–48 (2002)Google Scholar
  6. 6.
    Cicerone, S., D’Angelo, G., Di Stefano, G., Frigioni, D.: Partially dynamic efficient algorithms for distributed shortest paths. Theor. Comput. Sci. 411, 1013–1037 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Cicerone, S., D’Angelo, G., Di Stefano, G., Frigioni, D., Maurizio, V.: Engineering a new algorithm for distributed shortest paths on dynamic networks. Algorithmica 66(1), 51–86 (2013)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Cicerone, S., Stefano, G.D., Frigioni, D., Nanni, U.: A fully dynamic algorithm for distributed shortest paths. Theor. Comput. Sci. 297(1-3), 83–102 (2003)CrossRefzbMATHGoogle Scholar
  9. 9.
    D’Angelo, G., D’Emidio, M., Frigioni, D.: Pruning the computation of distributed shortest paths in power-law networks. Informatica 37(3), 253–265 (2013)MathSciNetGoogle Scholar
  10. 10.
    D’Angelo, G., D’Emidio, M., Frigioni, D.: A loop-free shortest-path routing algorithm for dynamic networks. Theor. Comput. Sci. 516, 1–19 (2014)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    D’Angelo, G., D’Emidio, M., Frigioni, D., Romano, D.: Enhancing the computation of distributed shortest paths on real dynamic networks. In: Proceedings 1st Mediterranean Conference on Algorithms (MEDALG2012), volume 7659 of Lecture Notes in Computer Science, pp 148–158 (2012)Google Scholar
  12. 12.
    Elmeleegy, K., Cox, A.L., Ng, T.S.E.: On count-to-infinity induced forwarding loops in ethernet networks. In: Proceedings 25th IEEE Conference on Computer Communications (INFOCOM2006), pp 1–13 (2006)Google Scholar
  13. 13.
    Frigioni, D., Marchetti-Spaccamela, A., Nanni, U.: Fully dynamic algorithms for maintaining shortest paths trees. J. Algorithm. 34(2), 251–281 (2000)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Garcia-Lunes-Aceves, J.J.: Loop-free routing using diffusing computations. IEEE/ACM Trans. Netw. 1(1), 130–141 (1993)CrossRefGoogle Scholar
  15. 15.
    Humblet, P.A.: Another adaptive distributed shortest path algorithm. IEEE Trans. Commun. 39(6), 995–1002 (1991)CrossRefzbMATHGoogle Scholar
  16. 16.
    Hyun, Y., Huffaker, B., Andersen, D., Aben, E., Shannon, C., Luckie, M., Claffy, K.: The CAIDA IPv4 routed/24 topology dataset. http://www.caida.org/data/active/ipv4_routed_24_topology_dataset.xml.
  17. 17.
    Italiano, G.F.: Distributed algorithms for updating shortest paths. In: International Workshop on Distributed Algorithms, volume 579 of Lecture Notes in Computer Science, pp 200–211 (1991)Google Scholar
  18. 18.
    McQuillan, J.: Adaptive Routing Algorithms for Distributed Computer Networks. Technical Report BBN Report 2831. Cambridge, MA (1974)Google Scholar
  19. 19.
    Moy, J.T.: OSPF: Anatomy of an Internet routing protocol. Addison-Wesley, Reading (1998)Google Scholar
  20. 20.
    Myers, A., Ng, E., Zhang, H.: Rethinking the service model: Scaling ethernet to a million nodes. In: Proceedings 3rd Workshop on Hot Topics in Networks (ACM HotNets). ACM Press (2004)Google Scholar
  21. 21.
    Narváez, P., Siu, K.-Y., Tzeng, H.-Y.: New dynamic algorithms for shortest path tree computation. IEEE/ACM Trans. Netw. 8(6), 734–746 (2000)CrossRefGoogle Scholar
  22. 22.
    OMNeT ++: Discrete event simulation environment. http://www.omnetpp.org.
  23. 23.
    Orda, A., Rom, R.: Distributed shortest-path and minimum-delay protocols in networks with time-dependent edge-length. Distrib. Comput. 10, 49–62 (1996)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Pahlavan, K., Krishnamurthy, P.: Networking Fundamentals: Wide, Local and Personal Area Communications. Wiley, New York (2009)CrossRefGoogle Scholar
  25. 25.
    Ramarao, K.V.S., Venkatesan, S.: On finding and updating shortest paths distributively. J. Algorithm. 13, 235–257 (1992)MathSciNetCrossRefzbMATHGoogle Scholar
  26. 26.
    Ray, S., Guérin, R., Kwong, K.-W., Sofia, R.: Always acyclic distributed path computation. IEEE/ACM Trans. Netw. 18(1), 307–319 (2010)CrossRefGoogle Scholar
  27. 27.
    Rosen, E.C.: The updating protocol of arpanet’s new routing algorithm. Comput. Netw. 4, 11–19 (1980)Google Scholar
  28. 28.
    Wu, J., Dai, F., Lin, X., Cao, J., Jia, W.: An extended fault-tolerant link-state routing protocol in the internet. IEEE Trans. Comp. 52(10), 1298–1311 (2003)CrossRefGoogle Scholar
  29. 29.
    Yao, N., Gao, E., Qin, Y., Zhang, H.: Rd: Reducing message overhead in DUAL. In: Proceedings 1st International Conference on Network Infrastructure and Digital Content (IC-NIDC2009), IEEE Press, pp 270–274 (2009)Google Scholar
  30. 30.
    Zhao, C., Liu, Y., Liu, K.: A more efficient diffusing update algorithm for loop-free routing. In: Proceedings 5th International Conference on Wireless Communications, Networking and Mobile Computing (WiCom2009), IEEE Press, pp 1–4 (2009)Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Gianlorenzo D’Angelo
    • 1
  • Mattia D’Emidio
    • 2
  • Daniele Frigioni
    • 2
  • Daniele Romano
    • 3
  1. 1.Gran Sasso Science Institute (GSSI)L’AquilaItaly
  2. 2.Department of Information Engineering, Computer Science and MathematicsUniversity of L’AquilaL’AquilaItaly
  3. 3.Department of Industrial and Information Engineering and EconomicsUniversity of L’AquilaL’AquilaItaly

Personalised recommendations