http://iet.metastore.ingenta.com
1887

Theoretical analysis for tree-like networks using random geometry

Theoretical analysis for tree-like networks using random geometry

For access to this article, please select a purchase option:

Buy article PDF
$19.95
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Among various network topologies, tree-like networks, also known as hierarchical networks are proposed to decrease the overhead of the routing table especially for the situation involving many network nodes. Usually, the routing table size and the routing complexity are the two crucial concerns in designing a large network. Although there have been various algorithms to optimise the routing strategies for the hierarchical networks, hardly exists any work in studying and evaluating the routing table size and the routing complexity rigorously in the statistical sense. In this study, the authors generalise a new mathematical framework by applying the point process in random geometry. The new framework proposed by the authors leads to the explicit statistical measures of the routing table size and the routing complexity, which can be specified as the functions of the hierarchical network parameters including the number of the hierarchical levels and the cluster population for each hierarchical level. After the relationship between the network topology and these two network performance measures (routing complexity and routing table size) is established, a cluster-population optimisation method for hierarchical networks is presented. The simulation results are also provided to demonstrate the advantage of a hierarchical network over the associated conventional network without hierarchy.

References

    1. 1)
      • R. Hekmat . (2006) Ad-hoc networks: fundamental properties and network topologies.
    2. 2)
    3. 3)
      • L. Li , Y. Zhu , Y. Yu . Link scheduling and data forwarding in wireless sensor networks of long chains tree topology. IET Commun. , 297 - 300
    4. 4)
      • J.M. McQuillan . (1974) Adaptive routing algorithms for distributed computer networks.
    5. 5)
    6. 6)
      • Lauer, G.S.: `Hierarchical routing design for suran', Proc. IEEE ICC, June 1986, p. 93–102.
    7. 7)
    8. 8)
      • Ramamoorthy, C.V., Tsai, W.T.: `An adaptive hierarchical routing algorithm', Proc. IEEE COMPSAC, November 1983, p. 93–104.
    9. 9)
    10. 10)
    11. 11)
      • L. Kleinrock , F. Kamoun . Hierarchical routing for large networks: performance evaluation and optimization, computer networks. Comput. Netw.
    12. 12)
      • Houstic, C.E., Leon, B.J.: `An adaptive routing algorithm for large store-and-forward computer communication networks', Phase Report, October 1977.
    13. 13)
      • Murthy, S., Garcia-Luna-Aceves, J.J.: `Loop-free internet routing using hierarchical routing trees', Proc. IEEE INFOCOM, April 1997, p. 7–11.
    14. 14)
    15. 15)
    16. 16)
      • Behrens, J., Garcia-Luna-Aceves, J.J.: `Hierarchical routing using link vectors', Proc. IEEE INFOCOM, April 1998, p. 702–710.
    17. 17)
    18. 18)
      • Susec, J., Marsic, I.: `Clustering overhead for hierarchical routing in mobile ad hoc networks', Proc. IEEE INFOCOM, April 2002, p. 1698–1706.
    19. 19)
      • D. Stoyan , W. Kendall , J. Mecke . (1995) Stochastic geometry and its applications.
    20. 20)
    21. 21)
      • M.G. Kendall , P.A.P. Moran . (1962) Geometric probability.
    22. 22)
    23. 23)
    24. 24)
    25. 25)
    26. 26)
    27. 27)
      • S.G. Foss , S.A. Zuyev . On a certain segment process with Voronoi clustering. INRIA, Rapport de Recherche , 1 - 17
    28. 28)
      • J.L. Meijering . Interface area, edge length, and number of vertices in crystal aggregates with random nucleation. Philips Research Reprint , 270 - 290
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-com.2011.0025
Loading

Related content

content/journals/10.1049/iet-com.2011.0025
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address