Graph Structure of the Web

  • Krishna Raj P. M.Email author
  • Ankith Mohan
  • K. G. Srinivasa
Part of the Computer Communications and Networks book series (CCN)


The Web is a humungous system that is evolving at an enormous rate. Understanding this graph can help comprehend the structure of large social network applications which are quickly catching up in size. By understanding the structure of the Web and the properties exhibited by it, the insights gained can be translated into algorithms that can be used for other structures. This chapter looks at the seminal paper, Broder, Kumar, Maghoul, Raghavan, Rajagopalan, Stata, Tomkins, Wiener (Computer networks 33: 309–320, 2000, [1]) which uncovered the bowtie structure of the Web and the studies of Faloutsos et al (ACM SIGCOMM computer communication review 29:251–262, 1999, [2]) which computes the rank, out-degree, hop-plot and eigen exponents of the Web.


  1. 1.
    Broder, Andrei, Ravi Kumar, Farzin Maghoul, Prabhakar Raghavan, Sridhar Rajagopalan, Raymie Stata, Andrew Tomkins, and Janet Wiener. 2000. Graph structure in the web. Computer Networks 33 (1–6): 309–320.Google Scholar
  2. 2.
    Faloutsos, Michalis, Petros Faloutsos, and Christos Faloutsos. 1999. On power-law relationships of the internet topology. In ACM SIGCOMM computer communication review, vol. 29, 251–262, ACM.Google Scholar
  3. 3.
    Newman, Mark E.J. 2005. Power laws, pareto distributions and zipf’s law. Contemporary Physics 46 (5): 323–351.Google Scholar
  4. 4.
    Pansiot, Jean-Jacques, and Dominique Grad. 1998. On routes and multicast trees in the internet. ACM SIGCOMM Computer Communication Review 28 (1): 41–50.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Krishna Raj P. M.
    • 1
    Email author
  • Ankith Mohan
    • 1
  • K. G. Srinivasa
    • 2
  1. 1.Department of ISERamaiah Institute of TechnologyBangaloreIndia
  2. 2.Department of Information TechnologyC.B.P. Government Engineering CollegeJaffarpurIndia

Personalised recommendations