Technological Networks

  • Bivas MitraEmail author
Part of the Modeling and Simulation in Science, Engineering and Technology book series (MSSET)

The study of networks in the form of mathematical graph theory is one of the fundamental pillars of discrete mathematics. However, recent years have witnessed a substantial new movement in network research. The focus of the research is shifting away from the analysis of small graphs and the properties of individual vertices or edges to consideration of statistical properties of large scale networks. This new approach has been driven largely by the availability of technological networks like the Internet [12], World Wide Web network [2], etc. that allow us to gather and analyze data on a scale far larger than previously possible. At the same time, technological networks have evolved as a socio-technological system, as the concepts of social systems that are based on self-organization theory have become unified in technological networks [13]. In today’s society, we have a simple and universal access to great amounts of information and services. These information services are based upon the infrastructure of the Internet and the World Wide Web. The Internet is the system composed of ‘computers’ connected by cables or some other form of physical connections. Over this physical network, it is possible to exchange e-mails, transfer files, etc. On the other hand, the World Wide Web (commonly shortened to the Web) is a system of interlinked hypertext documents accessed via the Internet where nodes represent web pages and links represent hyperlinks between the pages. Peer-to-peer (P2P) networks [26] also have recently become a popular medium through which huge amounts of data can be shared. P2P file sharing systems, where files are searched and downloaded among peers without the help of central servers, have emerged as a major component of Internet traffic. An important advantage in P2P networks is that all clients provide resources, including bandwidth, storage space, and computing power. In this chapter, we discuss these technological networks in detail. The review is organized as follows. Section 2 presents an introduction to the Internet and different protocols related to it. This section also specifies the socio-technological properties of the Internet, like scale invariance, the small-world property, network resilience, etc. Section 3 describes the P2P networks, their categorization, and other related issues like search, stability, etc. Section 4 concludes the chapter.


Degree Distribution Percolation Threshold Transmission Control Protocol Average Path Length Distribute Hash Table 
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.


  1. 1.
    L. A. Adamic, R. M. Lukose, A. R. Puniyani, B. A. Huberman, Search in power-law networks, Physical Review E, 64, 046135, 2001.CrossRefGoogle Scholar
  2. 2.
    R. Albert, H. Jeong, A.-L. Barabasi, Diameter of the world wide web, Nature, 401, 130–131, 1999.CrossRefGoogle Scholar
  3. 3.
    R. Albert, H. Jhong, A.-L. Barabasi, Error and attack tolerance of complex networks, Nature, 406, 2000.Google Scholar
  4. 4.
    N. Berger, C. Borgs, T. Chayes, A. Saberi, On the spread of viruses on the Internet, Proceedings of the 16th ACM-SIAM Symposium on Discrete Algorithms (SODA), 301–310, 2005.Google Scholar
  5. 5.
    T. Bu, D. Towsley, On distinguishing between Internet power law topology generators, Proceedings of INFOCOM, New York, NY, USA, 2002.Google Scholar
  6. 6.
    D. Clark, Face-to-face with peer-to-peer networking, IEEE Computer, 34 (1), pp. 18–21, January 2001.Google Scholar
  7. 7.
    Clip2 Company, Gnutella.
  8. 8.
    R. Cohen, K. Erez, D. Avraham, S. Havlin, Resilience of the Internet to random breakdown, Physical Review Letters, 85 (21), 2000.Google Scholar
  9. 9.
    R. Cohen, K. Erez, D. Avraham, S. Havlin, Resilience of the Internet under intentional attack, Physical Review Letters, 86 (16), 2001.Google Scholar
  10. 10.
    Q. Deng, H. Lv, Analyzing unstructured peer-to-peer Search Networks with QIL Proceedings of the IEEE International Conference on Services Computing, pp. 547–550, Shanghai, China, 2004.Google Scholar
  11. 11.
    P. Erdos, A. Renyi, On Random Graphs I, Publ. Mathematical, Debrecen, 6, 290–297, 1959.MathSciNetGoogle Scholar
  12. 12.
    M. Faloutsos, P. Faloutsos, C. Faloutsos, On power-law relationships of the internet topology, Computer Communications Review, 29, 251262, 1999.CrossRefGoogle Scholar
  13. 13.
    C. Fuchs, The Internet as a self-organizing socio-technological system”, Cybernetics and Human Knowing, 12 (31), pp. 37–81, 2005.Google Scholar
  14. 14.
  15. 15.
    R. Govindan, H. Tangmunarunkit, Heuristics for internet map discovery, Proceedings of IEEE Infocom, 2000.Google Scholar
  16. 16.
    C. Griffin, R. Brooks, A note on the spread of worms in scale-free networks, IEEE Transactions on Systems, Man, and Cybernetics, Part B, Feb. 2006.Google Scholar
  17. 17.
    L. Guo, S. Jiang, X. Zhang, H. Wang, LightFlood: Minimizing redundant messages and maximizing scope of peer-to-peer search, IEEE Transactions on Parallel and Distributed Systems (TPDS) 19 (5), pp. 601–614, May 2008.Google Scholar
  18. 18.
    T. Hong, in Peer-to-Peer: Harnessing the benefits of a disruptive technology, Andy Oram (ed), O'Reilly, Sebastopol, CA, Chap. 14, pp. 203–241, 2001.Google Scholar
  19. 19.
    C. Hunt, TCP/IP Network Administration, Second Edition, O'Reilly Networking, December 1997.Google Scholar
  20. 20.
    S. Jin, A. Bestavros, Small-World Internet topologies possible causes and implications on scalability of end-system multicast, Boston University, Technical Report BUCS-TR-2002-004, January 2002.Google Scholar
  21. 21.
    S. Jin, H. Jiang, Novel approaches to efficient flooding search in peer-to-peer networks, Computer Networks: The International Journal of Computer and Telecommunications Networking, 51(10), pp. 2818–2832, July 2007.Google Scholar
  22. 22.
    V. Kalogeraki, D. Gunopulos, D. Zeinalipour-yazti, A local search mechanism for peer to peer networks, Proc. of the 11th ACM Conference on Information and Knowledge Management (ACM CIKM02), 2002.Google Scholar
  23. 23.
    J. O. Kephart, A Biologically inspired immune system for computers, artificial Life IV: Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systemsl, Cambridge, MA, July, 1994.Google Scholar
  24. 24.
    J. M. Kleinberg, S. R. Kumar, P. Raghavan, S. Rajagopalan, A. Tomkins, The Web as a graph: Measurements, models and methods, in Proceedings of the International Conference on Combinatorics and Computing, Lecture Notes in Computer Science, pp. 118, Springer, Berlin, 1999.Google Scholar
  25. 25.
    X. Li, J. Wu, Searching techniques in peer-to-peer networks, Handbook of Theoretical and Algorithmic Aspects of Sensor, Ad Hoc Wireless and Peer-to-Peer Networks, CRC Press, Ann Arbur, MI, 2005.Google Scholar
  26. 26.
    Q. Lv, P. Cao, E. Cohen, K. Li, S. Shenker, Search and replication in unstructured peer-to-peer networks, ACM International Conference on Supercomputing, New York, USA, 2002.Google Scholar
  27. 27.
    G. Manku, Routing networks for distributed hash tables, Annual ACM Symposium on Principles of Distributed Computing archive Proceedings of the twenty-second annual symposium on Principles of distributed computing, Boston, Massachusetts, pp. 133–142, 2003.Google Scholar
  28. 28.
    B. Mitra, F. Peruani, S. Ghose, N. Ganguly, Analyzing the vulnerability of super-peer networks against attack, 14th ACM Conference on Computer and Communications Security, Alexandria, USA, 29 Oct–2 Nov, 2007.Google Scholar
  29. 29.
    B. Mitra, Md M. Afaque, S. Ghose, N. Ganguly, Developing analytical frame-work to measure robustness of peer-to-peer networks, 8th International Conference on Distributed Computing and Networking - ICDCN 2006 (formerly IWDC), December 27–30, 2006, IIT Guwahati, India.Google Scholar
  30. 30.
    B. Mitra, S. Ghose, N. Ganguly, Effect of dynamicity on peer to peer networks, 14th International Conference on High Performance Computing, Goa, India, 19–22 December 2007.Google Scholar
  31. 31.
  32. 32.
    R. Pastor-Satorras, A. Vzquez, A. Vespignani, Dynamical and correlation properties of the Internet, Phys Rev Lett, 87, 258701, 2001.CrossRefGoogle Scholar
  33. 33.
    R. Pastor-Satorras, A. Vespignani, Epidemics and immunization in scale-free networks in S. Bornholdt and H. G. Schuster (eds.), Handbook of Graphs and Networks, Wiley-VCH, Berlin, 2003.Google Scholar
  34. 34.
    R. Pastor-Satorras, A. Vespignani, Epidemic dynamics in finite size scale-free networks, Physical Review E, 65, 035108, 2002.CrossRefGoogle Scholar
  35. 35.
    R. Pastor-Satorras, A. Vespignani, Epidemic dynamics and epidemic states in complex networks, Physical Review E, 63, 066117, 2001.CrossRefGoogle Scholar
  36. 36.
    R. Pastor-Satorras, A. Vespignani, Epidemic spreading in scale-free networks, Physical Review Letters, 86, 32003203, 2001.CrossRefGoogle Scholar
  37. 37.
    K. Patch, Internet stays small world, Technology Research News, 2003.Google Scholar
  38. 38.
    B. Pretre, Attacks on peer-to-peer networks, Ph.D. thesis, Swiss Federal Institute of Technology (ETH) Zurich, 2005.Google Scholar
  39. 39.
    Y. J. Pyun, D. S. Reeves, Constructing a balanced, log(N)-diameter super-peer topology, Proceedings of the 4th International Conference on Peer-to-Peer Computing, Zurich, Switzerland, August 2004.Google Scholar
  40. 40.
    K. Singh, H. Schulzrinne, peer-to-peer internet telephony Using SIP, Columbia University Technical Report CUCS-044-04, New York, NY, October, 2004.Google Scholar
  41. 41.
    P. Szor, The art of computer virus research and defense, Symantec Press, Indianapolis, IN, 2005.Google Scholar
  42. 42.
    A. Vazquez, R. Pastor-Satorras, A. Vespignani, Large-scale topological and dynamical properties of the Internet, Physical Rev E, 65, 066130, 2002.CrossRefGoogle Scholar
  43. 43.
    C. Wang, B. Li, Peer-to-Peer Overlay Networks: A Survey, Department of Computer Science. The Hong Kong University of Science and Technology, Technical Report, 2003.Google Scholar
  44. 44.
    D. J. Watts, S. H. Strogatz, Collective dynamics of ‘small-world’ networks, Nature, 393, 440–442, 1998.CrossRefGoogle Scholar
  45. 45.
    B. Yang, H. Garcia-Molina, Improving search in peer-to-peer networks, Proc. of the 22nd IEEE International Conference on Distributed Computing (IEEE ICDCS02), 2002.Google Scholar
  46. 46.
    B. Yang, H. Garca-Molina, Designing a super-peer networks, Proceedings of the International Conference on Data Engineering (ICDE), Los Alamitos, CA, March 2003.Google Scholar
  47. 47.
    S. Yook, H. Jeong, Y. Tu, A. L. Barabasi, Weighted evolution networks, Phys. Rev. Lett., 86, 5835, 2001.CrossRefGoogle Scholar

Copyright information

© Birkhäuser Boston, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringIndian Institute of TechnologyKharagpurIndia

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