Complex Networks

Chapter
Part of the Texts in Computer Science book series (TCS)

Abstract

Complex networks consist of tens of thousands of nodes and hundreds of thousands of edges connecting these nodes. The graphs used to model these networks are large and special methods are commonly needed for the analysis of these networks. The main complex networks which are biological networks, social networks, technological networks and information networks are reviewed with brief description of the algorithms needed to solve some problems in these networks in this chapter.

References

  1. 1.
    Akram VK, Orhan Dagdeviren O (2015) On k-connectivity problems in distributed systems. Advanced methods for complex network analysis. IGI GlobalGoogle Scholar
  2. 2.
    Alzoubi KM, Wan P-J, Frieder O (2002) New distributed algorithm for connected dominating set in wireless ad hoc networks. In: Proceedings of 35th Hawaii international conference on system sciences, Big Island, HawaiiGoogle Scholar
  3. 3.
    Caldarelli G, Vespignani A (2007) Large scale structure and dynamics of complex networks: from information technology to finance and natural science. Complex Systems and Interdisciplinary Science. World Scientific Publishing Company. Chapter 8, ISBN-13: 978-9812706645CrossRefGoogle Scholar
  4. 4.
    Cokuslu D, Erciyes K, Dagdeviren O (2006) A dominating set based clustering algorithm for mobile ad hoc networks. Int Conf Comput Sci 1:571–578MATHGoogle Scholar
  5. 5.
    Das B, Bharghavan V (1997) Routing in ad-hoc networks using minimum connected dominating sets. In: IEEE international conference on communications (ICC97), vol 1, pp 376380Google Scholar
  6. 6.
    Dongen SV (2000) Graph clustering by flow simulation. Ph.D. Thesis, University of Utrecht, The NetherlandsGoogle Scholar
  7. 7.
    Erciyes K (2014) The Internet and the Web. In: Complex networks: an algorithmic perspective. CRC Press. ISBN-10: 1466571667, ISBN-13: 978-1466571662CrossRefGoogle Scholar
  8. 8.
    Erciyes K (2015) Distributed and sequential algorithms for Bioinformatics, Springer, Berlin (Chaps. 10 and 11)Google Scholar
  9. 9.
    Fiedler M (1973) Algebraic connectivity of graphs. Czechoslov Math J 23:298–305MathSciNetMATHGoogle Scholar
  10. 10.
    Gerla M, Tsai JTC (1995) Multicluster, mobile, multimedia radio network. Wirel Netw 1:255–265CrossRefGoogle Scholar
  11. 11.
    Girvan M, Newman MEJ (2002) Community structure in social and biological networks. PNAS 99:7821–7826MathSciNetCrossRefGoogle Scholar
  12. 12.
    Hagen L, Kahng AB (1992) New spectral methods for ratio cut partitioning and clustering. IEEE Trans Comput Aided Des Integr Circuits Syst 11(9):1074–1085CrossRefGoogle Scholar
  13. 13.
    Harary F (1953) On the notion of balance of a signed graph. Mich Math J 2(2):143–146MathSciNetCrossRefGoogle Scholar
  14. 14.
    International Organization for Standardization (1989-11-15) ISO/IEC 7498-4:1989 – Information technology – open systems interconnection – basic reference model: naming and addressing. ISO Standards Maintenance Portal. ISO Central Secretariat. Retrieved 17 Aug 2015Google Scholar
  15. 15.
    Jorgic M, Goel N, Kalaichevan K, Nayak A, Stojmenovic I (2007) Localized detection of k-connectivity in wireless ad hoc, actuator and sensor networks. In: Proceedings of 16th international conference on computer communications and networks (ICCCN 2007), pp 33–38Google Scholar
  16. 16.
    Kleinberg J (1999) Authoritative sources in a hyperlinked environment. J ACM 46(5):604–632MathSciNetCrossRefGoogle Scholar
  17. 17.
    Lin CR, Gerla M (1997) Adaptive clustering for mobile wireless networks. IEEE J Sel Areas Commun 15(1):1265–1275CrossRefGoogle Scholar
  18. 18.
    Mount DM (2004) Bioinformatics: sequence and genome analysis, 2nd edn. Cold Spring Harbor Laboratory Press, NY. ISBN 0-87969-608-7Google Scholar
  19. 19.
    Newman M (2003) Fast algorithm for detecting community structure in networks. Phys Rev E 69:066133CrossRefGoogle Scholar
  20. 20.
    Olman V, Mao F, Wu H, Xu Y (2009) Parallel clustering algorithm for large data sets with applications in bioinformatics. IEEE/ACM Trans Comput Biol Bioinform 6:344–352CrossRefGoogle Scholar
  21. 21.
    RFC 4271 - A Border Gateway Protocol 4 (BGP-4). www.ietf.org
  22. 22.
    Titz B, Rajagopala SV, Goll J, Hauser R, McKevitt MT, Palzkill T, Uetz P (2008) The binary protein interactome of Treponema pallidum, the syphilis spirochete. PLOS ONE 3(5):e2292CrossRefGoogle Scholar
  23. 23.
    Wu J, Li H (1999) On calculating connected dominating set for ef- ficient routing in ad hoc wireless networks. In: Proceedings of the third international workshop on discrete algorithms and methods for mobile computing and communications, pp. 7–14Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.International Computer InstituteEge UniversityIzmirTurkey

Personalised recommendations