Skip to main content

Complex Networks

  • Chapter
  • First Online:
Guide to Graph Algorithms

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

  • 3542 Accesses

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 84.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Akram VK, Orhan Dagdeviren O (2015) On k-connectivity problems in distributed systems. Advanced methods for complex network analysis. IGI Global

    Google Scholar 

  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, Hawaii

    Google Scholar 

  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: 978-9812706645

    Book  Google Scholar 

  4. Cokuslu D, Erciyes K, Dagdeviren O (2006) A dominating set based clustering algorithm for mobile ad hoc networks. Int Conf Comput Sci 1:571–578

    MATH  Google Scholar 

  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 376380

    Google Scholar 

  6. Dongen SV (2000) Graph clustering by flow simulation. Ph.D. Thesis, University of Utrecht, The Netherlands

    Google Scholar 

  7. Erciyes K (2014) The Internet and the Web. In: Complex networks: an algorithmic perspective. CRC Press. ISBN-10: 1466571667, ISBN-13: 978-1466571662

    Book  Google Scholar 

  8. Erciyes K (2015) Distributed and sequential algorithms for Bioinformatics, Springer, Berlin (Chaps. 10 and 11)

    Google Scholar 

  9. Fiedler M (1973) Algebraic connectivity of graphs. Czechoslov Math J 23:298–305

    MathSciNet  MATH  Google Scholar 

  10. Gerla M, Tsai JTC (1995) Multicluster, mobile, multimedia radio network. Wirel Netw 1:255–265

    Article  Google Scholar 

  11. Girvan M, Newman MEJ (2002) Community structure in social and biological networks. PNAS 99:7821–7826

    Article  MathSciNet  Google Scholar 

  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):1074–1085

    Article  Google Scholar 

  13. Harary F (1953) On the notion of balance of a signed graph. Mich Math J 2(2):143–146

    Article  MathSciNet  Google Scholar 

  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 2015

    Google Scholar 

  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 33–38

    Google Scholar 

  16. Kleinberg J (1999) Authoritative sources in a hyperlinked environment. J ACM 46(5):604–632

    Article  MathSciNet  Google Scholar 

  17. Lin CR, Gerla M (1997) Adaptive clustering for mobile wireless networks. IEEE J Sel Areas Commun 15(1):1265–1275

    Article  Google Scholar 

  18. Mount DM (2004) Bioinformatics: sequence and genome analysis, 2nd edn. Cold Spring Harbor Laboratory Press, NY. ISBN 0-87969-608-7

    Google Scholar 

  19. Newman M (2003) Fast algorithm for detecting community structure in networks. Phys Rev E 69:066133

    Article  Google Scholar 

  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 6:344–352

    Article  Google Scholar 

  21. RFC 4271 - A Border Gateway Protocol 4 (BGP-4). www.ietf.org

  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):e2292

    Article  Google Scholar 

  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. 7–14

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Erciyes .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Erciyes, K. (2018). Complex Networks. In: Guide to Graph Algorithms. Texts in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-73235-0_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73235-0_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73234-3

  • Online ISBN: 978-3-319-73235-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics