Bio-inspired Communications in Wireless Sensor Networks

  • Barış Atakan
  • Özgür B. Akan
  • Tuna Tuğcu
Part of the Computer Communications and Networks book series (CCN)


Wireless-sensor networks (WSN) are expected to enable connection between physical world and the Internet to provide access to vast amount of information from anywhere and anytime through any kind of communication devices and services. However, this vision poses significant challenges for WSN. Due to the pervasion in its nature, centralized control of WSN is not a practical solution. Instead, WSN and its communication protocols must have the capabilities of scalability, self-organization, self-adaptation, and survivability. In nature, the biological systems intrinsically have these capabilities such that billions of blood cells, which constitute the immune system, can protect the organism from the pathogens without any central control of the brain. Similarly, in the insect colonies insects can collaboratively allocate certain tasks according to the sensed information from the environment without any central controller. Therefore, the natural biological systems may give great inspiration to develop the communication network models and techniques for WSN. In this chapter, we introduce potential solution avenues from the biological systems toward addressing the challenges of WSN such as scalability, self-organization, self-adaptation, and survivability. After the existing biological models are first investigated, biologically inspired communication approaches are introduced for WSN. The objective of these communication approaches is to serve as a roadmap for the development of efficient scalable, adaptive, and self-organizing bioinspired communication techniques for WSN.


Sensor Node Wireless Sensor Network Source Node Sink Node Actor Node 
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.
    Akyildiz I F, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Communications Magazine 40:102–114.CrossRefGoogle Scholar
  2. 2.
    Bonabeau E, Dorigo M, Theraulaz G (1999) Swarm Intelligence, From Natural to Artificial System. Oxford University Press, Oxford.zbMATHGoogle Scholar
  3. 3.
    Muraleedharan R, Osadciw L A (2003) Sensor communication network using swarm intelligence. IEEE Upstate New York Workshop, Syracuse, NY, USA.Google Scholar
  4. 4.
    Muraleedharan R, Osadciw L A (2003) Balancing the performance of a sensor network using an ant system. Annual Conference on Information Sciences and Systems, Baltimore, MD, USA.Google Scholar
  5. 5.
    Caro G D, Ducatelle F, Gambardella L M (2005) AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks. European Transactions on Telecommunications 16:443–455.CrossRefGoogle Scholar
  6. 6.
    Hong Y W, Scaglione A (2005) A scalable synchronization protocol for large scale sensor networks and its applications. IEEE Journal on Selected Areas in Communications 23:1085–1099.CrossRefGoogle Scholar
  7. 7.
    Werner-Allen G, Tewari G, Patel A, Welsh M, Nagpal R (2005) FireflyInspired Sensor Network Synchronicity with Realistic Radio Effects. SenSys’05.Google Scholar
  8. 8.
    Carreras I, Chlamtac I, Woesner H, Kiraly C (2005) BIONETS: Bioinspired next generation networks. Lecture Notes in Computer Science 3457:245–252.CrossRefGoogle Scholar
  9. 9.
    Dressler F (2005) Efficient and Scalable Communication in autonomous networking using bio-inspired mechanisms – An overview. Informatica 29:183–188.Google Scholar
  10. 10.
    Dressler F, Krüger B, Fuchs G, German R (2005) Self-Organization in Sensor Networks Using Bio-Inspired Mechanism. ARCS’05.Google Scholar
  11. 11.
    Dressler F (2005) Locality Driven Congestion Control in Self-Organizing Wireless Sensor Networks. SASO-STEPS’05.Google Scholar
  12. 12.
    Wokoma T, Shum L L, Sacks L, Marshall I (2005) A biologically inspired clustering algorithm dependent on spatial data in sensor networks. Second European Workshop on Wireless Sensor Networks.Google Scholar
  13. 13.
    Atakan B, Akan O B (2007) Immune system based energy efficient and reliable communication in wireless sensor networks. In: Dressler F and Carreras I (eds.) Advances in Biologically Inspired Information Systems, Springer, New York, NY.Google Scholar
  14. 14.
    Timmis J, Neal M, Hunt J (2000) An artificial immune system for data analysis. Biosystems 55:143–150.CrossRefGoogle Scholar
  15. 15.
    Jerne N K (1984) Idiotypic network and other preconceived ideas. Immunological Review 79:5–24.CrossRefGoogle Scholar
  16. 16.
    Farmer J D, Packard N H, Perelson A S (1986) The immune system, adaptation, and machine learning. Physica 22:187–204.MathSciNetGoogle Scholar
  17. 17.
    Vuran M C, Akan O B, Akyildiz I F (2004) Spatio-temporal correlation: theory and applications for wireless sensor networks. Computer Networks Journal (Elsevier) 45:245–261.CrossRefzbMATHGoogle Scholar
  18. 18.
    Berger J O, Oliviera V, Sanso B (2001) Objective bayesian analysis of spatially correlated data. Journal of the American Statistical Association 96:1361–1374.CrossRefzbMATHMathSciNetGoogle Scholar
  19. 19.
    Neal M, Timmis J (2005) Once more unto the breach towards artificial homeostasis. Recent Advances in Biologically Inspired Computing, Idea Group, pp. 340–365.zbMATHGoogle Scholar
  20. 20.
    Oppenheim A V, Schafer R W, Buck J R (1999) Discrete-Time Signal Processing, Prentice Hall, Upper Saddle River, NJ.Google Scholar
  21. 21.
    Hightower J, Borriello G (2001) Location systems for ubiquitous computing. IEEE Computer 34:57–66.Google Scholar
  22. 22.
    Welch P D (1967) The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short modified periodogram. IEEE Transaction on Audio and Electroacoustics 15:70–73.CrossRefMathSciNetGoogle Scholar
  23. 23.
    Akyildiz I F, Kasimoglu I H (2004) Wireless sensor and actor networks: research challenges. Ad Hoc Networks 2:351–367.CrossRefGoogle Scholar
  24. 24.
    Heinzelman W, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Transaction on Wireless Communications 1:660–667.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  • Barış Atakan
    • 1
  • Özgür B. Akan
  • Tuna Tuğcu
  1. 1.Department of Electrical and Electronics EngineeringMiddle East Technical UniversityAnkaraTurkey

Personalised recommendations