Bio-inspired Clustering and Data Diffusion in Machine Social Networks

  • Iva Bojic
  • Tomislav Lipic
  • Vedran Podobnik


At the end of 2010, we are at the effective end of the second phase of research in the field of Social Networks (SNs) and aspects such as Human-to-Human (H2H) interactions have pretty much had their day due to advances in Machine-to-Machine (M2M) interactions. This chapter will provide a useful insight into the differences between those two types of SNs: the human SNs (hSNs) based on H2H interactions and the machine SNs (mSNs) based on M2M interactions. During the last two decades rapid improvements in computing and communication technologies have enabled a proliferation of hSNs and we believe they will induce the formation of mSNs in the next decades. To this end, we will show how to carry out successful SN analyses (e.g. clustering and data diffusion) by connecting ethological approaches to social behaviour in animals (e.g. the study of firefly synchronization) and M2M interactions.


Cluster Coefficient Data Diffusion Community Detection Smart Home Smart City 
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.



The authors acknowledge the support of the research project “Content Delivery and Mobility of Users and Services in New Generation Networks” (036-0362027-1639), funded by the Ministry of Science, Education and Sports of the Republic of Croatia.


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Copyright information

© Springer-Verlag London 2012

Authors and Affiliations

  1. 1.Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia
  2. 2.Centre for Informatics and ComputingRudjer Boskovic InstituteZagrebCroatia

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