Soft Computing

, Volume 23, Issue 4, pp 1133–1150 | Cite as

BIAM: a new bio-inspired analysis methodology for digital ecosystems based on a scale-free architecture

  • Vincenzo ContiEmail author
  • Simone Sante Ruffo
  • Salvatore Vitabile
  • Leonard Barolli
Methodologies and Application


Today we live in a world of digital objects and digital technology; industry and humanities as well as technologies are truly in the midst of a digital environment driven by ICT and cyber informatics. A digital ecosystem can be defined as a digital environment populated by interacting and competing digital species. Digital species have autonomous, proactive and adaptive behaviors, regulated by peer-to-peer interactions without central control point. An interconnecting architecture with few highly connected nodes (hubs) and many low connected nodes has a scale- free architecture. A new bio-inspired analysis methodology (BIAM) environment, an investigation strategy for information flow, fault and error tolerance detection in digital ecosystems based on a scale-free architecture is presented in this paper. In order to extract the information about modules and digital species role, the analysis methodology, inspired by metabolic network working, implements a set of three interacting techniques, i.e., topological analysis, flux balance analysis and extreme pathway analysis. Highly connected nodes, intermodule connectors and ultra-peripheral nodes can be identified by evaluating their impact on digital ecosystems behavior and addressing their strengthen, fault tolerance and protection countermeasures. Two real case studies of ecosystems have been analyzed in order to test the functionalities of the proposed (BIAM) environment and the goodness of this approach.


Digital ecosystems Metabolic networks Scale-free architecture DE architectural analysis 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Faculty of Engineering and ArchitectureUniversity of Enna KOREEnnaItaly
  2. 2.Department of Biopathology and Medical BiotechnologiesUniversity of PalermoPalermoItaly
  3. 3.Department of Information and Communication EngineeringFukuoka Institute of TechnologyHigashi-kuJapan

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