Research on Life Characteristics of Internet Based on Network Motifs

TL;DR

This paper investigates the life-like behaviors of the Internet, such as metabolism, self-replication, and mutation, through network motifs and topology analysis, revealing its complex artificial life characteristics.

Contribution

It introduces a framework analyzing Internet evolution via network motifs, highlighting life-like behaviors and mutation phenomena driven by environmental influences.

Findings

Internet exhibits metabolism, self-replication, and mutation behaviors.

Motif M3 fluctuations cause Internet mutations.

Environmental factors trigger Internet mutations.

Abstract

From biosystem to complex system,the study of life is always an important area. Inspired by hyper-cycle theory about the evolution of non-life system, we study the metabolism, self-replication and mutation behavior in the Internet based on node entity, connection relationship and function subgraph--motif--of network topology. Firstly a framework of complex network evolution is proposed to analyze the birth and death phenomena of Internet topology from January 1998 to August 2013. Then we find the Internet metabolism behavior from angle of node, motif to global topology, i.e. one born node is only added into Internet, subsequently takes part in the local reconstruction activities. Meanwhile there are nodes' and motifs' death. In process of the local reconstruction, although the Internet system replicates motifs repeatedly by adding or removing actions, the system characteristics and global structure are not destroyed. Statistics about the motif M3 which is a full connectivity subgraph shows that the process of its metabolism is fluctuation that causes mutation of Internet. Furthermore we find that mutation is instinctive reaction of Internet when it's influenced from inside or outside environment, such as Internet bubble, social network rising and finance crisis. The behaviors of metabolism, self-replication and mutation of Internet indicate its life characteristic as a complex artificial life. And our work will inspire people to study the life-like phenomena of other complex systems from angle of topology structure.