Bio-Inspired Approaches for Enhancing Scalability, Adaptability, and Resilience in Modern Networking Systems

Abstract

In recent years, computer networks have evolved from static, hierarchical structures to highly
distributed, autonomous systems. This shift necessitates self-adaptive and self-organizing capabilities
in networking nodes. Challenges such as scalability, mobility, resource constraints, and the need for
infrastructure-less operation are addressed through biologically inspired approaches. Techniques like
Ant Colony Optimization, Artificial Immune Systems, and epidemic spreading offer promising
solutions for efficient and robust network control. This paper explores various bio-inspired models
and their applications in modern networking paradigms, highlighting their potential to enhance the
performance and resilience of large-scale, dynamic, and heterogeneous networks.