Bio Cognitive Mesh: Harnessing Swarm Intelligence for Self-Organizing AI at the Network Edge

Unprecedented challenges of growing edge computing and the Internet of Things (IoT) have created the need of the hour to change the architecture of unchanging centralized AI [1], [2]. In this paper, we describe a framework for deploying decentralized artificial intelligence using swarm intelligence in edge computing networks such that all intelligence algorithms can be executed concurrently through swarm intelligence. Currently, most traditional AI deployment requires heavy and centralized reliance on the cloud infrastructure, leading to data transmission bottlenecks, higher latency, and privacy concerns [3], [4]. We use bio-inspired swarm algorithms to distribute computational intelligence across edge devices in a fashion whose computational intelligence is collectively made without central control [5], [6]. We demonstrate consistent improvements in smart city infrastructure, autonomous vehicle testbeds, and IoT networks: reducing latency by 78x, decreasing bandwidth consumption by 83x, and securing system resilience while maintaining model accuracy. This research contributes to the edge AI field by presenting a scalable and resilient architecture for distributed intelligence on constrained resources [7], [8].