Federated Cognitive Architectures for Edge Based Swarms

ABSTRACT

The deployment of personal digital assistants is severely hindered by the privacy risks associated with uploading sensitive personal data to centralized cloud environments. We propose a federated framework that enables a swarm of specialized workers running on local edge devices to collaboratively solve complex tasks without sharing raw user data. By exchanging only encrypted cognitive state updates and leveraging secure multi party computation for global routing our system achieves near cloud orchestration capabilities. This research mathematically guarantees local data sovereignty while maintaining high intelligence.