Platform for Decentralized Management of Generative AI Services in Edge Computing Systems

Abstract

The present invention discloses a decentralized platform for managing generative artificial intelligence services in edge computing environments. The system comprises a network of distributed edge nodes capable of executing AI models locally, thereby reducing latency, bandwidth usage, and reliance on centralized cloud infrastructure. A decentralized orchestration mechanism dynamically distributes workloads based on real-time parameters such as resource availability, network conditions, and task requirements. The platform incorporates model optimization techniques to enable efficient deployment of generative AI models on resource-constrained devices. Secure communication protocols and trust management systems ensure data integrity, privacy, and node authentication. Additionally, the system supports federated learning for collaborative model improvement without sharing raw data. A monitoring and analytics module provides continuous performance evaluation and adaptive optimization. The invention enables scalable, secure, and efficient deployment of generative AI services across heterogeneous edge environments.

Dependencies are inferred from the claim text.