On Consensus-Based Distributed Edge Computing Resource Scheduling

Abstract

This paper proposes a novel approach to distributed edge computing resource scheduling based on consensus mechanisms. Traditional edge computing resource management often suffers from inefficiencies due to manual allocation, lack of real-time adaptability, and limited scalability. This research addresses these limitations by leveraging blockchain or similar consensus algorithms to automate and optimize the allocation and scheduling of edge computing resources. The core claim is to utilize these mechanisms for intelligent scheduling and optimization. The proposed system constructs a resource management system driven by consensus, enabling autonomous resource assignment and dynamic scheduling, thereby improving resource utilization. This work presents a framework for building such a system and highlights the potential benefits of integrating consensus-based approaches into the edge computing landscape. The system's design incorporates mechanisms for fault tolerance, security, and scalability, crucial considerations for deploying edge computing solutions in heterogeneous environments. The core mechanism involves a self-organizing system that responds dynamically to changing workloads and resource availability. This paper explores the theoretical underpinnings and outlines a practical implementation strategy, paving the way for more efficient and robust edge computing deployments. ---