Graph-Based Model of Distributed Computing Systems Using Cloud, Fog, and Edge Technologies for Data Flow Optimization
Abstract
Graph-Based Model of Distributed Computing Systems Using Cloud, Fog, and Edge Technologies for Data Flow Optimization
Incoming article date: 11.09.2025The paper presents the results of an analysis of modern approaches to organizing distributed computing architectures that integrate cloud, fog, and edge levels. The limitations of existing models, which fail to provide a comprehensive description of data flows and the dynamics of interactions between computing nodes, are examined. An adaptive graph-based model is proposed, in which the computing system is formalized as a weighted directed graph with parameters of latency, bandwidth, and energy consumption. The model is implemented within a graph database environment and is designed for multicriteria optimization of information exchange routes. Dependencies for calculating flow characteristics and mechanisms for selecting optimal routes based on QoS indicators are provided. The practical applicability of the concept is confirmed by its potential integration into Internet of Things infrastructures, intelligent manufacturing, and transportation systems, where reducing latency and increasing the resilience of the computing architecture are critical.
Keywords: distributed computing system, cloud computing, fog computing, edge computing, graph model, data flow, route optimization, multicriteria optimization, bandwidth, latency, energy consumption, digital twin, Internet of Things, database, Dijkstra’s algorithm