Adaptive approach to load balancing with QoS guarantees in an Edge-Fog-Cloud environment

The article proposes an adaptive approach to load balancing in heterogeneous Edge-Fog-Cloud computing environments ensuring Quality of Service (QoS) guarantees. A mathematical model of a three-tier infrastructure is developed, formalizing the characteristics of computing nodes, task flows, and QoS constraints. A node priority evaluation function is proposed, taking into account computing load, network latency, energy efficiency, and reliability; the weight coefficients are dynamically adapted to the task class. The algorithm makes decisions on task placement across Edge, Fog, and Cloud tiers based on the current system state and task QoS requirements. Simulation results in the iFogSim environment compared to Round Robin, Random, and Min-Min algorithms demonstrate a 36–44% reduction in average execution latency, a 30–37% decrease in energy consumption, and an increase in the QoS compliance ratio to 89–98% under various load scenarios.