Work

SIA: A Stackelberg-induced Actor-Critic framework for optimized cloud infrastructure scheduling

Year: 2025

Type: article

Abstract: An innovative Stackelberg-induced Actor-Critic Framework (SIA) is proposed to address QoS optimization and load balancing challenges in cloud infrastructure. SIA models their interaction as a hierarchical control problem using a Stackelberg game, where the leader (QoS components) anticipates the follower's (load balancing components) responses; both influence task assignments to virtual machines. Operating on a discrete-time nonlinear system, SIA employs adaptive critic design with neural networks. Experimental results show that SIA substantially improves QoS prediction in cloud workflow scheduling, achieving RMSE reductions from 22.93% to 35.82% and MAE reductions exceeding 100% compared to existing methods.

Source: Nonlinear Theory and Its Applications IEICE

DOI: 10.1587/nolta.16.622

Authors: Alisha Maity, Nitish Das

Institutions: Amity University, MIT Art, Design and Technology University

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Amity University