Title: Dynamic SLA negotiation and conflict resolution in multi-cloud infrastructures using reinforcement learning and Nash bargaining

Authors: Zeng Sai-feng

Addresses: Department of Computer and Communication, Hunan Institute of Engineering, Xiangtan, 411104, China

Abstract: Cloud computing enables elastic resource provisioning, yet multi-cloud systems face challenges in policy heterogeneity and SLA inefficiency. Existing solutions inadequately resolve policy conflicts and SLA management in multi-cloud environments. This paper proposes the policy-driven SLA management in multi-cloud (PSM-MC) framework, integrating policy coordination, dynamic SLA negotiation with game-theoretic bargaining, and adaptive admission control using reinforcement learning. Key innovations include real-time policy conflict resolution via Pareto-optimal compromises, hybrid SLA monitoring combining proactive prediction with reactive adjustments, and Nash bargaining-based resource allocation to balance provider-user tradeoffs. Experimental results demonstrate PSM-MC achieves 15-30% higher virtual resource utilisation and 20% improved SLA compliance compared to existing approaches in large-scale multi-cloud testbeds.

Keywords: multi-cloud; resource policy; virtual machine; SLA negotiation.

DOI: 10.1504/IJWGS.2026.154460

International Journal of Web and Grid Services, 2026 Vol.22 No.2, pp.181 - 200

Received: 25 Feb 2025
Accepted: 12 Mar 2026
Published online: 29 Jun 2026 *

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