ADSLANF: A negotiation framework for cloud management systems using a bulk negotiation behavioral learning approach

Authors : RAJKUMAR RAJAVEL, MALA THANGARATHINAM

Pages : 563-590

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Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :One of the major challenges in cloud computing is the development of a service-level agreement insert ignore into journalissuearticles values(SLA); negotiation framework using an intelligent third-party broker negotiation strategy. Current frameworks exploit various negotiation strategies using game theoretic, heuristic, and argumentation-based approaches for obtaining optimal negotiation with a better success rate insert ignore into journalissuearticles values(negotiation commitment);. However, these approaches fail to optimize the negotiation round insert ignore into journalissuearticles values(NR);, total negotiation time insert ignore into journalissuearticles values(TNT);, and communication overhead insert ignore into journalissuearticles values(CO); involved in the negotiation strategy. To overcome these problems, certain researchers have exploited trade-off, concession, and behavioral learning strategies with varying degrees of sacrifices insert ignore into journalissuearticles values(reductions); in their concerned proposal generation. Such sacrifices can prevent negotiation break-off and optimize the negotiation strategy to an extent with fewer NRs, less TNT, and less CO. It maximizes the utility value and the success rate. To further optimize the negotiation strategy and prevent negotiation break-off, a bulk negotiation behavioral learning insert ignore into journalissuearticles values(BNBL); approach is proposed. This approach uses the reinforcement learning negotiation strategy to provide varying degrees of sacrifice for obtaining an optimal result. Hence, the proposed automated dynamic SLA negotiation framework insert ignore into journalissuearticles values(ADSLANF); using the BNBL approach will reduce the NRs, TNT, and CO. It also significantly maximizes the utility value and success rate insert ignore into journalissuearticles values(SLA commitment); among negotiation parties such as service consumers and service providers.
Keywords : Negotiation framework, intelligent third party broker agent, bulk proposal negotiation, reinforcement learning approach