An Intelligent Negotiation Model for Quality of Service Chain

The cloud computing and Service-oriented architecture (SOA) assist and partake for cost-effective improvement of cloud service suppliers in recent years. This paper describes a new grey forecasting which optimize the negotiation process of adaptive Quality of Service (QoS). This study designs a generally weighted moving average (GWMA) sign chart for quality of service chain. A group of suppliers and consumers faced with multiple negotiations related to dynamic services exited both-side benefits conflicting. In a complicated and challenging negotiation procedure to produce multiple acceptable alternatives by both-side preferences. The intelligent service ranking controller assists planners to optimize generalized favourite agreement over the negotiations. The contribution of the research is to present that the alternatives of favourite ranking sequence by a GWMA-adaptive genetic algorithm (AGA) negotiation approach can be significant to improve in the quality of service chain. Finally, an experimental simulation is presented to verify this research.