Multi-objective Optimization Framework to Support Decision-making for Applications Migration in Cloud Computing

Abstract

Moving programs to the cloud could have a significant positive impact on everyone who is interested in cloud computing. For example, on-demand computing systems offer economic advantages. These include the ability to scale applications up and down to meet businesses' continuously changing needs. Customers, on the other hand, may struggle to decide whether to move an app to the cloud. Customers should be able to achieve their objectives without difficulty, and they should also consider the quality of the service they receive. Various issues must be addressed to choose the best cloud service provider that offers the lowest pricing, improves performance (lower response times), and reduces Service Level Agreement (SLA) violations. (Not specific about the method). We offer a multi-objective optimization framework that helps decision-makers determine the optimal trade-off among lowering costs, improving performance, and preventing service level agreement breaches. This framework provides a better option. This system was developed to address these issues. The proposed framework can produce up to 80% more optimal solutions than current search optimization strategies. These solutions offer lower prices, better performance, and fewer service-level agreement violations. This is the case when comparing the system to other methods of optimizing search results. These optimization solutions are intended to help people decide whether to transfer apps to the cloud.