Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Software as a Service (SaaS) is a software delivery model for application vendors to serve large amount of users with customized services. To meet the different non-functional requirements of different users, multi-tenant SaaS applications must support different QoS level of different tenants. To ensure QoS level while maintaining high resource utilizing efficiency, this paper proposes a user requirement supporting system resource allocation method. The goal of system resource allocation is analyzed, and the mathematical model of the problem is put forward. Then 2 algorithms to solve the problem are proposed: one based on heuristic algorithm and one based on genetic algorithm. Through experimental results of the solution quality and execution time,  compare the performance and put forward the selection policy beten the 2 algorithms.
['Hongyong Yu', 'Deshuai Wang']
I am writing a research paper on a idea System resource allocation algorithm for multi-tenant SaaS application
[{"from": "human", "value": "I am writing a research paper on a idea System resource allocation algorithm for multi-tenant SaaS application"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Software as a Service (SaaS) is a software delivery model for application vendors to serve large amount of users with customized services. To meet the different non-functional requirements of different users, multi-tenant SaaS applications must support different QoS level of different tenants. To ensure QoS level while maintaining high resource utilizing efficiency, this paper proposes a user requirement supporting system resource allocation method. The goal of system resource allocation is analyzed, and the mathematical model of the problem is put forward. Then 2 algorithms to solve the problem are proposed: one based on heuristic algorithm and one based on genetic algorithm. Through experimental results of the solution quality and execution time,  compare the performance and put forward the selection policy beten the 2 algorithms."}]