Description

Cloud computing have a three services. In this paper, We describe the Software as a service. We describe the how the cloud provide the software for user and allocating the user request based. Specifically, a radial basis function neural network is established to transform simulation tasks with abstract descriptions into specific resource requirements in terms of their quantities and qualities. A novel mathematical model is constructed to represent the complex resource allocation process in a multi-tenant computing environment by considering priority-based tenant satisfaction, total computational cost and multi-level load balance. The resource allocation, an improved multi-objective genetic algorithm is proposed based on the elitist archive and the K-means approaches. Our proposed framework and methods can effectively support the cloud simulation paradigm and efficiently meet tenants’ computational requirements in a distributed environment.