Cloud Computing emerged from Grid Computing empowered with the concept of virtualization. The advantage of switching to a virtual environment is quite beneficial, however in cloud computing there are significant problems pertaining to performance and cost optimization because of various kinds of resource requirement and execution of multiple jobs. Thus the level of performance and criteria of SLA to be maintained becomes very arduous due to such constraints. To overcome these constraints and amend the solution quality, an integrated approach of scheduling model and resource cost timeline model labelled as Multi-Faceted Optimization Scheduling Framework (MFOSF) has been endeavouring in this paper in a timely manner. Resource Cost timeline model manifest the relation between user budget and producer cost while scheduling Model based on optimization in performance and cost can be achieved by the help of PSO. Some simulation has been made to evaluate this framework by applying four different metrics a) Cost b) the Makespan c) Deadline d) Resource Utilization. On the basis of aforesaid metrics, experiment outcomes show MFOSF-PSO method is more effective than the other models peculiarly increases 57.4 % in best case scenario.

云计算源于网格计算的虚拟化概念。切换到虚拟环境的优势非常有益，但是在云计算中，由于各种资源需求和多个作业的执行，存在与性能和成本优化有关的重大问题。因此，由于这种限制，要维持的SLA的性能水平和标准变得非常艰巨。为了克服这些限制并改善解决方案质量，本文中正在适时尝试一种被称为多目标优化调度框架（MFOSF）的调度模型和资源成本时间轴模型的集成方法。资源成本时间轴模型可显示用户预算与生产者成本之间的关系，而调度则可借助PSO来实现基于性能和成本优化的模型。通过应用四个不同的指标，已经进行了一些模拟评估此框架，其中包括：a）成本b）生成时间c）截止日期d）资源利用。根据上述指标，实验结果表明，MFOSF-PSO方法比其他模型更有效，在最佳情况下增加了57.4％。