Cloud is a collection of heterogeneous resources and requirements of these resources can change dynamically. Cloud providers are always interested in maximizing the resources utilization and the associated revenues, by trimming down energy consumption and operational expenses, while on the other hand cloud users are interested in minimizing response time and optimizing overall application throughput. In cloud environment to allocate the resources with minimum overhead time along with efficient utilization of available resources is very challenging task. The resources in cloud datacenter are allocated using a virtual machine (VM) scheduling technique. So there is a need of an efficient VM scheduling technique to maximize system performance and cost saving. In this paper two dynamic virtual machine scheduling techniques i.e. Best fit and Worst fit are proposed for reducing the response time along with efficient and balanced resource utilization. The proposed algorithms removes the limitations of the previously proposed Novel Vector based algorithm and minimizes the response time complexity in order of O(log n) and O(1) using Best Fit and Worst Fit strategies respectively.