In the emerging e-commerce scenario, information captured by enterprises through their web-based applications has been exploding. Extensive use of applications based on multimedia and social media effects in exponential growth of data. Cloud computing system (or simply cloud) provides the required infrastructure for storing the large data generated by these applications. According to [3], a cloud is defined as ”A model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort of service provider interaction”. Efficient task scheduling in the cloud will reduce the task completion time so that efficient services can be provided to the users. Ant colony- and simulated annealing-based algorithms, genetic algorithms and hybrid algorithms are the ones proposed in the literature for improving the performance of the cloud. In this paper, we have assumed that a cloud consists of a controller node and one or more compute nodes. The controller node does the control of compute nodes present in the cloud including task scheduling. The compute node store the data and carry out the execution of tasks. Virtual machines (VMs) are created in the compute nodes to execute the user tasks. We have assumed that a fixed number of VMs are available (or created) in the compute nodes and different execution environments are maintained in these VMs. Note that, in a cloud environment VMs carry out the execution of tasks.