Cloud computing is an important source of computing worldwide because it can serve customers as needed and without additional costs. Moreover, it serves the customer at the lowest cost and fastest time by providing computing sources in various forms. Aside from providing millions of users the means to use offered services through their own computers, terminals, and mobile devices, studying cloud computing on real cloud systems is difficult at times. Thus, researchers used a specialized program called cloud simulator to study cloud computing, which in turn studies cloud computing from different perspectives, such as energy consumption, cloud services, and resource management. In this paper, we used Green Cloud simulator to model and simulate cloud data centers (DCs). Through this simulator, we presented an experimental comparative study among common task scheduling algorithms in cloud computing (i.e., green, power-saver, random, and round-robin schedulers). These algorithms are discussed and analyzed briefly. The metrics used to evaluate the task scheduling algorithms include (1) server loads, (2) DC loads, and (3) number of servers used.