Grid Computing is the technology of dividing computer networks with different and heterogeneous resources based on distribution computing. Grid computing has no limitation due to its geographical domain and the type of undercover resources. Generally, a grid network can be considered as a series of several big branches, different kinds of microprocessors, thousands of PC computers and workstations in all over the world. The goal of grid computing is to apply available computing resources easily for complicated calculations vie sites which are distributed geographically. In another words, the least cost for many users is to support parallelism, minimize the time of task operation and so on in scientific, trade and industrial contexts. To reach the goal, it is necessary to use an efficient scheduling system as a vital part for grid environment. Generally, scheduling plays very important role in grid networks. So, selecting the type of scheduling algorithm has an important role in optimizing the reply and waiting time which involve as two important factors. As providing scheduling algorithms which can minimize tasks runtime and increase operational power has remarkable importance in these categories. In this paper, we discuss about scheduling algorithms which involve independent algorithms such as Minimum Execution Time, Minimum Completion Time, Min-min, Max-min and XSuffrage.