Abstract: With the rapid development of cloud computing,large scale distributed computation is used widely．However,recently,energy consumption of such distributed systems has become problem for further application．Existing methods for saving energy are developed mainly by decreasing the amount of running servers．However,these approaches do not consider the energy cost on network devices．This paper proposed a hierarchical scheduling algorithm．Our algorithm employs a dynamic maximum node sorting (DMNS) method to optimize the assignment of applications on servers which are connected to a switch in the same level．Secondly,we transfered the applications on the nodes with low load to the nodes which can handle more application in order to reduce the number of nodes．In addition,we chose the transfer path which bears less capacity of data exchange and less length which helps to reduce the energy consumption of network．As a result,both the running servers and the data transfer can be greatly reduced．The time complexity of HSA is satisfactory,and its stability is verified through simulations．Experimental results show that the performance of HSA outperforms existing methods.

Key words: Distributed computing,Energy-saving schedule,HAS,KMNS,DMNS