Abstract:The whole efficiency of traditional task scheduling algorithms is low under the cloud environment

In order to improve the whole efficiency of the task scheduling

this article based on Map/Reduce presents a Difference Matrix Scheduling tasks schedule algorithm based on processing time. Firstly

pretreatment of complex tasks

the complex tasks is converted to Directed Acyclic Graph figure

the tasks are topological sorted in an optimal manner according to the size of the task dependencies

and the work node is accordance with the sort to processing the complex tasks; Secondly

using the ratio of predictive time that node process tasks to node process capacity as a subtask in each node time quantitative modeling

then establish the task and the metric matrix of process time

according the Difference Matrix Scheduling to processing the matrix

and obtain the optimal scheme of task assignment. Finally

the experiment evaluates the Difference Matrix Scheduling

fair scheduling algorithm

genetic algorithm in the task scheduling and resource utilization efficiency angles. The results show that the algorithm can significantly improve the overall efficiency of complex task scheduling and make full use of the capacity of the compute nodes to improve the Map / Reduce scheduling efficiency.