The Analysis Of Distributed Task Scheduling System Base On Genetic Algorithm

Task Scheduling is one core of the Distributed Computing System Research. In order to make the system have the best performance, it imports to distribute the reasonable resource to execute the task, this is the problem which the task scheduling will solve. The Task Scheduling is very complex, because the Heterogeneity and dynamic of the Grid System and the different need of the resources of the application program. Bad Task Scheduling will increase the Running time and reduce the throughput of the whole Distributed System.In this paper it introduces the current development state of the Distributed Computing System first, then it analyzes the basic functions of the Task Scheduling and designs the resource collection model in the System. Genetic Algorithm has good performance when it is used to solve the NP Complete Problem of the Task Scheduling, but the traditional Genetic Algorithms have precocious defect. This paper provides an improved Genetic Algorithm according the defect of the traditional Genetic Algorithm. It can provide the user the best performance and increase the efficiency of the task to schedule dynamically according the computing capacity load and network state of the node. In this paper, first it defines the Task Scheduling Problem, then re-designs the selection, crossover and mutation operator according the dynamic characteristic of the Distributed Computing Task Scheduling System in the basis of the basic Genetic Algorithm. At last, it provides the simulation results and the conclusions.The Task Scheduling Problem is NP-Complete Problem,it can shorten the complete time and improve the efficiency of the Distributed System with the characteristics of parallelism and global solution space of the Genetic Algorithm when using the Genetic Algorithm to solve the Task Scheduling Problem.