A Based On SDN Improved Delaying Scheduler

With the the development of the network and various applications,the internet produces a lot of data,how to store and deal with these large-scale data has become an urgent problem to be solved.In order to meet solve related problems,the operation of large-scale distributed computing data center is being constructed around the world.As the core infrastructure for the data center,the distributed computing framework Hadoop is proposed.For reducing the time caused by data migration during job execution,the algorithm which plays an important role in Hadoop will assign the task to the node where the input data resigns,so as to shorten the response time of the job and improve the performance of the cluster.On the premise of guaranteeing the fairness of the job,the delay scheduling algorithm proposed by Zaharia M el at allocate the tasks to the storage nodes where the data of the tasks require.However,the algorithm just set a static waiting time threshold according to artificial experience,which can not effectively adapt to the dynamic load changes in the data center,leading to the performance of the scheduling algorithm.The proposed algorithm BS-IDS fully consider the data center load,network,the execution state of the head job and so on serveral factors,which affects the performance of delay scheduling algorithm.From this algorithm,we can get an adaptive waiting time threshold. Through the use of SDN(Software Defined Network) to control the flexibility of the network,we can control the network of the data migration,avoiding the impact of the response time casued by changes in the network load.Experimental outcomes indicate that the BS-IDS algorithm is able to adapt to the dynamic change of the data center,and compared with traditional delay scheduling algorithm,it has a better performance in the job response time and so on.