A resource license scheduling method for hadoop in cloud computing using resource allocation

A resource license scheduling method using resource allocation is proposed to improve the poor performance caused by different computing capacities of nodes and mixed workload in cloud computing. The method improves the performance through reducing the resources wasting or overload. It collects resource information and estimates resource requirements of workloads and allocates computing resources dynamically according to available resources and resource requirements of workloads. Licenses uncoupled with resources are used to launch tasks and to adjust the number of parallel tasks to adapt the cloud environment by controlling the number of licenses. The method is evaluated in the national high performance computing center (Xi'an). Results show that the completion times of single job workloads of the proposed method are better than those of the FAIR scheduler in competitive environments. Moreover, the completion times of mixed workloads of the method in three environments reduce 27.5%, 37.1% and 50.98% respectively on average, that is, the performance of the method has a significant improvement. It can be concluded from the results that the proposed method adapts the complex environment and solve the performance problem in cloud computing. ©, 5015, Xi'an Jiaotong University. All right reserved.