Abstract: Provided is a method for scheduling cloud-computing resource, and a system applying the method is herein disclosed. It is featured that the load history record becomes a basis to obtain a computing pattern for each computing node based on a request. The load history is the basis to predict the future computing capability, and accordingly to distribute the computing task. The cloud-computing capability can therefore be advanced. The method firstly receives a computing request. The request includes a number of computing nodes, a start time of computing, and a length of computing time. A computing resource table is established based on the load history for each node, and used to calculate availability and confidence. After that, a resource expectation value is obtained from the availability and confidence. After sorting the expectation values, one or more computing nodes are selected for further task distribution.

Abstract: Provided is a method for scheduling cloud-computing resource, and a system applying the method is herein disclosed. It is featured that the load history record becomes a basis to obtain a computing pattern for each computing node based on a request. The load history is the basis to predict the future computing capability, and accordingly to distribute the computing task. The cloud-computing capability can therefore be advanced. The method firstly receives a computing request. The request includes a number of computing nodes, a start time of computing, and a length of computing time. A computing resource table is established based on the load history for each node, and used to calculate availability and confidence. After that, a resource expectation value is obtained from the availability and confidence. After sorting the expectation values, one or more computing nodes are selected for further task distribution.