Multi-queue peak-alternation scheduling model and multi-queue peak-alteration scheduling method based on task classification in cloud computing

The invention discloses a multi-queue peak-alternation scheduling model and a multi-queue peak-alteration scheduling method based on task classification in cloud computing. The multi-queue peak-alternation scheduling model is characterized by comprising a task manager, a local resource manager, a global resource manager and a scheduler. The multi-queue peak-alternation scheduling method comprises the following steps: firstly, according to demand conditions of a task to resources, dividing tasks into a CPU (central processing unit) intensive type, an I/O (input/output) intensive type and a memory intensive type; sequencing the resources according to the CPU, the I/O and the memory load condition, and staggering a resource using peak during task scheduling; scheduling a certain parameter intensive type mask to a resource with relatively light index load, scheduling the CPU intensive type mask to the resource with relatively low CPU utilization rate. According to the multi-queue peak-alternation scheduling model and the multi-queue peak-alternation scheduling method disclosed by the invention, load balancing can be effectively realized, scheduling efficiency is improved and the resource utilization rate is increased.