Institute of Electrical & Electronic Engineers
With Virtual Machine (VM) technology being increasingly mature, compute resources in cloud systems can be partitioned in fine granularity and allocated on demand. The authors make three contributions in this paper: they formulate a deadline-driven resource allocation problem based on the cloud environment facilitated with VM resource isolation technology, and also propose a novel solution with polynomial time, which could minimize users' payment in terms of their expected deadlines. By analyzing the upper bound of task execution length based on the possibly inaccurate workload prediction, they further propose an error-tolerant method to guarantee task's completion within its deadline. They validate its effectiveness over a real VM-facilitated cluster environment under different levels of competition.