The problem of minimizing the execution monetary cost of applications on cloud computing platforms has been studied recently, and satisfying the deadline constraint of an application is one of the most important quality of service requirements. Previous method of minimizing the execution monetary cost of deadline-constrained applications was the “upward” approach (i.e., from exit to entry tasks) rather than combining the “upward” and “downward” approaches. In this study, we propose monetary cost optimization algorithm (DCO/DUCO) by employing “downward” and “upward” approaches together to solve the problem of execution cost minimization. “Downward” cost optimization is implemented by introducing the concept of the variable deadline-span and transferring the deadline of an application to each task. On the basis of DCO, the slack time is utilized to implement “upward” cost optimization without violating the precedence constraints among tasks and the deadline constraint of the application. Experimental results illustrate that the proposed approach is more effective than the existing method under various conditions.

最近已经研究了使应用程序在云计算平台上的执行资金成本最小化的问题，并且满足应用程序的期限约束是最重要的服务质量要求之一。最小化受截止日期限制的应用程序的执行资金成本的先前方法是“向上”方法（即，从退出到进入任务），而不是结合“向上”和“向下”方法。在这项研究中，我们提出了货币成本优化算法（DCO / DUCO），该算法通过同时使用“向下”和“向上”方法来解决执行成本最小化的问题。“下行”成本优化是通过引入可变截止期限的概念并将应用程序的截止日期转移到每个任务来实现的。在DCO的基础上，闲暇时间用于实现“向上”成本优化，而不会违反任务之间的优先约束和应用程序的期限约束。实验结果表明，该方法在各种条件下均比现有方法更有效。