论文标题
基于容器的弹性过程的成本效益自动缩放
Cost-efficient Auto-scaling of Container-based Elastic Processes
论文作者
论文摘要
在业务流程景观中，一个普遍的挑战是提供必要的计算资源来制定单个过程步骤。以一种经济高效的方式解决此问题的一种众所周知的方法是使用弹性概念，即以快速方式提供基于云的计算资源，并在这些资源上制定单个过程步骤。提供弹性过程的现有方法主要基于虚拟机（VM）。利用容器技术可以使过程步骤更细粒度分配给计算资源，从而使资源利用率得到更好的利用和提高的成本效率。 在本文中，我们提出了一种通过应用四倍自动缩放方法来优化弹性过程资源分配的方法。主要目标是通过使用容器最大程度地降低过程制定成本。为此，我们制定并实施了应用混合企业线性编程的多目标优化问题，并使用转换步骤将软件服务分配给容器。我们彻底评估了优化问题，并表明它可以在维持服务LEV的同时节省大量成本
In business process landscapes, a common challenge is to provide the necessary computational resources to enact the single process steps. One well-known approach to solve this issue in a cost-efficient way is to use the notion of elasticity, i.e., to provide cloud-based computational resources in a rapid fashion and to enact the single process steps on these resources. Existing approaches to provide elastic processes are mostly based on Virtual Machines (VMs). Utilizing container technologies could enable a more fine-grained allocation of process steps to computational resources, leading to a better resource utilization and improved cost efficiency. In this paper, we propose an approach to optimize resource allocation for elastic processes by applying a four-fold auto-scaling approach. The main goal is to minimize the cost of process enactments by using containers. To this end, we formulate and implement a multi-objective optimization problem applying Mixed-Integer Linear Programming and use a transformation step to allocate software services to containers. We thoroughly evaluate the optimization problem and show that it can lead to significant cost savings while maintaining Service Lev
