Recently, growing cloud services (CSs) have been leased by organizations for high-performance computation and massive data storage of data-intensive applications (DiAs). To improve the resource utilization of leased CSs, it has become a challenging task to optimize infrastructure as a service CS composition for DiAs (ICSCDs) from the user side. This paper proposes a resource utilization-aware collaborative optimization approach. Targeting the collaboration features of tasks in a DiA, the environments—classes, agents, roles, groups, and objects model is used to formalize the ICSCD problem from the perspective of role-based collaboration. Aiming at the dynamic characteristics of the cloud environment, an integrated method is presented to evaluate the qualification of CSs via the interval numbers with multiple parameters. Based on the exact qualification values, the ICSCD can be optimized for improving the resource utilization of the CSs. A solution using the IBM ILOG CPLEX optimization package is put forward to solve the problem. The experimental results demonstrate that the approach can provide high precision, performance, stability, resource utilization, and low usage cost for the resource utilization-aware ICSCD from the user side.

中文翻译：

---

面向数据密集型应用的 IaaS 云服务组合的资源利用感知协同优化

最近，组织租用了不断增长的云服务 (CS)，用于数据密集型应用程序 (DiAs) 的高性能计算和海量数据存储。为了提高租用 CS 的资源利用率，从用户侧优化 DiAs（ICSCD）的基础设施即服务 CS 组合已成为一项具有挑战性的任务。本文提出了一种资源利用感知的协同优化方法。针对 DiA 中任务的协作特性，环境——类、代理、角色、组和对象模型用于从基于角色的协作的角度形式化 ICSCD 问题。针对云环境的动态特性，提出了一种基于多参数区间数对CSs的合格性进行综合评价的方法。根据确切的资格值，可以优化 ICSCD 以提高 CS 的资源利用率。提出了使用IBM ILOG CPLEX 优化包的解决方案来解决该问题。实验结果表明，该方法可以为用户侧的资源利用率感知ICSCD提供高精度、性能、稳定性、资源利用率和低使用成本。