Industry 4.0 have automated the entire manufacturing sector (including technologies and processes) by adopting Internet of Things and cloud computing. To handle the workflows from Industrial Cyber-Physical systems, more and more data centers have been built across the globe to serve the growing needs of computing and storage. This has led to an enormous increase in energy usage by cloud data centers, which is not only a financial burden but also increases their carbon footprint. The private software defined wide area network (SDWAN) connects a cloud provider's data centers across the planet. This gives the opportunity to develop new scheduling strategies to manage cloud providers workload in a more energy-efficient manner. In this context, this article addresses the problem of scheduling data-driven industrial workflow applications over a set of private SDWAN connected data centers in an energy-efficient manner while managing tradeoff of a cloud provider’ revenue. Our proposed algorithm aims to minimize the cloud provider's revenue and the usage of nonrenewable energy by utilizing the real-world electricity prices with the availability of green energy on different cloud data centers, where the energy consumption consists of the usage of running application over multiple data centers and transferring the data among them through SDWAN. The evaluation shows that our proposed method can increase usage of green energy for the execution of industrial workflow up to 3×3\times times with a slight increase in the cost when compared to cost-based workflow scheduling methods.

中文翻译：

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使用绿色能源感知调度算法在软件定义的多云环境中运行工业工作流应用程序


工业4.0通过采用物联网和云计算实现了整个制造业（包括技术和流程）的自动化。为了处理工业信息物理系统的工作流程，全球各地建立了越来越多的数据中心，以满足不断增长的计算和存储需求。这导致云数据中心的能源使用量大幅增加，这不仅是财务负担，而且还增加了其碳足迹。私有软件定义的广域网 (SDWAN) 连接云提供商遍布全球的数据中心。这使得我们有机会开发新的调度策略，以更节能的方式管理云提供商的工作负载。在此背景下，本文解决了在一组私有 SDWAN 连接数据中心上以节能方式调度数据驱动的工业工作流程应用程序的问题，同时管理云提供商收入的权衡。我们提出的算法旨在通过利用现实世界的电价和不同云数据中心上绿色能源的可用性，最大限度地减少云提供商的收入和不可再生能源的使用，其中能源消耗包括在多个数据上运行应用程序的使用中心并通过 SDWAN 在它们之间传输数据。评估表明，与基于成本的工作流调度方法相比，我们提出的方法可以将执行工业工作流的绿色能源使用量提高多达 3×3 倍，而成本略有增加。