Cloud computing is a well-known technology that provides flexible, efficient, and cost-effective information technology solutions for multinationals to offer improved and enhanced quality of business services to end-users. The cloud computing paradigm is instigated from grid and parallel computing models as it uses virtualization, server consolidation, utility computing, and other computing technologies and models for providing better information technology solutions for large-scale computational data centers. The recent intensifying computational demands from multinationals enterprises have motivated the magnification for large complicated cloud data centers to handle business, monetary, Internet, and commercial applications of different enterprises. A cloud data center encompasses thousands of millions of physical server machines arranged in racks along with network, storage, and other equipment that entails an extensive amount of power to process different processes and amenities required by business firms to run their business applications. This data center infrastructure leads to different challenges like enormous power consumption, underutilization of installed equipment especially physical server machines, CO₂ emission causing global warming, and so on. In this article, we highlight the data center issues in the context of Pakistan where the data center industry is facing huge power deficits and shortcomings to fulfill the power demands to provide data and operational services to business enterprises. The research investigates these challenges and provides solutions to reduce the number of installed physical server machines and their related device equipment. In this article, we proposed server consolidation technique to increase the utilization of already existing server machines and their workloads by migrating them to virtual server machines to implement green energy-efficient cloud data centers. To achieve this objective, we also introduced a novel Virtualized Task Scheduling Algorithm to manage and properly distribute the physical server machine workloads onto virtual server machines. The results are generated from a case study performed in Pakistan where the proposed server consolidation technique and virtualized task scheduling algorithm are applied on a tier-level data center. The results obtained from the case study demonstrate that there are annual power savings of 23,600 W and overall cost savings of US$78,362. The results also highlight that the utilization ratio of already existing physical server machines has increased to 30% compared to 10%, whereas the number of server machines has reduced to 50% contributing enormously toward huge power savings.

云计算是一项众所周知的技术，可为跨国公司提供灵活，高效和具有成本效益的信息技术解决方案，以为最终用户提供改进和增强的业务服务质量。云计算范例从网格和并行计算模型中得到启发，因为它使用虚拟化，服务器整合，实用程序计算和其他计算技术和模型来为大型计算数据中心提供更好的信息技术解决方案。跨国企业最近对计算的需求日益增加，促使大型复杂的云数据中心处理不同企业的业务，货币，互联网和商业应用的放大。云数据中心包含成千上万台布置在机架中的物理服务器计算机以及网络，存储和其他设备，这些设备需要大量电源来处理业务公司运行其业务应用程序所需的不同流程和便利设施。这种数据中心基础架构导致各种挑战，例如巨大的功耗，未充分利用已安装的设备（尤其是物理服务器计算机），CO_2个导致全球变暖的排放等。在本文中，我们重点介绍了巴基斯坦背景下的数据中心问题，巴基斯坦数据中心行业正面临巨大的电力短缺和缺陷，无法满足为企业提供数据和运营服务所需的电力需求。该研究调查了这些挑战，并提供了解决方案以减少已安装的物理服务器计算机及其相关设备的数量。在本文中，我们提出了服务器整合技术，通过将现有服务器计算机迁移到虚拟服务器计算机以实现绿色节能的云数据中心，从而提高了现有服务器计算机及其工作负载的利用率。为了达到这个目的，我们还介绍了一种新颖的虚拟化任务调度算法，用于管理物理服务器计算机的工作负载并将其正确分配到虚拟服务器计算机上。结果是从在巴基斯坦进行的案例研究中得出的，在该案例研究中，将建议的服务器整合技术和虚拟化的任务调度算法应用于层级数据中心。从案例研究中获得的结果表明，每年可节省23,600瓦的功率，总成本可节省78,362美元。结果还突出表明，现有物理服务器计算机的利用率从10％提高到30％，而服务器计算机的数量减少到50％，为节省大量电量做出了巨大贡献。结果是从在巴基斯坦进行的案例研究中得出的，在该案例研究中，将建议的服务器整合技术和虚拟化的任务调度算法应用于层级数据中心。从案例研究中获得的结果表明，每年可节省23,600瓦的功率，总成本可节省78,362美元。结果还突出表明，现有物理服务器计算机的利用率已从10％提高到30％，而服务器计算机的数量已减少到50％，为节省大量电能做出了巨大贡献。结果是从在巴基斯坦进行的案例研究中得出的，在该案例研究中，将建议的服务器整合技术和虚拟化的任务调度算法应用于层级数据中心。从案例研究中获得的结果表明，每年可节省23,600瓦的功率，总成本可节省78,362美元。结果还突出表明，现有物理服务器计算机的利用率从10％提高到30％，而服务器计算机的数量减少到50％，为节省大量电量做出了巨大贡献。