article · IEEE Access
Rising digital transformation drives heavy demand for cloud computing services, increasing the need for electrical energy efficiency across cloud data centres. An energy-efficient hybrid framework combines request scheduling and server consolidation to tackle power use in these facilities. Customer requests are initially sorted according to their time and power requirements before task allocation takes place. A dedicated scheduling algorithm incorporates power consumption criteria into decision-making. Alongside this, a consolidation algorithm detects overloaded systems, identifies underloaded servers to place into sleep or hibernation modes, and determines which virtual machines require migration. A companion migration algorithm handles the relocation of these virtual machines to designated host servers. In simulation experiments, this dual approach outperformed single-strategy methods, improving power usage effectiveness, data centre energy productivity, average task execution time, system throughput, and overall cost savings.
Rapidly expanding cloud usage creates substantial electricity demands, raising operational expenses and carbon footprints for data centres. Combining intelligent task allocation with active server consolidation helps facilities cut wasted power without compromising processing performance. This supports the transition toward greener digital infrastructure by improving energy productivity and lowering operational running costs.
The framework is relevant to cloud service providers and enterprise data centre operators seeking to reduce power bills and improve hardware utilisation. Because the system has been evaluated only through simulation experiments rather than physical deployments, it represents early-stage to applied software research that requires real-world testing on live operational infrastructure before commercial adoption.
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The increasing growth in the demand for cloud computing services, due to the increasing digital transformation and the high elasticity of the cloud, requires more efforts to improve the electrical energy efficiency of cloud data centers. In this paper, an energy-efficient hybrid (EEH) framework for improving the efficiency of consuming electrical energy in data centers is proposed and evaluated. The proposed framework is based on both the request scheduling and servers consolidation approaches rather than depending only on one approach as in the existing related works. The EEH framework sorts the customers' requests (tasks) according to their time and power needs before performing the scheduling. It has a scheduling algorithm that considers power consumption when taking its scheduling decisions. It also has a consolidation algorithm that determines the underloaded servers to be slept or hibernated, the overloaded servers, the virtual machines to be migrated and the servers that will receive migrated virtual machines. In addition, the EEH framework includes a migration algorithm for transferring migrated virtual machines to new servers. Results of simulation experiments indicate the superiority of the EEH framework to the utilization of one approach only to reduce power consumption in terms of power usage effectiveness (PUE), data center energy productivity (DCEP), average execution time, throughput and cost saving.
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DOI: 10.1109/access.2020.3002184
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