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.

Virtual cloud network (VCN) usage is popular today among large and small organizations due to its safety and money-saving. Moreover, it makes all resources in the company work as one unit. VCN also facilitates sharing of files and applications without effort. However, cloud providers face many issues in managing the VCN on cloud computing including these issues: Power consumption, network failures, and data availability. These issues often occur due to overloaded and unbalanced load tasks. In this paper, we propose a new automatic system to manage VCN for executing the workflow. The new system called Multi-User Hybrid Scheduling (MUSH) can solve running issues and save power during workflow execution. It consists of three phases: Initialization, virtual machine allocation, and task scheduling algorithms. The MUSH system focuses on the execution of the workflow with deadline constraints. Moreover, it considers the utilization of virtual machines. The new system can save makespan and increase the throughput of the execution operation.