Energy-Efficient Scheduling for Tasks with Deadline in Virtualized Environments

Abstract

Data centers, as resource providers, take advantage of virtualization technology to achieve excellent resource utilization, scalability, and high availability. However, large numbers of computing servers containing virtual machines of data centers consume a tremendous amount of energy. Thus, it is necessary to significantly improve resource utilization. Among the many issues associated with energy, scheduling plays a very important role in successful task execution and energy consumption in virtualized environments. This paper seeks to implement an energy-efficient task scheduling algorithm for virtual machines with changeless speed comprised of two main steps: assigning as many tasks as possible to virtual machines with lower energy consumption and keeping the makespan of each virtual machine within a deadline. We propose a novel scheduling algorithm for heterogeneous virtual machines in virtualized environments to effectively reduce energy consumption and finish all tasks before a deadline. The new scheduling strategy is simulated using the CloudSim toolkit package. Experimental results show that our approach outperforms previous scheduling methods by a significant margin in terms of energy consumption.

Classification and Performance Study of Task Scheduling Algorithms in Cloud Computing Environment

“…Simulation results show that TETS reduced energy consumption by 49 % and makespan by 14 %. (Du, et al, 2014) have presented an energy-efficient task scheduling algorithm that finish all tasks before a deadline for heterogeneous virtual machines in virtualized environments with changeless variable speed. The algorithm is based on combining the list scheduling and the key property of VM speed.…”

Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: A review

“…Nevertheless, VMs also consume a considerable amount of power. Thus, an energy efficient task scheduling algorithm would be effective [65,75] the future. This method has provided to do VM migration as well as maintaining the VM performance level [62].…”

“…In most current and previous research works, simulation systems and some simulation toolkits like CloudSim [52,56,57,65] Microsoft assessment and Planning toolkit (MAP) [80] have been utilized to evaluate the performance of existing or proposed algorithms, techniques, models, and framework. A toolkit has been proposed by Tian [79] for VM modeling and simulation considering the real-time VM allocation.…”