In virtualized cloud computing systems, energy reduction is a serious concern since it can offer many major advantages, such as reducing running costs, increasing system efficiency, and protecting the environment. At the same time, an energy-efficient task scheduling strategy is a viable way to meet these goals. Unfortunately, mapping cloud resources to user requests to achieve good performance by minimizing the energy consumption of cloud resources within a user-defined deadline is a huge challenge. This paper proposes Energy and Performance-Efficient Task Scheduling Algorithm (EPETS) in a heterogeneous virtualized cloud to resolve the issue of energy consumption. There are two stages in the proposed algorithm: initial scheduling helps to reduce execution time and satisfy task deadlines without considering energy consumption, and the second stage task reassignment scheduling to find the best execution location within the deadline limit with less energy consumption. Moreover, to make a reasonable balance between task scheduling and energy saving, we suggest an energy-efficient task priority system. The simulation results show that, compared to current energy-efficient scheduling methods of RC-GA, AMTS, and E-PAGA, the proposed solution helps to reduce significant energy consumption and improve performance by $5\%$–$20\%$ with deadline constraint satisfied.

在虚拟化云计算系统中，降低能耗是一个严重的问题，因为它可以提供许多主要优势，例如降低运行成本，提高系统效率和保护环境。同时，节能任务调度策略是实现这些目标的可行方法。不幸的是，通过在用户定义的期限内将云资源的能耗降至最低，将云资源映射到用户请求以实现良好性能是一项巨大的挑战。本文提出了一种在异构虚拟化云中的能源和性能高效的任务调度算法（EPETS），以解决能源消耗问题。提出的算法分为两个阶段：初始调度有助于减少执行时间并满足任务期限，而无需考虑能耗；以及第二阶段的任务重新分配计划，以在截止期限限制内以更少的能耗找到最佳的执行位置。此外，为了在任务调度和节能之间取得合理的平衡，我们建议使用节能的任务优先级系统。仿真结果表明，与当前的RC-GA，AMTS和E-PAGA的节能调度方法相比，所提出的解决方案可通过以下方法帮助减少大量能耗并提高性能：$5％$–$20％$ 满足最后期限约束。