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Tasks scheduling with lessen energy usage over a cloud server using hybrid adaptive multi-queue approach

机译:使用混合自适应多队列方法在云服务器上以较低的能耗进行任务调度

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High power is individual the major problem of cloud computing networks. Recent tasks computing structures have the randomness environment and calculate the jobs have to be mechanical on all the period to await in-coming jobs. Green cloud computing is model for enabling convent, environments sustainability in information technology sector that can be speedily provisioned and unconfined with lack management effort or green provider communication. The main advantage of the power saving mode; it can use sleep mode, hibernate mode in which energy consumption are less. The green cloud computing solves the major issues of increase with maximum in energy consumption. The objective of green cloud computing is optimize the vigour consumed by physical properties in data centre and except energy and also increases the presentation of the system. There are several scheduling algorithms such as Adaptive Min-Min Scheduling Algorithm; Multilevel Feedback Queue Scheduling Algorithm etc. are utilizing in green cloud computing to lower the energy and time consumption. So, to solve this problem, in proposed work scheduling algorithm will be implementing which is Multilevel Feedback Queue Scheduling algorithm. On the basis of them, energy consumption takes place will be reducing after using improved Adaptive Min-Min Scheduling Algorithm. Check the evaluation of the research method using energy and time parameter.
机译:高功率是云计算网络的主要问题。最近的任务计算结构具有随机性环境,并且计算作业必须在所有期间都是机械的,以等待传入的作业。绿云计算是在信息技术领域实现修道院,环境可持续性的模型,可以在缺乏管理工作或绿色提供商沟通的情况下快速配置和不受限制。省电模式的主要优点;它可以使用能耗较低的睡眠模式,休眠模式。绿云计算解决了能源消耗最大化带来的主要增长问题。绿云计算的目标是优化数据中心中物理属性消耗的活力(除了能量之外),并增加系统的外观。有几种调度算法,例如自适应最小-最小调度算法;多级反馈队列调度算法等在绿色云计算中得到了利用,以降低能耗和时间消耗。因此,为解决该问题,将在所提出的工作调度算法中执行该算法,即多级反馈队列调度算法。在此基础上,使用改进的自适应最小-最小调度算法可以减少能耗。使用能量和时间参数检查研究方法的评估。

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