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首页> 外文会议>2017 International Conference on Emerging Trends amp; Innovation in ICT >Challenges in green computing for energy saving techniques
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Challenges in green computing for energy saving techniques

机译：绿色计算对节能技术的挑战

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摘要

Virtual machines use are increasing day by day as people are using many smart gadgets which are highly computing and for operating them smoothly, required virtual machines. Virtualization is the basic technique of creating various resources from the available physical infrastructure. It is the backbone of cloud computing technology. This paper try to deal with studying various techniques, models, algorithms, for efficient green cloud computing by using virtualization techniques. It mainly involves virtual machines(VMs) consolidation. Power utilization can be reduced by simply deactivating and reactivating physical machines to meet the current workload. Power awareness in distributed system can be defined as identifying the parameters which minimize the energy consumption along with better QOS, SLA. The various strategies discussed here are mainly focusing on saving power and making data centers more efficient by considering server and network as its scope, however in future due to requirement of high bandwidth and network connectivity of data centers, power requirement of data center will go beyond our imagination. To handle the above mentioned concern require actual study of how power consumption happens in data centers, most of the part of power are consumed by servers, CPU and switches i.e. network devices. There still lots of research need to be done to design such modern algorithm and techniques which achieve better energy efficiency along with consideration of QOS, SLA, and VM consolidation by defining VM topologies which are fault tolerant and also helps nature, mankind by minimizing Co emission.
机译：随着人们使用许多智能小工具，这些小工具具有很高的计算能力，并且需要平稳运行它们，虚拟机的使用正日益增加。虚拟化是从可用物理基础架构中创建各种资源的基本技术。它是云计算技术的骨干。本文试图通过使用虚拟化技术来研究各种技术，模型，算法，以进行有效的绿色云计算。它主要涉及虚拟机（VM）整合。可以通过简单地停用和重新激活物理机来满足当前的工作量来降低功耗。分布式系统中的功率感知可以定义为识别参数，这些参数可以最大程度地降低能耗以及更好的QOS，SLA。这里讨论的各种策略主要集中在以服务器和网络作为其范围，以节省电力并提高数据中心的效率，但是在将来，由于对数据中心的高带宽和网络连接的要求，数据中心的功率需求将超出我们的想象力。为了解决上述问题，需要对数据中心的功耗如何进行实际研究，其中大部分功率由服务器，CPU和交换机（即网络设备）消耗。要设计这样的现代算法和技术，还需要进行大量研究，这些算法和技术通过定义具有容错能力并且还通过最大程度地减少Co排放来帮助自然，人类的VM拓扑，从而在考虑QOS，SLA和VM整合的同时实现更高的能源效率。 。

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