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A Probabilistic Model for Finding an Optimal Host Framework and Load Distribution in Cloud Environment

机译:用于在云环境中查找最佳主机框架和负载分布的概率模型

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Cloud Computing is being widely accepted in this computing world and comprises of many hardware and software resources. It becomes critical to meet their client's needs on time if the cloud data centers are so overloaded. In this regard, if the utilization of resources becomes an intelligent way so that we focused on the selection problem of the physical hosts for deploying the tasks. So, OPH-LB (Optimal Physical Host with effective Load Balancing) framework is proposed to model the service of client's requests in this IaaS architecture with heterogeneous virtual machines. It proposes the thought of accomplishing load balancing in this dynamic environment. Firstly, this OPH-LB approach is filtering the qualified hosts among all which accomplishes the requirement of deploying tasks. Then out of those qualified sets, we apply probablistic model which helps to find the most optimal host in terms of its computing capability and its performance function. Further, the performance is analyzed using Cloudsim simulation tool and compared with existing approaches. The results demonstrate that our model has improved the throughput, reduced the failure rate and optimized the attainment of cloud data centers.
机译:在该计算世界中广泛接受云计算,并包括许多硬件和软件资源。如果云数据中心如此过载,则满足客户的需求变得至关重要。在这方面,如果资源的利用成为一种智能化方式,我们将专注于用于部署任务的物理主机的选择问题。因此,提出了OPH-LB(具有有效负载均衡的最佳物理主机)框架,以利用异构虚拟机模拟客户在此IAAS架构中的请求服务。它提出了在这种动态环境中实现负载平衡的思考。首先,这种OPH-LB方法正在过滤所有的主机,其中包括部署任务的要求。然后从这些合格的套装中取出,我们应用了概率模型,有助于在其计算能力及其性能函数方面找到最佳的主机。此外,使用CloudSim仿真工具分析性能,并与现有方法进行比较。结果表明,我们的模型提高了吞吐量,降低了失败率并优化了云数据中心的达到。

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