Abstract
Reducing energy consumption of data centers is an important way for cloud providers to improve their investment yield, but they must also ensure that the services delivered meet the various requirements of consumers. In this paper, we propose a resource management strategy to reduce both energy consumption and Service Level Agreement (SLA) violations in cloud data centers. It contains three improved methods for subproblems in dynamic virtual machine (VM) consolidation. For making hosts detection more effective and improving the VM selection results, first, the overloaded hosts detecting method sets a dynamic independent saturation threshold for each host, respectively, which takes the CPU utilization trend into consideration; second, the underutilized hosts detecting method uses multiple factors besides CPU utilization and the Naive Bayesian classifier to calculate the combined weights of hosts in prioritization step; and third, the VM selection method considers both current CPU usage and future growth space of CPU demand of VMs. To evaluate the performance of the proposed strategy, it is simulated in CloudSim and compared with five existing energy–saving strategies using real-world workload traces. The experimental results show that our strategy outperforms others with minimum energy consumption and SLA violation.
Highlights
Cloud computing [1] has revolutionized the ownership model of IT infrastructure by offering on-demand provisioning of elastic resources [2]
We first present the impact of the parameter n in the overloaded hosts detecting method, on the performance of the proposed resource management strategy and determine the optimal value for it. en, the performance of our strategy is evaluated relying on the aforementioned metrics, and the experimental results are analyzed in comparison to some benchmark strategies
When the value of n is too large, some saturated state hosts cannot be timely converted into overloaded state for virtual machine (VM) migrations; the resource requests of some VMs on them may not be satisfied, resulting in increasing Service Level Agreement (SLA) violations and energy consumption
Summary
Cloud computing [1] has revolutionized the ownership model of IT infrastructure by offering on-demand provisioning of elastic resources [2]. Lowlatency, and parallel processing capability, it has become a suitable and popular platform in many areas Many industry magnates, such as Google, IBM, Microsoft, and Amazon, have begun to put massive manpower and financial resources to promote the commercialization of cloud computing and related services [3]. Since the average energy consumption of a data center is almost as much as 25000 households’, the rapid expansion of the number of data centers must be accompanied by the fast increasing in energy demand. Such high energy consumption can directly lead to the increasing of carbon dioxide (CO2) emissions and operational costs of data centers [4]. Improving the energy efficiency and eliminating unnecessary energy costs have become hot spots in the industry and the main difficulty and challenge of the next-generation data centers
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