Effective Resource Management of Cloud Data Center

Hu XUE, Jian-ping LUO, Xiong-wen HUANG, Yun YANG


Cloud computing is playing an increasingly important role in modern life, especially in the information age. What followed is a growing number of large-scale data centers were established around the world. It is conceivable that so many data centers must consume huge amounts of electrical energy. A considerable part of the consumption of these electrical energy is due to the irrational use of resources. In this study, the proposed adaptive heuristics for dynamic consolidation of VMs is based on an analysis of hybrid historical data from the resource usage by VMs, which significantly reduce energy consumption, while guaranteeing a high level of Service Level Agreements (SLA). Through simulations we validate that our approach reduces power consumption and ensures SLA compared to other algorithms using PlanetLab workload traces.


Cloud computing, Resource management, QoS, Virtual machine, Consolidation


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