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Cost-Effective Resource Provisioning in Cloud Using Cooperative Coevolutionary Genetic Algorithm

机译:使用合作共同遗传遗传算法云中经济有效的资源供应

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Nowadays, cloud is widely used platform for intensive computing, bulk storage, and networking. Elastically scalable on demand pay as per used model is one of the major reasons for the acceptability of the cloud-based computing. Data centers with huge amount of computing devices are distributed over the cloud service provider as the back end to provide services. Computing devices are arranged bombastically in data centers to ensure 24/7 availability. Inspired from Pantriyagin's maximization principle for optimal control and self-balancing population with predator-prey interaction in ecological environment, a model for resource provisioning with cost-effective approach and efficient resource utilization scheme is presented in this paper. We present an optimal resource provisioning model by taking into account the matter of sustainability and profitability. Cooperative coevolutionary genetic algorithm is implemented in CloudSim simulation tool to find the optimal cost per provisioning.
机译:如今,云广泛使用平台,用于密集计算,批量存储和网络。按需按需支付可弹性可扩展,根据二手模型是基于云计算的可接受性的主要原因之一。具有大量计算设备的数据中心分布在云服务提供商上作为后端提供服务。计算设备在数据中心批量布置,以确保24/7可用性。灵感来自于Pantriyagin的最大化原则,以获得生态环境中的捕食者 - 猎物互动的最佳控制和自我平衡人口,本文提出了一种具有成本效益的方法和有效资源利用方案的资源供应模型。我们通过考虑到可持续性和盈利能力来提出最佳资源供应模型。 CloudSim仿真工具中实现了协作共同遗传遗传算法,以找到每个配置的最佳成本。

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