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Resource allocation and request handling for user-aware content retrieval in the cloud

机译:资源分配和请求处理,用于在云中检索用户感知的内容

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The user-aware content retrieval services are always data-intensive and require much resource to satisfy the user demand, which incurs the high cost of implementation. Considering that they could largely exploit the pay-as-you-go paradigm and the almost unlimited resource pool of the cloud, we investigate the design issues of deploying the services to the cloud in a cost-effective way. We formulate the resource allocation and request handling problem which aims at lowering the deployment cost and guaranteeing the service quality simultaneously. Due to the hardness of obtaining an optimal solution, we design two approximate algorithms with different points of emphasis and analyze their approximation ratios as well. In addition, we discuss the implementation issues in applying the proposed algorithms to the practical systems. Finally, the algorithms are evaluated and validated through both trace-based and synthesized simulations where they show a large improvement in terms of the total system cost.
机译:用户感知的内容检索服务始终是数据密集型的,并且需要大量资源来满足用户需求,这会带来高昂的实现成本。考虑到他们可以在很大程度上利用随用随付的范式和几乎无限的云资源池,因此,我们研究了以经济高效的方式将服务部署到云中的设计问题。我们制定资源分配和请求处理问题,旨在降低部署成本并同时保证服务质量。由于获得最优解的难度,我们设计了两种具有不同重点的近似算法,并分析了它们的近似比率。另外,我们讨论了将所提出的算法应用于实际系统的实现问题。最后,通过基于迹线的仿真和综合仿真对算法进行评估和验证,它们在总系统成本方面显示出了很大的改进。

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