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Penalty Cost Minimization for Multi-tenant Query Deadline Employing Cache Optimization and Log Based Dispatching

机译:利用缓存优化和基于日志的调度,使多租户查询截止日期的代价成本最小化

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摘要

Execution time is an important indicator of Service Level Agreement. Software as a Service providers expect to finish all queries before their respective deadlines and avoid penalties in violation of agreements. Hence, caching frequently occupied multi-tenant data is an efficient way of reducing execution time and penalty cost. However, it is difficult to minimize penalty cost through choosing cached data from massive multi-tenant data since it hardly finds a quantitative relationship between cached data and penalty cost. To address the challenge, we develop a mechanism of penalty cost minimization for multi-tenant queries based on cache optimization. We generate the cached data by analyzing cost space of multi-tenant data and the violation of queries of each node, and dispatch the incoming queries on the node with the shortest execution time according to multi-tenant cached data distribution. Experimental results suggest that penalty cost by employing the developed mechanism reduces 30% than that of the benchmark solution. Further, the developed mechanism is capable of limiting the dispatching time of queries within 1ms.
机译:执行时间是服务水平协议的重要指标。软件即服务提供商希望在各自的截止日期之前完成所有查询,并避免违反协议的处罚。因此,缓存频繁占用的多租户数据是减少执行时间和代价的有效方法。但是,难以通过从大量多租户数据中选择缓存数据来最小化代价成本,因为它几乎找不到缓存数据与代价成本之间的定量关系。为了解决这一挑战,我们开发了一种基于缓存优化的多租户查询惩罚成本最小化的机制。通过分析多租户数据的成本空间和每个节点查询的冲突情况,生成缓存数据,并根据多租户缓存数据的分布情况,在执行时间最短的节点上调度传入的查询。实验结果表明,采用基准机制的惩罚成本比基准解决方案降低了30%。此外,开发的机制能够将查询的调度时间限制在1ms之内。

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