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Dynamic Affinity Cluster Allocation in a Shared Disks Cluster

机译:共享磁盘群集中的动态相似性群集分配

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A shared disks (SD) cluster couples multiple computing nodes for high performance transaction processing, and all nodes share a common database at the disk level. In the SD cluster, a front-end router selects a node for an incoming transaction to be executed. An affinity-based routing can increase the buffer hit ratio of each node by clustering transactions referencing similar data to be executed on the same node. However, the affinity-based routing is non-adaptive to the changes of the system load. This means that a specific node would be overloaded if corresponding transactions rush into the system. In this paper, we propose a new transaction routing algorithm, named Dynamic Affinity Cluster Allocation (DACA). DACA can make an optimal balance between the affinity-based routing and indiscriminate sharing of load in the SD cluster. As a result, DACA can increase the buffer hit ratio and reduce the frequency of inter-node buffer invalidations while achieving the dynamic load balancing.
机译:共享磁盘(SD)群集耦合多个计算节点以进行高性能事务处理,并且所有节点在磁盘级别共享一个公共数据库。在SD群集中,前端路由器为要执行的传入事务选择一个节点。基于相似性的路由可以通过将引用要在同一节点上执行的相似数据的事务进行聚类来增加每个节点的缓冲区命中率。但是,基于相似性的路由不适应系统负载的变化。这意味着,如果相应的事务进入系统,则特定节点将过载。在本文中,我们提出了一种新的事务路由算法,称为动态亲和力群集分配(DACA)。 DACA可以在基于亲和力的路由和SD群集中不加选择地共享负载之间取得最佳平衡。结果,DACA可以在实现动态负载平衡的同时提高缓冲区命中率,并减少节点间缓冲区失效的频率。

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