Caching optimization with accessor clustering

Abstract

Distributed computing system (DCS) performance is enhanced by caching optimizations. The DCS includes nodes with local caches. Resource accessors such as users are clustered based on their similarity, and the clusters are assigned to nodes. Then processing workloads are distributed among the nodes based on the accessors the workloads implicate, and based on which nodes were assigned to those accessors' clusters. Clustering may place security peers together in a cluster, and hence place peers together on a node. Security peers tend to access the same resources, so those resources will more often be locally cached, improving performance. Workloads implicating peers also tend to access the same resources, such as peers' behavior histories, so those resources will likewise tend to be cached locally, thus optimizing performance as compared for example to randomly assigning accessors to nodes without clustering and without regard to security peer groupings.