A replication strategy for a distributed high-speed caching system based on spatiotemporal access patterns of geospatial data

Abstract

Distributed high-speed caching uses replication strategies to improve the parallel service efficiency in data-intensive services in cloud-based environments. This paper proposes a replication strategy based on the access pattern of tile in order to optimize load balancing for large-scale user access in cloud-based WebGISs. First, this strategy considers the access bias and repeatability involved in tile access, to cache tiles with higher popularities, and obtains a higher cache hit rate under limited distributed caches. Second, on the basis of the uneven distribution and temporal local changes of tile access, it generates hot tile replicas with a seat allocation scheme to efficiently allocate the distributed cache. Finally, it balances the load for tile access requests based on the spatial correlation and spatial locality in tile access patterns to achieve fast data extraction. Experimental results indicate that the proposed strategy can be adopted to handle numerous WebGISs tile requests in a cloud-based environment.