Specific features of tile access patterns can be applied in a cache replacement strategy to a limited distributed high-speed cache for the cloud-based networked geographic information services (NGISs), aiming to adapt to changes in the access distribution of hotspots. By taking advantage of the spatiotemporal locality, the sequential features in tile access patterns, and the cache reading performance in the burst mode, this article proposes a tile sequence replacement method, which involves structuring a Least Recently Used (LRU) stack into three portions for the different functions in cache replacement and deriving an expression for the temporal locality and popularity of the relevant tile to facilitate the replacement process. Based on the spatial characteristics of both the tiles and the cache burst mode with regard to reading data, the proposed method generates multiple tile sequences to reflect spatiotemporal locality in tile access patterns. Then, we measure the caching value by a technique based on a weighted-based method. This technique draws on the recent access popularity and low caching costs of tile sequences, with the aim of balancing the temporal and spatial localities in tile access. It ranks tile sequences in a replacement queue to adapt to the changes in accessed hotspots while reducing the replacement frequency. Experimental results show that the proposed method effectively improves the hit rate and utilization rate for a limited distributed cache while achieving satisfactory response performance and high throughput for users in an NGIS. Therefore, it can be adapted to handle numerous data access requests in NGISs in a cloud-based environment.

Community user access of a WebGIS is characterized by intensity and popularity.The requested geospatial data have the characteristics of spatial and temporal locality.This paper proposed an expression for the replacement feature by balancing spatial and temporal locality as well as long-term and short-term popularity in tile access to ensure that the replacement process can not only optimize global access but also adapt to the access pattern changes.Then, using the Hash function and linear linked chains to provide cooperative cache management in a heterogeneous cluster-based caching system speeds up the query and replacement process of tiles and improves the performance of the cluster-based cache service.Experimental results revealed that the proposed method obtained a higher cache hit rate and a good average response performance for a heterogeneous distributed cluster-based cache system, providing service to more users and thus increased its service capacity.

Cache replacement strategy is the core for a distributed high-speed caching system, and effects the cache hit rate and utilization of a limited cache space directly. Many reports show that there are temporal and spatial local changes in access patterns of geospatial data, and there are popular hot spots which change over time. Therefore, the key issue for cache replacement strategy for geospatial data is to get a combination method which considers both temporal local changes and spatial local changes in access patterns, and balance the relationship between the changes. And the cache replacement strategy should fit the distribution and changes of hotspot. This paper proposes a cache replacement strategy based on access pattern which have access spatiotemporal localities. Firstly, the strategy builds a method to express the access frequency and the time interval for geospatial data access based on a least-recently-used replacement (LRU) algorithm and its data structure; secondly, considering both the spatial correlation between geospatial data access and the caching location for geospatial data, it builds access sequences based on a LRU stack, which reflect the spatiotemporal locality changes in access pattern. Finally, for achieving the aim of balancing the temporal locality and spatial locality changes in access patterns, the strategy chooses the replacement objects based on the length of access sequences and the cost of caching resource consumption. Experimental results reveal that the proposed cache replacement strategy is able to improve the cache hit rate while achieving a good response performance and higher system throughput. Therefore, it can be applied to handle the intensity of networked GISs data access requests in a cloud-based environment.