The LRU-K page replacement algorithm for database disk buffering
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
The PYRAMID system for multiscale raster analysis
Computers & Geosciences
The COMFORT automatic tuning project
Information Systems
Middle-tier database caching for e-business
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Adaptive Load Balancing in Disk Arrays
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Prefetching Tiled Internet Data Using a Neighbor Selection Markov Chain
IICS '01 Proceedings of the International Workshop on Innovative Internet Computing Systems
Caching Technologies for Web Applications
Proceedings of the 27th International Conference on Very Large Data Bases
Proceedings of the 27th International Conference on Very Large Data Bases
2Q: A Low Overhead High Performance Buffer Management Replacement Algorithm
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Semantic Data Caching and Replacement
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
ADBIS '01 Proceedings of the 5th East European Conference on Advances in Databases and Information Systems
Adaptation of a Neighbor Selection Markov Chain for Prefetching Tiled Web GIS Data
ADVIS '02 Proceedings of the Second International Conference on Advances in Information Systems
MTCache: Transparent Mid-Tier Database Caching in SQL Server
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Caching with "good enough" currency, consistency, and completeness
VLDB '05 Proceedings of the 31st international conference on Very large data bases
ARC: A Self-Tuning, Low Overhead Replacement Cache
FAST '03 Proceedings of the 2nd USENIX Conference on File and Storage Technologies
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Hotmap: Looking at Geographic Attention
IEEE Transactions on Visualization and Computer Graphics
Self-tuning database systems: a decade of progress
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Scalable query result caching for web applications
Proceedings of the VLDB Endowment
On-Line Index Selection for Shifting Workloads
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
An adaptive neural network-based method for tile replacement in a web map cache
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part I
A prefetching model based on access popularity for geospatial data in a cluster-based caching system
International Journal of Geographical Information Science
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Public geospatial services are now commonly available on the Web. These services often render maps to users by dividing the maps into tiles. Given that geospatial services experience significant user load, it is desirable to pre-compute tiles at a time of low load in order to increase overall performance. Based on our analysis of the request log of a public geospatial service provider, we observe that times of low load occur with a periodic pattern. In addition, our analysis shows that tile access patterns exhibit strong spatial skew. Based on these observations, we propose an adaptive strategy restricting the set of tiles that are pre-computed to fit the low load time window. Ideally, the restricted tile set should deliver performance comparable to the full tile set. To achieve this result, tiles should be selected based on their expected popularity. Our key observation is that the popularity of a tile can be estimated by analyzing the tiles that users have previously requested. Our adaptive strategy constructs heatmaps of previous requests and uses this information to decide which tiles to pre-compute. We examine two alternative heuristics, one of which exploits that nearby tiles have a high likelihood of having similar popularity. We evaluate our methods against a real production workload, and observe that the latter heuristic achieves a 25% increase in the hit ratio compared to current methods, without pre-computing a larger set of tiles.