Simultaneous optimization and evaluation of multiple dimensional queries
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Locality-aware request distribution in cluster-based network servers
Proceedings of the eighth international conference on Architectural support for programming languages and operating systems
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
On the Multiple-Query Optimization Problem
IEEE Transactions on Knowledge and Data Engineering
Common Subexpression Processing in Multiple-Query Processing
IEEE Transactions on Knowledge and Data Engineering
Semantic Caching and Query Processing
IEEE Transactions on Knowledge and Data Engineering
Multiple Query Optimization for Data Analysis Applications on Clusters of SMPs
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
Scalable Spatio-temporal Continuous Query Processing for Location-aware Services
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Query planning for the grid: adapting to dynamic resource availability
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Scalable content-aware request distribution in cluster-based networks servers
ATEC '00 Proceedings of the annual conference on USENIX Annual Technical Conference
Multiple query scheduling for distributed semantic caches
Journal of Parallel and Distributed Computing
Special issue for data intensive eScience
Distributed and Parallel Databases
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In distributed scientific query processing systems, leveraging distributed cached data is becoming more important. In such systems, a front-end query scheduler distributes queries among many application servers rather than processing queries in a few high-performance workstations. Although many query scheduling policies exist such as round-robin and load-monitoring, they are not sophisticated enough to exploit cached results as well as balance the workload. Efforts were made to improve the query processing performance using statistical methods such as exponential moving average. However, existing methods have limitations for certain query patterns: queries with hotspots, or dynamic query distributions. In this paper, we propose novel query scheduling policies that take into account both the contents of distributed caching infrastructure and the load balance among the servers. Our experiments show that the proposed query scheduling policies outperform existing policies by producing better query plans in terms of load balance and cache-hit ratio.