A Dynamic Load-Balancing Policy with a Central Job Dispatcher (LBC)
IEEE Transactions on Software Engineering
Load Balancing Problems for Multiclass Jobs in Distributed/Parallel Computer Systems
IEEE Transactions on Computers
Load Balancing in Distributed Systems: An Approach Using Cooperative Games
IPDPS '02 Proceedings of the 16th International Symposium on Parallel and Distributed Processing
Dynamic Load Balancing for Multiple Processors
RTCSA '06 Proceedings of the 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Efficient Data Migration in Self-managing Storage Systems
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
Dynamic Data Migration Policies for Query-Intensive Distributed Data Environments
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
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Modern large distributed applications, such as mobile communications and banking services, require fast responses to enormous and frequent query requests. This kind of application usually employs in a distributed query-intensive data environment, where the system response time significantly depends on ways of data distribution. Motivated by the efficiency need, we develop two novel strategies: a static data distribution strategy DDH and a dynamic data reallocation strategy DRC to speed up the query response time through load balancing. DDH uses a hash-based heuristic technique to distribute data off-line according to the query history. DRC can reallocate data dynamically at runtime to adapt the changing query patterns in the system. To validate the performance of these two strategies, experiments are conducted using a simulation environment and real customer data. Experimental results show that they both offer favorable performance with the increasing query load of the system.