Evolutionary Algorithms for Allocating Data in Distributed Database Systems
Distributed and Parallel Databases
Computers and Operations Research
IEEE Transactions on Knowledge and Data Engineering
Active Gateway: A Facility for Video Conferencing Traffic Control
COMPSAC '97 Proceedings of the 21st International Computer Software and Applications Conference
Document replication and distribution in extensible geographically distributed web servers
Journal of Parallel and Distributed Computing - Scalable web services and architecture
Static and adaptive distributed data replication using genetic algorithms
Journal of Parallel and Distributed Computing
A Powerful Direct Mechanism for Optimal WWW Content Replication
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Comparison and analysis of ten static heuristics-based Internet data replication techniques
Journal of Parallel and Distributed Computing
A vertical partitioning algorithm for distributed multimedia databases
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Document replication strategies for geographically distributed web search engines
Information Processing and Management: an International Journal
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A major cost in retrieving multimedia data from multiple sites is the cost incurred in transferring multimedia data objects (MDOs) from different sites to the site where the query is initiated. The objective of a data allocation algorithm is to locate the MDOs at different sites so as to minimize the total data transfer cost incurred in executing a given set of queries. The optimal allocation of MDOs depends on the query execution strategy employed by a distributed multimedia system while the query execution strategy optimizes a query based on this allocation. We fix the query execution strategy and develop a site-independent MDO dependency graph representation to model the dependencies among the MDOs accessed by a query. Given the MDO dependency graphs as well as the set of multimedia database sites, data transfer costs between the sites, the allocation limit on the number of MDOs that can be allocated at a site, and the query execution frequencies from the sites, an allocation scheme is generated. We formulate the data allocation problem as an optimization problem. We solve this problem with a number of techniques that broadly belong to three classes: max-flow min-cut, state-space search, and graph partitioning heuristics. The max-flow min-cut technique formulates the data allocation problem as a network-flow problem, and uses a hill-climbing approach to try to find the optimal solution. For the state-space search approach, the problem is solved using a best-first search algorithm. The graph partitioning approach uses two clustering heuristics, the agglomerative clustering and divisive clustering. We evaluate and compare these approaches, and assess their cost-performance trade-offs. All algorithms are also compared with optimal solutions obtained through exhaustive search. Conclusions are also made on the suitability of these approaches to different scenarios