Content-based Multimedia Data Retrieval on Heterogeneous System Environment
نویسندگان
چکیده
In this paper, we propose a static data partitioning scheme for content-based multimedia data retrieval using a heterogeneous cluster system. Multimedia data is represented by unified k-tree structure of kdimensional(k-d) signals proposed in [6]. Each dimension of k-d data is separated into small blocks and then formed into a hierarchical multidimensional tree structure, called a k-tree. The parallel version of k-tree model was introduced in [7]. The previous experimental results show the huge reduction of retrieval time on a cluster of homogeneous workstations. In this paper, we extend our parallel model to a heterogeneous cluster system environment, by taking into consideration the system characteristics such as computational time, input/output time, available storage, and communication latency. The experiments of the model with load balancing shows a significant reduction of retrieval time while maintaining the quality of perceptual results.
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