The massive amount of data and large variety of data distributions in the big data era call for access methods that are efficient in both query processing and index management, and over both practical and worst-case workloads. To address this need, we revisit two classic multidimensional access methods—the R-tree and the space-filling curve. We propose a novel R-tree packing strategy based on space-filling curves. This strategy produces R-trees with an asymptotically optimal I/O complexity for window queries in the worst case. Experiments show that our R-trees are highly efficient in querying both real and synthetic data of different distributions. The proposed strategy is also simple to parallelize, since it relies only on sorting. We propose a parallel algorithm for R-tree bulk-loading based on the proposed packing strategy and analyze its performance under the massively parallel communication model. To handle dynamic data updates, we further propose index update algorithms that process data insertions and deletions without compromising the optimal query I/O complexity. Experimental results confirm the effectiveness and efficiency of the proposed R-tree bulk-loading and updating algorithms over large data sets.
Abstract. Aiming at the problems existing on the expression of atmospheric pollution dispersion, a data model of state-oriented and object-oriented hybrid modeling is designed. The model supports true three-dimensional grid representation and cellular automata deduction, and can combine the calculation and deduction of atmospheric pollution to improve the accuracy and efficiency of the model. The simulation experiments of single source and multi-source pollutants are carried out. The results show that: the model conforms to the diffusion law of atmospheric pollution. The pollutant concentration at any time, section or space in the whole diffusion process can be calculated and expressed dynamically, which improves the accuracy, rapidity, intuitiveness and analysation of the deduction of atmospheric pollutant diffusion process.
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