A network data analytics system visualized as a temporal graph (network state as a function of time)in which unbounded streams of data are processed and stored can result in the data size becoming extra-ordinarily large and unmanageable. Thus, efficient partitioning schemes are often needed to partition the data. In some instances, data in a temporal graph system can be partitioned either temporally or spatially. This proposal provides techniques to facilitate partitioning (both temporally and spatially)and persistence of data based on the application intent.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.