%0 Journal Article %1 srinivasan2018sharedmemory %A Srinivasan, S. %A Pollard, S. %A Das, S. K. %A Norris, B. %A Bhowmick, S. %D 2018 %J IEEE Transactions on Big Data %K algorithms dynamic_graphs graph_algorithms parallel_algorithms %P 1-1 %R 10.1109/TBDATA.2018.2870136 %T A Shared-Memory Algorithm for Updating Tree-Based Properties of Large Dynamic Networks %U https://ieeexplore.ieee.org/document/8464249 %X n this paper, we present a network-based template for analyzing large-scale dynamic data. Specifically, we present a novel shared-memory parallel algorithm for updating treebased structures, including connected components (CC) and the minimum spanning tree (MST) on dynamic networks. We propose a rooted tree-based data structure to store the edges that are most relevant to the analysis. Our algorithm is based on updating the information stored in this rooted tree.n this paper, we present a network-based template for analyzing large-scale dynamic data. Specifically, we present a novel shared-memory parallel algorithm for updating tree-based structures, including connected components (CC) and the minimum spanning tree (MST) on dynamic networks. We propose a rooted tree-based data structure to store the edges that are most relevant to the analysis. Our algorithm is based on updating the information stored in this rooted tree.I

@article{srinivasan2018sharedmemory, abstract = {n this paper, we present a network-based template for analyzing large-scale dynamic data. Specifically, we present a novel shared-memory parallel algorithm for updating treebased structures, including connected components (CC) and the minimum spanning tree (MST) on dynamic networks. We propose a rooted tree-based data structure to store the edges that are most relevant to the analysis. Our algorithm is based on updating the information stored in this rooted tree.n this paper, we present a network-based template for analyzing large-scale dynamic data. Specifically, we present a novel shared-memory parallel algorithm for updating tree-based structures, including connected components (CC) and the minimum spanning tree (MST) on dynamic networks. We propose a rooted tree-based data structure to store the edges that are most relevant to the analysis. Our algorithm is based on updating the information stored in this rooted tree.I}, added-at = {2019-09-12T19:30:07.000+0200}, author = {{Srinivasan}, S. and {Pollard}, S. and {Das}, S. K. and {Norris}, B. and {Bhowmick}, S.}, biburl = {https://www.bibsonomy.org/bibtex/20f61cca54894fc8bdbb9147d4cfd6f6b/peter.ralph}, doi = {10.1109/TBDATA.2018.2870136}, interhash = {79b78b15bc0accec38bcc22878fd1c33}, intrahash = {0f61cca54894fc8bdbb9147d4cfd6f6b}, journal = {IEEE Transactions on Big Data}, keywords = {algorithms dynamic_graphs graph_algorithms parallel_algorithms}, pages = {1-1}, timestamp = {2019-09-12T19:30:07.000+0200}, title = {A Shared-Memory Algorithm for Updating Tree-Based Properties of Large Dynamic Networks}, url = {https://ieeexplore.ieee.org/document/8464249}, year = 2018 }