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Efficient Semi-External SCC Computation
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DOI：10.1109/TKDE.2021.3138994.png)
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In literature, many algorithms are proposed to find strongly connected components (SCC) for directed graphs. Specifically, a SCC of a directed graph G is one of its maximal subgraphs, in which any two nodes are reachable to each other. Existing in-memory algorithms are efficient, and can find all the SCCs of G in a linear time, with respect to the size of G. Nevertheless, as the sizes of graphs grow rapidly in real applications, current efforts have been focused on semi-external algorithms. Existing semi-external algorithms maintain an in-memory sketch A of G, and gradually restructure A with their in-memory processes (IMP) until all the SCCs can be computed based on A. However, the I/O and CPU costs of existing algorithms are still high when G is relatively large. Thus, this paper proposes a new semi-external algorithm EP-SCC with a novel IMP EP-Reduction for finding all the SCCs of G efficiently. Extensive experiments are conducted on both synthetic and real graphs, in which WDC-2014 contains 1.7 billion nodes, and eu-2015 has over 91 billion edges. Experimental results confirm that EP-SCC significantly outperforms existing semi-external SCC algorithms.
Keyword:
Computational modeling
Memory management
Costs
Directed graphs
Optimization methods
Arrays
Vegetation
Strongly connected component
semi-external memory
graph algorithm
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10.4
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6.9K
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3.2W
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