Efficient computation of distance labeling for decremental updates in large dynamic graphs

Abstract

Since today's real-world graphs, such as social network graphs, are evolving all the time, it is of great importance to perform graph computations and analysis in these dynamic graphs. Due to the fact that many applications such as social network link analysis with the existence of inactive users need to handle failed links or nodes, decremental computation and maintenance for graphs is considered a challenging problem. Shortest path computation is one of the most fundamental operations for managing and analyzing large graphs. A number of indexing methods have been proposed to answer distance queries in static graphs. Unfortunately, there is little work on answering such queries for dynamic graphs. In this paper, we focus on the problem of computing the shortest path distance in dynamic graphs, particularly on decremental updates (i.e., edge deletions). We propose maintenance algorithms based on distance labeling, which can handle decremental updates efficiently. By exploiting properties of distance labeling in original graphs, we are able to efficiently maintain distance labeling for new graphs. We experimentally evaluate our algorithms using eleven real-world large graphs and confirm the effectiveness and efficiency of our approach. More specifically, our method can speed up index re-computation by up to an order of magnitude compared with the state-ofthe-art method, Pruned Landmark Labeling (PLL).

Scaling Distance Labeling on Small-World Networks

“…For the distance label maintenance under edge insertion, existing technique [4] fails in eliminating the outdated labels and thus breaks the minimal property of PLL. For the distance label maintenance under edge deletion, existing approach [22] needs to conduct BFS from affected nodes and the speedup over the baseline of recomputing all the labels is thus marginal (up to one order of magnitude). Due to the challenges to maintain the PLL index, it is non-trivial to extend PSL to handle dynamic graphs using multiple cores.…”

Towards Real-Time Counting Shortest Cycles on Dynamic Graphs: A Hub Labeling Approach

“…Dynamic Maintenance for 2-hop Labeling: To adapt to the dynamic update of the network, some works [30], [37], [38] proposed dynamic algorithms to deal with edge insertion and deletion. For the edge insertion, a partial BFS for each affected hub is started from one of the inserted-edge endpoints and creates a label when finding the tentative distance is shorter than the query answer from the previous index.…”

Efficient Maintenance of Highway Cover Labelling for Distance Queries on Large Dynamic Graphs

“…Note that, in case of decremental updates, outdated and redundant distance entries must be removed; otherwise distance labelling cannot be correctly updated. To tackle the problem of maintaining 2-hop cover distance labelling for decremental updates, Qin et al [8] proposed a method using the well-ordering property of 2-hop cover distance labelling. However, this method is inefficient to perform updates for even moderately large graphs and can only scale to graphs that have a few millions of vertices and edges.…”

“…Fig. 1 Performance overview of our proposed method ParDHL and the state-of-the-art methods DecM [8], DecPLL [9], DecFD [10] and DecHL [11] for processing 1,000 edge deletions.…”