Graph partitioning is a common solution to scale up the graph algorithms, and shortest path (SP) computation is one of them. However, the existing solutions typically have a fixed partition method with a fixed path index and fixed partition structure, so it is unclear how the partition method and path index influence the pathfinding performance. Moreover, few studies have explored the index maintenance of partitioned SP (PSP) on dynamic graphs. To provide a deeper insight into the dynamic PSP indexes, we systematically deliberate on the existing works and propose a universal scheme to analyze this problem theoretically. Specifically, we first propose two novel partitioned index strategies and one optimization to improve index construction, query answering, or index maintenance of PSP index. Then we propose a path-oriented graph partitioning classification criteria for easier partition method selection. After that, we re-couple the dimensions in our scheme (partitioned index strategy, path index, and partition structure) to propose five new partitioned SP indexes that are more efficient either in the query or update on different networks. Finally, we demonstrate the effectiveness of our new indexes by comparing them with state-of-the-art PSP indexes through comprehensive evaluations.

翻译：图分区是扩展图算法规模的常见解决方案，最短路径计算便是其中之一。然而，现有解决方案通常采用固定的分区方法、固定的路径索引和固定的分区结构，因此分区方法与路径索引对寻路性能的影响尚不明确。此外，鲜有研究探讨动态图上分区最短路径索引的维护问题。为深入理解动态分区最短路径索引，我们系统梳理了现有工作，并提出一种通用方案来理论分析该问题。具体而言，我们首先提出两种新颖的分区索引策略及一项优化，以改善分区索引的构建、查询回答或维护性能。随后提出一种面向路径的图分区分类准则，便于更简便地选择分区方法。在此基础上，我们将方案中的维度（分区索引策略、路径索引与分区结构）重新组合，提出五种新的分区最短路径索引，分别在不同网络上的查询或更新过程中具有更高效率。最后，通过综合评估与现有最先进分区最短路径索引的对比，验证了新索引的有效性。