SP²: spanner construction for shortest path computation on streaming graph

Computing shortest paths in graphs is one of the most fundamental and well-studied problem. It has a range of applications such as robot navigation, optimal pipelining of VLSI chip, traffic planning, and telecommunications messages routing. Many of these applications require to be solved by streaming data in real time, and recently new graph algorithmic techniques have been introduced to deal with such streaming data. This paper presents SPanner construction for Shortest Path computation (SP²) framework with three main operators C, U, and P-operator, which constructs the spanner for computation of shortest paths over a large graph stream. We compute three types of shortest paths like Single Source Shortest Path (SSSP), Single Pair Shortest Path (SPSP), and All Pairs Shortest Path (APSP) using the dynamic algorithm for constructing the spanner in small internal memory. We experimentally demonstrate and verify that this algorithm of SP² using real datasets. Therefore, it works significantly to reduce the time complexity for updating and processing query in response to dynamic changes, such as edge insertions and deletions in a graph.