Minimum Spanning Trees are a well-studied subset of graph problems. While classical algorithms have existed to solve these problems for decades, new variations and application areas are constantly being discovered. When dealing with large graph problems, however, memory constraints can often be limiting, especially when using these classical methods in memory restricted environments. In this work, we propose an augmentation of Prim's algorithm that can be empirically shown to solve MST problems with a reduction in auxiliary memory usage of over 90%, and a margin of error of less than 0.3%.

翻译：最小生成树是图论问题中一个研究较为充分的分支。尽管解决这些问题的经典算法已存在数十年，但新的变体和应用领域仍不断被发现。然而，在处理大规模图问题时，内存约束常常成为限制因素，尤其是在内存受限环境中使用这些经典方法时。在本研究中，我们提出了一种对普里姆算法的增强方案，实验表明，该方案能够将求解最小生成树问题所需的辅助内存使用量降低超过90%，同时误差率小于0.3%。