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：最小生成树是图问题中一个研究充分的分支。尽管经典算法解决这些问题已有数十年历史，但新的变体与应用领域仍在不断涌现。然而，在处理大规模图问题时，内存限制往往成为瓶颈，尤其是在内存受限环境中使用这些经典方法时。本文提出一种对普里姆算法的改进方案，实验表明，该方案在解决最小生成树问题时，辅助内存使用量可降低90%以上，且误差率小于0.3%。