  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%.
