论文标题
通用Dijkstra算法的经验时间复杂性
Empirical Time Complexity of Generic Dijkstra Algorithm
论文作者
论文摘要
通用Dijkstra是一种新颖的算法,用于在波长分割多路复用网络(WDM)和弹性光学网络(EON)中找到最佳最短路径,声称可以极大地胜过已知算法。由于它的新颖性,它没有被独立实施和验证。它的时间复杂性也是未知的。在本文中,我们执行运行时分析,并证明通用Dijkstra运行时间随图形顶点的数量而二次增长,并且与边缘单元的数量进行对数。我们还发现,网络利用功能中通用Dijkstra算法的运行时间不是单调的,因为峰值运行时间约为0.25网络利用率。此外,我们在Python语言中提供了独立的开源Dijkstra的开源实施。我们确认算法的正确性及其出色的性能。与过滤的图算法相比,通用Dijkstra在25至500个节点的网络中的速度约为2.3倍,而在90%的调用中,其计算时间较少。
Generic Dijkstra is a novel algorithm for finding the optimal shortest path in both wavelength-division multiplexed networks (WDM) and elastic optical networks (EON), claimed to outperform known algorithms considerably. Because of its novelty, it has not been independently implemented and verified. Its time complexity also remains unknown. In this paper, we perform run-time analysis and show that Generic Dijkstra running time grows quadratically with the number of graph vertices and logarithmically with the number of edge units. We also discover that the running time of the Generic Dijkstra algorithm in the function of network utilization is not monotonic, as peak running time is at approximately 0.25 network utilization. Additionally, we provide an independent open source implementation of Generic Dijkstra in the Python language. We confirm the correctness of the algorithm and its superior performance. In comparison to the Filtered Graphs algorithm, Generic Dijkstra is approximately 2.3 times faster in networks with 25 to 500 nodes, and in 90% of calls its computation takes less time.