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A Study on Rapid Incremental Maximum Flow Algorithm in Dynamic Network

机译:动态网络中快速增量最大流量算法的研究

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Maximum flow is a key measurement for the capacity of a flow network. When malfunction or damage occurs in branches of a dynamic network, it is urgent in many applications to identify whether the damaged network is still able to transfer demanded flow d. Obviously, recalculating maximum flow in the new network with the traditional algorithm is not a recommended solution for its higher time-complexity. As is known, in many existing maximum flow algorithms, the search for augmenting paths is critical but highly time-consuming. Thus, this paper proposes an incremental maximum flow algorithm based on augmented routing tree (IMFA_ART), directly producing augmenting paths without complex calculation. The algorithm caches the information of simple paths during calculating maximum flow in the original network. The cached data will be utilized to get the augmenting paths whenever network topology changes, without any complex calculation in residual network. In addition, in order to avoid traversing those invalid simple paths that contain saturated edges, an augmented routing tree is proposed to index all simple paths. With the aid of this tree, the next augmenting paths can be found sequentially to achieve maximum flow by traversing from the root to a leaf. The time complexity is determined by the height of ART, which is far less than the number of augmenting paths. Therefore, the algorithm performance can be improved significantly. Experiments show that IMFA_ART has greater advantage in time performance over Dinic, the most famous maximum flow algorithm.
机译:最大流量是衡量流量网络容量的关键指标。当在动态网络的分支中发生故障或损坏时,在许多应用中迫切需要确定损坏的网络是否仍然能够传输所需的流量d。显然,不建议使用传统算法在新网络中重新计算最大流量,因为它具有较高的时间复杂性。众所周知,在许多现有的最大流量算法中,寻找增加路径是至关重要的,但是非常耗时。因此,本文提出了一种基于增强路由树(IMFA_ART)的增量最大流量算法,该算法无需复杂的计算即可直接生成增强路径。该算法在计算原始网络中的最大流量时会缓存简单路径的信息。每当网络拓扑发生变化时,缓存的数据将用于获取扩展路径,而无需在残留网络中进行任何复杂的计算。另外,为了避免遍历那些包含饱和边的无效简单路径,提出了一种增强的路由树来索引所有简单路径。借助该树,可以依次找到下一个增强路径,以通过从根到叶的遍历实现最大流量。时间复杂度由ART的高度决定,ART的高度远小于增强路径的数量。因此,可以显着提高算法性能。实验表明,与最著名的最大流量算法Dinic相比,IMFA_ART在时间性能方面具有更大的优势。

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