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Detecting Communities by Revised max-flow Method in Networks

Communications in Theoretical Physics 2013年第8期60卷 258-262页

作者：刘传建朱志强吴建良 School of Mathematics Shandong University

A ubiquitous phenomenon in networks is the presence of communities within which the network connections are dense and between which they are *** paper proposes a max-flow algorithm in bipartite networks to detect communities in general ***,we construct a bipartite network in accordance with a general network and derive a revised max-flow problem in order to uncover the community *** we present a local heuristic algorithm to find the optimal solution of the revised max-flow *** method is applied to a variety of real-world and artificial complex networks,and the partition results confirm its effectiveness and accuracy.

关键词： community structure max-flow bipartite network

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Analyzing History Quality for Routing Purposes in Opportunistic Network Using max-flow

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Wireless Engineering and Technology 2012年第3期3卷 132-141页

作者： Muhammad Arshad Islam Marcel Waldvogel Distributed Systems Laboratory University of Konstanz Konstanz Germany Faculty of Computer Sciences and Engineering GIK Institute Topi Pakistan

Most of the existing opportunistic network routing protocols are based on some type of utility function that is directly or indirectly dependent on the past behavior of devices. The past behavior or history of a device is usually referred to as contacts that the device had in the past. Whatever may be the metric of history, most of these routing protocols work on the realistic premise that node mobility is not truly random. In contrast, there are several oracles based methods where such oracles assist these methods to gain access to information that is unrealistic in the real world. Although, such oracles are unrealistic, they can help to understand the nature and behavior of underlying networks. In this paper, we have analyzed the gap between these two extremes. We have performed max-flow computations on three different opportunistic networks and then compared the results by performing max-flow computations on history generated by the respective networks. We have found that the correctness of the history based prediction of history is dependent on the dense nature of the underlying network. Moreover, the history based prediction can deliver correct paths but cannot guarantee their absolute reliability.

关键词： Opportunistic Networks Delay Tolerant Networks Routing Protocols max-flow Simulation Modified Dijk-Stra Algorithm

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Two-stage controlled islanding strategy based on Stoer-Wagner and improved Dinic algorithms

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Journal of Modern Power Systems and Clean Energy 2016年第3期4卷 454-466页

作者： Fei TANG Jun JIA Lei CHEN Zheng ZHU Jiale LIU Qinfen LIAO Dichen LIU School of Electrical Engineering Wuhan UniversityWuhan 430072China Electric Power Research Institute of Jiangsu Electric Power Company Nanjing 211103China

The controlled islanding for the power system is an effective method to deal with the emergent situations caused by large disturbances. The size of the solution space would increase exponentially as the scale of the power grid increases. The goal of our controlled islanding strategy is to divide the system into several islands quickly. Meanwhile, the generator coherency and the power-flow disruption have to be taken into consideration carefully. This paper proposed a two-stage fast islanding strategy for large power networks, which is on the basis of large power grid graph theories. In the first stage, the Stoer-Wagner algorithm is employed to obtain the grouping cluster of coherent generators in the dynamic undirected liaison graph. In the second stage, the improved Dinic max-flow method is proposed to search the optimal splitting boundary so as to acquire the minimum power flow impact. Our two-stage islanding strategy does not need to reduce the whole power network. Simulations on IEEE 118-bus and162-bus power systems showed that the proposed strategy can acquire high quality solutions effectively and efficiently.

关键词： Controlled islanding Non-deterministic polynomial hard problem Stoer-Wagner max-flow Partition boundary

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