Most researches about complex networks are single-layer networks-based representation. However, in most cases, systems in the real world are not isolated but connective. In this paper, different from the traditional O...
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ISBN:
(纸本)9789811366215;9789811366208
Most researches about complex networks are single-layer networks-based representation. However, in most cases, systems in the real world are not isolated but connective. In this paper, different from the traditional Open System Interconnection (OSI) model, our research pays attention to application service layer and network control layer for the view of application. Two layers connect with each other by using IP mapping relationship. Firstly, to avoid unnecessary loss of computational efficiency, we modify Louvain algorithm to divide the nodes in network control layer into several parts. Secondly, we add additional community attractive force and introduce Barnes-Hut force-calculation model to fruchterman-Reingold algorithm in order to make nodes in network control layer aligned more structured and well-distributed efficiently. Finally, we merge the application service layer and the network control layer into a two-layer visualization model. Based on our two-layer model, the whole network trend, topology and incidence relation can be conveniently grasped.
To acquire the network topology which is complex, unknown and continually changed, automatic discovery and automatic layout can be the best reliable and effective ways. Because of the huge number of nodes, connections...
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ISBN:
(纸本)9780769537450
To acquire the network topology which is complex, unknown and continually changed, automatic discovery and automatic layout can be the best reliable and effective ways. Because of the huge number of nodes, connections, and circles in backbone network, the Force-directed Placement model which is form the physical system is brought in to optimize visualization. In this model, network topology is auto-layout by random initiation and iterative adjustments. The fr (fruchterman and Reingold) algorithm is improved to make the algorithm more suitable for backbone network topology auto-layout. By reevaluated the force function, the types and numbers of nodes can be identified for dynamic configuration. The placement can be edited and partly locked, and the crowded nodes are controlled in practice. The improvements and optimizations make it more available and adaptive in various networks. All the experimental data are derived from automatic discovery, which are authentic and practical.
The MOV and fr algorithms, which are representative attacks on elliptic curve cryptosystems, reduce the elliptic curve discrete logarithm problem (ECDLP) to the discrete logarithm problem in a finite field. This paper...
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The MOV and fr algorithms, which are representative attacks on elliptic curve cryptosystems, reduce the elliptic curve discrete logarithm problem (ECDLP) to the discrete logarithm problem in a finite field. This paper studies these algorithms and introduces the following three results. First, we show an explicit condition under which the MOV algorithm can be applied to non-supersingular elliptic curves. Next, by comparing the effectiveness of the MOV algorithm to that of the fr algorithm, it is explicitly shown that the condition needed for the MOV algorithm to be subexponential is the same as that for the fr algorithm except for elliptic curves of trace two. Finally, a new explicit reduction algorithm is proposed for the ECDLP over elliptic curves of trace two. This algorithm differs from a simple realization of the fr algorithm. Furthermore, pie show, by experimental results, that the running time of the proposed algorithm is shorter than that of the original fr algorithm.
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