Eccentric connectivity index has been found to have a low degeneracy and hence a significant potential of predicting biological activity of certain classes of chemical compounds. We present here explicit formulas for eccentric connectivity index of various families of graphs. We also show that the eccentric connectivity index grows at most polynomially with the number of vertices and determine ...

Let G be a connected graph and S be a set of vertices. The h-extra connectivity of G is the cardinality of a minimum set S such that G − S is disconnected and each component of G− S has at least h + 1 vertices. The h-extra connectivity is an important parameter to measure the reliability and fault tolerance ability of large interconnection networks. The h-extra connectivity for h = 1, 2 of k-ar...

Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic...

The h-super connectivity κh and the h-super edge-connectivity λh are more refined network reliability indices than the connectivity and the edge-connectivity. This paper shows that for a connected balanced digraph D and its line digraph L, if D is optimally super edge-connected, then κ1(L) = 2λ1(D), and that for a connected graph G and its line graph L, if one of κ1(L) and λ2(G) exists, then κ1...

In Mobile Ad hoc Networks (MANET), reliability in real time data transmission can be assured by confirming the connectivity of the network. Since, MANETs are characterized by dynamic topology changes; the established connection must be monitored for its consistency. In order to provide and maintain connectivity, in this paper, we propose a reliable real time data transmission technique in MANET...

Parcellating the brain into a set of distinct subregions is an essential step for building and studying brain connectivity networks. Connectivity driven parcellation is a natural approach, but suffers from the lack of reliability of connectivity data. Combining modalities in the parcellation task has the potential to yield more robust parcellations, yet hasn’t been explored much. In this paper,...

Fuzzy incidence graphs can be used as models for nondeterministic interconnection networks having extra node-edgerelationships. For example, ramps in a highway system may be modeled as a fuzzy incidence graph so that unexpectedflow between cities and highways can be effectively studied and controlled. Like node and edge connectivity in graphs,node connectivity and arc connectivity in fuzzy inci...

TINA aims to provide an architecture to enable telecommunications networks to support the flexible introduction of new, advanced services and to manage both the services and the network in an integrated fashion. While the specifications in the TINA Service Architecture are well advanced, network management aspects are less well defined. Resource Configuration Management is one of the most impor...

Structural connectivity models hold great promise for expanding what is known about the ways information travels throughout the brain. The physiologic interpretability of structural connectivity models depends heavily on how the connections between regions are quantified. This article presents an integrated structural connectivity framework designed around such an interpretation. The framework ...

The hypercube Qn is one of the most popular interconnection networks with high symmetry. To reduce diameter Qn, many variants have been proposed, such as n-dimensional locally twisted cube LTQn. further optimize LTQn, folded FLTQn which built based on LTQn by adding 2n−1 complementary edges. Connectivity an important indicator to measure fault tolerance and reliability a network. However, conne...