PROJECT TITLE :

Towards Optimal Connectivity on Multi- layered Networks - 2017

ABSTRACT:

Networks are prevalent in several high impact domains. Moreover, cross-domain interactions are frequently observed in many applications, which naturally type the dependencies between different networks. Such reasonably highly coupled network systems are called multi-layered networks, and are used to characterize numerous complicated systems, together with essential infrastructure networks, cyber-physical systems, collaboration platforms, biological systems, and many more. Completely different from single-layered networks where the functionality of their nodes is especially tormented by among-layer connections, multi-layered networks are additional susceptible to disturbance as the impact will be amplified through cross-layer dependencies, leading to the cascade failure to the complete system. To manipulate the connectivity in multi-layered networks, some recent ways are proposed primarily based on two-layered networks with specific sorts of connectivity measures. During this paper, we have a tendency to address the above challenges in multiple dimensions. 1st, we have a tendency to propose a family of connectivity measures (SUBLINE) that unifies a wide range of classic network connectivity measures. Third, we have a tendency to reveal that the connectivity measures in the SUBLINE family enjoy diminishing returns property, that guarantees a close to-optimal resolution with linear complexity for the connectivity optimization drawback. Finally, we tend to evaluate our proposed algorithm on real information sets to demonstrate its effectiveness and potency.


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