PROJECT TITLE :

A Computationally Efficient Connectivity Index for Weighted Directed Graphs With Application to Underwater Sensor Networks

ABSTRACT:

The global connectivity of complex networks that have random links is the topic of investigation in this paper. For the purpose of modeling the network, an expected communication graph with weighted edges has been utilized. It is well established that the concept of weighted vertex connectivity (WVC), which was initially introduced in the body of research as a generalization of the concept of vertex connectivity, is capable of accurately measuring the connectivity of networks of this kind. In spite of this, a numerically efficient approximate measure for the WVC is preferable because of the complexity of the computation involved in calculating it. In this paper, an approximation to the WVC that runs in polynomial time is derived. This approximation is less conservative than the one that was introduced earlier as an approximate measure. It has been demonstrated that the proposed approximation is identical to the WVC under certain conditions. [Citation needed] The usefulness of the proposed measure was demonstrated by the results of the simulation.