Local Fractional Strong Metric Dimension of Certain Rotationally Symmetric Planer Networks

Fractional versions of metric based networks invariants widen the scope of application in fields of intelligent systems, computer science and chemistry including, robot navigation, sensor networking, linear optimization problems, scheduling, assignment, operation research problems, image processing and drug discovery. It plays vital role in the study to check structural properties of the networks such as complexity, modularity and accessibility. Rotationally symmetric and planer networks have key importance in the fields of robot navigation, networking, telecommunication and chemistry due the structure of these networks which help in optimal rate of data transfer and minimize the time taken and resources used. In this paper we introduce a combinatorial technique to compute local fractional strong metric dimension (LFSMD) of networks. The technique is further used to compute LFSMD of certain rotationally symmetric planer networks.