The efficient design of membership function has a positive impact on the performance of fuzzy decision-making process.
The proposed protocol works by identifying groups using an efficient distributed group membership protocol, and then routing at the group level, rather than at the node level.
We have also used computationally efficient triangular functions as membership functions.
In order to determine a set of weights of each term in the objective function, the simplest and most efficient form of triangular membership functions has been considered.
As we have just seen, such assignments are based on the time or space complexity of the most efficient algorithms by which membership in a problem can be decided.
In order to determine a set of weights of objective function to represent the relative importance of each term, the simplest and most efficient form of triangular membership functions has been considered.
In order to determine a set of weights of objective function representing the relative importance of each term, the simplest and most efficient form of triangular membership functions have been employed.
Further, this paper also proposes an extended CGKD protocol based on clustered tree which is very scalable and efficient to deal with enormous membership changes.
