TY - JOUR
ID - 71809
TI - Estimation of Network Reliability for a Fully Connected Network with Unreliable Nodes and Unreliable Edges using Neuro Optimization
JO - International Journal of Engineering
JA - IJE
LA - en
SN - 1025-2495
AU - Bhardwaj, Diwakar
AU - Jain, Sandeep
AU - Singh, Manu Pratap
AD - Computer Engineering, , GLA Institute of Technology and Management, Math
AD - Computer Engineering, Institute of Basic science
AD - ICIS, Dr. B.R.Ambedkar University
Y1 - 2009
PY - 2009
VL - 22
IS - 4
SP - 317
EP - 332
KW - Network Reliability
KW - Neural Optimization
KW - Simulated Annealing
KW - Hopfield Model
DO -
N2 - In this paper it is tried to estimate the reliability of a fully connected network of some unreliable nodes and unreliable connections (edges) between them. The proliferation of electronic messaging has been witnessed during the last few years. The acute problem of node failure and connection failure is frequently encountered in communication through various types of networks. We know that a network can be defined as an undirected graph N(V,E). It is believed that in a network the nodes as well as the connections can fail and hence can cause unsuccessful communication. So, it is important to estimate the network reliability to encounter the network failure. Various tools have been used to estimate the reliability of various types of networks. In this paper we are considering the approach of neuro optimization for estimating the network reliability. We use the simulation annealing to estimate the probabilities of various nodes in the network and Hopfield model to calculate the energies of these nodes at various thermal equilibriums. The state of the minimum energy represents the maximum reliability state of the network.
UR - https://www.ije.ir/article_71809.html
L1 - https://www.ije.ir/article_71809_15e3346259182399ddf28d1387aa8d0a.pdf
ER -