Fine-tuning of k in a K-fold Multicast Network with Finite Queue using Markovian Model

Multicast has brought a drastic change in the field of networking by offering bandwidth effectivetechnology that leads to reduce tariff. It is popular for optimizing network performances. This paperevaluated a model for fine tuning the value of a k in a K-fold multicast network under different traffic loadsunder poisson traffic with finite queue at each node. Stationary distribution has been derived for thenetwork states and various expressions have been developed for the network to determine throughput andthe blocking probability of the network. It has been established from this research work that by increasingthe fold number, the network throughput can be increased very fast. However, it has been also observedthat after increasing the fold number up to a certain value, the blocking probability stops to increase andbecomes constant. We have also noticed that the throughput increases with the increase of the offeredtraffic and the blocking probability decreases when the system parameter k is increased. Moreover, anoptimum value of k ceases the blocking probability for a particular value of the offered traffic for finetuningthe outcome of the network.