A Dynamic Multi-cast Routing Algorithm for Opportunistic Networks:   Implementing the Expected Transmission Count Metric
  Cognitive radio (CR) technology enables an intelligent wireless communication system. CR provides an efficient solution for the inefficient spectrum utilization by allowing dynamic and opportunistic spectrum access. In designing CR networks, the main challenge is how to increase network throughput while protecting the performance of licensed primary radio networks (PRNs) and keeping the interference between primary users (PUs) and cognitive users (CUs) within a prescribed threshold. In this work, we develop a multi-cast routing algorithm that based on the expected transmission count metric (ETX), which implemented as a metric combined with minimum spanning tree (MST) and shortest path tree (SPT) schemes according to the various traffic loads in CRN to determine the path selection method and used the probability of Success (POS) metric for the channel assignment that used the required transmission time and the channel availability time in choosing unified channel. The main objective of our algorithm is to reduce the total number of the expected packet transmissions (with retransmissions) needed for successfully forwarding a data packet to a specific group of destinations and provide guarantees on the chances of a successful transmission over a given channel. This metric is capable to capture the CRNs environment, in which the channel availabilities are diversity and dynamically changing due to the dynamic and uncertainty activity of PUs. Our proposed protocol achieves high-throughput and packet delivery rate (PDR) through a joint channel assignment and path selection to the specific destinations. Simulation results is used to demonstrate the effectiveness of our proposed algorithm in terms of throughput and packet delivery rate compared to other existing multi-cast routing protocols over different network conditions by using matlab as a simulations. 
R. Z. Abu Samra, H. A. Bany salameh
cs.NI cs.IT math.IT