MARATTO

article · ICST Transactions on Mobile Communications and Applications

Centralized multicasting AODV routing protocol optimized for intermittent cognitive radio ad hoc networks

20241 citationOpen accessUniversity of Limpopo

Abstract

The advancement of wireless technology is affected by Spectrum scarcity and the overcrowding of free spectrum. Cognitive Radio Ad Hoc Networks (CRAHNs) have emerged as a possible solution to both the scarcity and overcrowding challenges of the spectrum. The CRAHNs ensure that the Secondary Users (SUs) do co-exist with Primary Users (PUs) in a non-interfering manner. The SUs access the licensed spectrum opportunistically when they are idle. CRAHNs have many use cases which include intermittent networks here referred to as intermittent CRAHNs (ICRAHNs). For example, the Military (MCRAHNs). MCRAHN is complex and characterized by a dynamic topology which is subject to frequent partitioning and route breakages due to attacks and destruction in combat. This study optimizes the routing protocols for intermittent networks such as the MCRAHNs. ICRAHN routing is a challenge due to the network’s intermittent attribute, which is subject to destruction in the case of MCRAHN which is characterized by frequent link breakages. To better understand the routing in this network scenario, this paper presents two analytic models for the AODV and MAODV protocols based on queuing theory. The analytic models simulate unicast and multicast AODV in terms of factors such as queuing delay, throughput, and network scalability. Numerical analysis shows that MAODV outperforms AODV. Furthermore, the suggested routing protocols' performance was tested using network simulations utilizing the following metrics: throughput, Routing Path delay, Node Relay delay, and Spectrum Mobility delay. The simulation findings suggest that the MAODV protocol outperforms the AODV protocol.

Research topics

  • Cognitive Radio Networks and Spectrum Sensing
  • Cooperative Communication and Network Coding
  • Advanced MIMO Systems Optimization

Read the original research

This page summarises published work. The authoritative version sits with the publisher.

DOI: 10.4108/eetmca.3888

Is something wrong with this record? Report it or request removal.

Discussion

Discuss this research

Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.

No discussion yet. Open the first thread.