Research And Implementation Of PUMA Multicast Routing Protocol Based On Queue Load Perceptive And Hash Chain

Wireless AD HOC network is a decentralized type of wireless network. It does not rely on a preexisting infrastructure, such as access points in central managed wireless networks. Instead, each node participates in routing by forwarding data for other nodes, and so the determination of which nodes forward data is made dynamically based on the network connectivity. Therefore, efficient, dynamic routing is one of the key challenges in wireless AD HOC networks.Multicasting is becoming a very important feature in AD HOC networks. Over the past few years, several multicast routing protocols have been proposed for such networks. Most existing AD HOC multicasting protocols can be classified as tree-based or mesh-based. PUMA to be introduced is a mesh-based multicast routing protocol. PUMA is novel, efficient and elegant; it can achieve a high data delivery ratio with very limited control overhead, which is almost constant for a wide range of network conditions. Nevertheless, PUMA is not suitable for all kinds of scenarios. Especially in heavy traffic network PUMA might get worse performance. PUMA does not ever take into account any security at all, so it’s vulnerable and apt to be attacked.To address these issues, this thesis proposes a queue load perceptive and hash chain based PUMA protocol. It mainly makes some innovation points at routing metric and security, modifies and optimizes the hop count based PUMA protocol. This thesis demonstrates three approaches based on queue load perceptive. When constructing the route, it focuses on the load of the node, which considers the count of the packets in the transmitting queue as the main metric and hop count the second. It also involves hash chain to make sure the hop count in the message has not been contaminated. So the route will bypass the malicious node.This thesis depicts the principle and implementation of the queue load perceptive and hash chain based PUMA protocol, uses NS2to evaluate the queue load perceptive based PUMA and hop count based PUMA, and makes comparison with respect to three performance functions between them. Queue load perceptive based PUMA and hop count based PUMA are the same order of magnitude. Especially in the heavy traffic scenarios, the former outperforms the latter.