Abstract:
Self-pruning broadcasting algorithm exploits neighbor knowledge to reduce redundant
retransmissions in mobile ad hoc wireless networks (MANETs). Although in self-
pruning, only a subset of nodes forward the message based on certain forwarding rule,
it belongs to one of the reliable broadcasting algorithm category where a broadcast
message is guaranteed (at least algorithmically) to reach all the nodes in the network.
In this thesis, we develop an analytical model to determine expected number of for-
warding nodes required to complete a broadcast in self-pruning algorithm. The derived
expression is a function of various network parameters (such as, network density and
distance between nodes) and radio transceiver parameters (such as transmission range).
Moreover, the developed mathematical expression provides us a better understanding
of the highly complex packet forwarding pattern of self-pruning algorithm and valuable
insight to design a new broadcasting heuristic. The proposed new heuristic is a dynamic
probabilistic broadcast where rebroadcast probability of each node is dynamically de-
termined from a developed mathematical expression. Extensive simulation experiments
have been conducted to validate the accuracy of the analytical model, as well as, to
evaluate the e ciency of the proposed heuristic. Performance analysis shows that the
proposed heuristic outperforms the static probabilistic broadcasting algorithm.
