Extended Neighborhood Knowledge based Dominant Pruning (ExDP)
Tasmiah Tamzid Anannya, Ashikur Rahman · 2018
Reducing number of forwarding nodes is the primary objective when broadcasting the same message to all the nodes in a multi-hop wireless network. Without proper measures broadcasting may result in many redundant (re)transmissions. The prominent Dominant Pruning (DP) algorithm reduces re-transmissions to some extent using only 2-hop neighbor information of each node. Further reduction is possible if a node is equipped with three or more hops' neighborhood information. In this paper, we propose a new broadcasting technique dubbed as “ExDP” which uses extended 3-hop neighborhood information of each node in order to reduce redundancy. Expanding neighborhood knowledge up to three hops enables a forwarding node to detect which other nodes in the previous node's forwarding list are going to cover some of its 2-hop neighbors and eliminate those from reconsideration. We verify the efficacy of the proposed protocol with rigorous simulation results. The experimental results show that the proposed protocol outperforms the dominant pruning algorithm in reducing broadcast redundancy. Although collecting 3-hop neighborhood information requires some extra overhead, the additional cost is amortized over large data packets as number of re-transmissions of data packets is significantly reduced in the proposed technique.