Improved Self-Pruning for Broadcasting in Ad Hoc Wireless Networks

Abstract

Reducing number of forwarding nodes is the main focus of any broadcasting algorithm designed for ad-hoc wireless networks. All reliable broadcasting techniques can be broadly classified under proactive and reactive approaches. In proactive approach, a node selects a subset of its neighbors as forwarding node and announces the forwarding node list in the packet header during broadcast. On the other hand, no such forwarding list is generated in reactive approach. Rather, a node (cognitively) determines by itself whether to forward the packet or not based on neighbor information. Dominant pruning and Self-pruning are two example techniques that fall under proactive and reactive approach respectively. Between the two methods, dominant pruning shows better performance than self-pruning in reducing number of forwarding nodes as they work with extended neighbor knowledge. However, appended forwarding node list increases message overhead and consumes more bandwidth. As a result, the approach becomes non-scalable in large networks. In this paper, we propose a reactive broadcasting technique based on self-pruning. The proposed approach dubbed as “Improved Self-pruning based Broadcasting (ISB)” algorithm completes the broadcast with smaller packet header (i.e., with no overhead) but uses extended neighbor knowledge. Simulation results show that ISB outperforms dominant pruning and self-pruning. Furthermore, as the network gets more spread and denser, ISB works remarkably well.