Directed Broadcast with Overhearing for Sensor Networks

The efficient management of scarce network resources, including energy and bandwidth, represents a central challenge for wireless sensor networks. The current trend in resource management relies on the introduction of control mechanisms, such as control message exchanges, node-specific addressing, and storage of partial network state information. These mechanisms typically incur communication and processing overhead that does not scale well for larger or denser networks. Instead of introducing control mechanisms for network resource management, this article proposes and evaluates a Directed Broadcast with Overhearing (DBO) approach for sensor networks that combines directed broadcast at the network layer with CSMA and packet overhearing at the MAC layer. Through avoidance of control messaging and exchange of network state information, DBO trades off limited packet duplication overhead for control messaging overhead. This article introduces an analytical model that provides the basis for DBO evaluation and for analysis of the approach's transient packet retransmissions, route convergence, and energy consumption in the average and worst cases. We also present the model implementation details and the simulation experiments that explore the suitability of DBO for networks of different sizes with three different radio models that vary the width of grey regions, and we compare DBO's energy consumption against conventional unicast beacon-based and snooping-based routing protocols. The results indicate that that DBO's route convergence requires an average of five hops for ideal radio reception, seven hops for narrow grey regions, and twelve hops for wide grey regions. These results confirm that DBO shifts energy consumption from critical nodes near the base station to nodes near the source. The overall energy consumption of limited packet duplication overhead with DBO compared to unicast routing shrinks for medium-to large-size networks, rendering it more favorable than conventional communication approaches for large and dense sensor networks.