Opportunistic underwater sensor networks (OUSNs) are deployed for various underwater applications, such as underwater creatures tracking and tactical surveillance. However, the storage capacity of the sensor nodes in such networks may be insufficient, especially when a wealth of data messages are generated rapidly in some emergency response applications. The message dissemination in OUSNs therefore may differ significantly from those in wireless sensor networks or delay-tolerant networks, where network throughput should be taken as one of the primary objectives of network performance. To this end, the strategies for message storing, disseminating and discarding are investigated, and a Message Dissemination Approach for Storage-Limited (MDA-SL) OUSNs is proposed. In MDA-SL, the messages are preferred to be disseminated to the nodes with higher speed or larger residual storage. In addition, the copies of newer messages are inclined to be discarded when their message holders’ storage is full. Simulation results demonstrate the excellent performance of MDA-SL, showing that it can achieve satisfactory network throughput with propagation delay being restricted according to the diverse application requirements.

Introduction

With the broad deployments of mobile sensor nodes, opportunistic mobile sensor networks (OMSNs) [1,2] are introduced to conduct large-scale sensing at a lower cost compared to that of a ubiquitous static infrastructure of sensing devices. Because of the node mobility, however, the available contacts between nodes may be scarce and short, leading to some unstable communication paths. Opportunistic message dissemination techniques enable the network nodes to communicate in an environment where the contemporaneous end-to-end paths are unavailable or unstable, by allowing a data message to be transferred from source to destination in discrete hops even when an end-to-end communication path never emerges. As a derivative form of OMSNs, the opportunistic underwater sensor networks (OUSNs) [3] technology enables various underwater applications, such as underwater creatures tracking [4] and tactical surveillance [5]. However, compared with massive collected data, the storage capacities of nodes are usually insufficient [6,7]. What is worse, the network throughput (which is defined as the total number of data messages received per unit time by the des- ∗ Corresponding author. tinations of all the multi-hop flows in the network) is significantly restricted because the capacity of nodal storage modules is extremely limited (the space memory is even measured in KB [8], e.g., the chip CC2430 has a flash memory of 128 KB [9]).