Interest in underwater acoustic networks has grown rapidly with the desire to monitor the large portion of the world covered by oceans. Fundamental differences between underwater acoustic propagation and terrestrial radio propagation may call for new criteria for the design of networking protocols. In this paper, we focus on some of these fundamental differences, including attenuation and noise, propagation delays, and the dependence of usable bandwidth and transmit power on distance (which has not been extensively considered before in protocol design studies). Furthermore, the relationship between the energy consumptions of acoustic modems in various modes (i.e., transmit, receive, and idle) is different than that of their terrestrial radio counterparts, which also impacts the design of energy-efficient protocols. The main contribution of this work is an in-depth analysis of the impacts of these unique relationships. We present insights that are useful in guiding both protocol design and network deployment. We design a class of energy-efficient routing protocols for underwater sensor networks based on the insights gained in our analysis. These protocols are tested in a number of relevant network scenarios, and shown to significantly outperform other commonly used routing strategies and to provide near optimal total path energy consumption. Finally, we implement in ns2 a detailed model of the underwater acoustic channel, and study the performance of routing choices when used with a simple MAC protocol and a realistic PHY model, with special regard to such issues as interference and medium access

Underwater acoustic networks have the potential to support a large variety of applications, such as mining equipment and environmental monitoring. Although underwater acoustics has been studied for decades, underwater networking and protocol design is just beginning as a research field. One critical tool used for the design and testing of new protocols is a network simulator. For simulators to be useful tools, accurate models of both the channel and the modem need to be implemented. In this paper we present the design and implementation of our interface and channel model for underwater acoustic networks in the ns2 network simulator. We show that the models accurately predict the channel conditions and interface costs by comparing them to previously published numerical predictions of channel state. Finally, we present a case study of a protocol designed and simulated using our model. Our simulation code is open source and available for general use.

Wireless reprogramming is a key functionality in Wireless Sensor Networks (WSNs). In fact, the requirements for the network may change in time, or new parameters might have to be loaded to change the behavior of a given protocol. In large scale WSNs it makes economical as well as practical sense to upload the code with the needed functionalities without human intervention, i.e., by means of efficient over the air reprogramming. This poses several challenges as wireless links are affected by errors, data dissemination has to be 100% reliable, and data transmission and recovery schemes are often called to work with a large number of receivers. State-of-the-art protocols, such as Deluge, implement error recovery through the adaptation of standard Automatic Repeat reQuest (ARQ) techniques. These, however, do not scale well in the presence of channel errors and multiple receivers. In this paper, we present an original reprogramming system for WSNs called SYNAPSE, which we designed to improve the efficiency of the error recovery phase. SYNAPSE features a hybrid ARQ (HARQ) solution where data are encoded prior to transmission and incremental redundancy is used to recover from losses, thus considerably reducing the transmission overhead. For the coding, digital Fountain Codes were selected as they are rateless and allow for lightweight implementations. In this paper, we design special Fountain Codes and use them at the heart of SYNAPSE to provide high performance while meeting the requirements of WSNs. Moreover, we present our implementation of SYNAPSE for the Tmote Sky sensor platform and show experimental results, where we compare the performance of SYNAPSE with that of state of the art protocols.