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Abstract: Interest in underwater sensor networks has increased recently due to the possibility of using autonomous underwater vehicles and sensors to explore the oceans and monitor underwater equipment. Such networks, due to the need for long term deployments, must be energy efficient, like their terrestrial counterparts. However, there are fundamental differences between radio interfaces and acoustic modems, both in terms of achievable performance (e.g. bit rate and latency) and in terms of energy consumption (i.e. transmit power, receive power, sleep power, etc.). These differences may cause techniques that are highly effective for radios to perform poorly in acoustic scenarios. This paper considers asynchronous idle-time power management techniques and the effects of acoustic modem properties on the optimal solutions. Specifically, we compare two main techniques, a sleep cycling solution and a wakeup mode solution. We show that for traffic rates of greater than one packet every few hours, using a wakeup mode may be the most efficient way to save energy. [Copyright &y& Elsevier]

Abstract: Sensor network protocols must minimize energy consumption due to their resource-constrained nature. Large amounts of redundant data are produced by the sensors in such networks; however, sending unnecessary data wastes energy. One common technique used to reduce the amount of data in sensor networks is data aggregation. Therefore, we consider the impact and cost of data aggregation in sensor networks to achieve energy-efficient operation. We propose a new notion of energy efficiency that can be used to decide where aggregation points in the network should be placed. The optimal choice of these points is determined by the aggregation efficiency, which determines the amount of data reduction, and the cost in terms of energy to perform the aggregation. We present our aggregation tree algorithm “Oceanus” that produces energy-efficient aggregation trees by taking into account both of these factors. Our evaluation shows that Oceanus provides higher energy efficiency compared to existing solutions. [Copyright &y& Elsevier]