The DESERT Underwater emulation system (http://nautilus.dei.unipd.it/desert-underwater), originally designed for testing underwater acoustic networks, has been recently extended. The new framework now includes multi-modal communication functionalities encompassing low rate and high rate acoustics as well as optics, the capability of testing wireless telemetry for underwater equipment, a connection to the most recent version of the World Ocean Simulation System (WOSS), a modification to the RECORDS system for sea trial remote control, and an interface between external tools, e.g., Matlab, and the EvoLogics modem. In addition, experimental activities are now supported by an accurate real-time event scheduler which has been shown to support, among others, long experiments involving time-division multiple-access (TDMA)-based MAC protocols. These additional protocol schemes from the MAC to the application layer (most of which have been tested in controlled environments and sea trials) now make DESERT Underwater a comprehensive tool for underwater network simulation and experimentation. In this paper, we present the new functionalities developed over the last two years.
Climate changes have a tremendous impact on coastal and littoral areas, strongly affected by seaquakes and floods. Moreover, global warming causes a drastic change on the biodiversity of rivers, seas, lakes, including in biodiversity hotspots and protected areas, such as the Venice Lagoon in Italy. A similar impact is caused by pollutants: this called for a largescale long-term action that aims to monitor aquatic environmental parameters in order to predict, manage and mitigate these effects. Yet, coastal systems are highly heterogeneous in space and variable over short (daily), medium and long (seasonal, interannual) timescales, making reliable but affordable monitoring a challenging task. This paper proposes to automate this process with the use of a low-power sustainable integrated underwater and above water Internet of Things sensor network, able to collect water measurements in a cloud database and make them available to researchers to monitor the status of a certain area and develop their predictions models. Simulation results highlight how Low-Power Wide-Area Networks can support the data collection from a dense sensor deployment.
Wearable devices are becoming a natural and economic means to gather biometric data from end users. The massive amount of information that they will provide, unimaginable until a few years ago, owns an immense potential for applications such as continuous monitoring for personalized healthcare and use within fitness applications. Wearables are however heavily constrained in terms of amount of memory, transmission capability and energy reserve. This calls for dedicated, lightweight but still effective algorithms for data management. This paper is centered around lossy data compression techniques, whose aim is to minimize the amount of information that is to be stored on their onboard memory and subsequently transmitted over wireless interfaces. Specifically, we analyze selected compression techniques for biometric signals, quantifying their complexity (energy consumption) and compression performance. Hence, we propose a new class of codebook-based (CB) compression algorithms, designed to be energy efficient, online and amenable to any type of signal exhibiting recurrent patterns. Finally, the performance of the selected and the new algorithm is assessed, underlining the advantages offered by CB schemes in terms of memory savings and classification algorithms.
The recent uptake of non-acoustic underwater transmission systems suggests that in the near future it will be common for underwater devices to incorporate different physical communication technologies. Such devices are typically described as multimodal. They seek flexibility by compensating for the shortcomings of a given technology through the advantages of another. For example, a system encompassing acoustic and optical communication systems can provide long-range, lowbit rate communications, while enabling faster data transfer at very short range.As the development of non-acoustic underwater communications is taking momentum, so is the research on how to optimally exploit the multimodal communications capabilities in different scenarios. This paper presents a survey of past and recent work on this topic, covering the development both of the communication technologies and of the networking schemes and protocols for multimodal networks. As an example of the opportunities offered by multimodal communications, we discuss two different case studies. We conclude with an outlook on likely future developments for multimodal communications.
We report the details of ASUNA, a freely shared dataset for underwater network emulation (ASUNA). ASUNA tackles the time-consuming and costly logistics of multiple underwater networking sea trials by providing a benchmark database of time-varying network topologies recorded across multiple sea experiments, thus facilitating experiment replay and network emulation. The ASUNA database currently includes 20 diverse, time-varying topology structures, multimodal communication technologies, and different link quality measurements. With the aim of becoming a standard benchmark, ASUNA is open to extensions as new data becomes available from the underwater communications community. We provide the details of ASUNA structure, the list of recorded topologies, as well as examples of how to use the database as part of an emulation system to test the performance of two scheduling protocols. We freely share the database and the emulation code both through a web server and via the Code Ocean repository.
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