1,721,027 research outputs found
Feasibility study for authenticated key exchange protocols on underwater acoustic sensor networks
No full textThe paper concerns a comparative performance evaluation of protocols for two honest parties to securely share a common secret session key in an Underwater Acoustic Sensor Network (UASN) scenario. The simulation-based comparison is performed by implementing in SUNSET SDCS three key exchange protocols and two solutions for implicit certificate distribution. The three key exchange solutions are the Fully Hashed Menezes-Qu-Vanstone, the Hashed One-pass Menezes-Qu-Vanstone (both based on Elliptic Curve Cryptography) and Diffie-Hellman. Certificate distribution is performed via the Elliptic Curve Qu-Vanstone protocol (implicit) and by X.509 certificates (explicit). Combinations of the selected protocols are considered to secure multipath-based communications in UASNs of different size. Investigated metrics concern the energy consumed and the time required to complete the exchange of keys between two nodes. Our results show that implicit certificates-based solutions obtain application-dependent tradeoffs between security and energy efficiency and a level of security comparable to that of the standard, terrestrial combination of Diffie-Hellman with the X.509 explicit certificates
Enabling the mobile IoT: Wake-up unmanned aerial systems for long-lived data collection
No full textNetworking and robotics are increasingly coming together to meet the requirements of applications that only advances in both fields can enable. This paper explores one of these joint applications, namely, using a robotic platform such as an Unmanned Aerial System (UAS) to wirelessly retrieve data produced by the devices of a sensor network. For energy conservation purposes devices operate according to a set duty cycle, or are endowed with wake-up radio transceivers allowing them to transmit and receive data only when needed. We define two simple UAS-aided data collection strategies depending on whether the devices use duty cycling or can be woken up by the visiting UAS. The performance of the two strategies is evaluated by using GreenCastalia, an open source simulator extended to model duty cycles, wake-up radio capabilities and the mobility of the UAS. We compare the two strategies with respect to the amount of data the UAS can collect in its visit, the energy consumption of the devices and the corresponding network lifetime. Our results show the key role of low-cost, low-energy consumption wake-up receivers in providing ways of collecting all data from the sensing devices while consuming a negligible fraction of the energy required to devices operating with a duty cycle. As a result, the lifetime of wake-up radio-based networks is orders of magnitude higher than that afforded to networks with duty cycling: Many decades vs. the very few years of networks with extremely low duty cycles
On the Effectiveness of Semantic Addressing for Wake-up Radio-enabled Wireless Sensor Networks
No full textThis paper investigates various ways of minimizing energy consumption in Wireless Sensor Networks (WSNs). We are interested in those methods and technologies that allow network nodes to drastically decrease energy consumption by turning off their primary communication circuitry (main radio), arguably the main culprit of energy depletion. We consider WSNs whose nodes operate according to pre-set duty cycles and WSNs with nodes featuring very low-power wake-up radio devices. In these scenarios we evaluate the performance of an energy-aware routing protocol, showing that when nodes wake up their neighbors based on their suitability to forward data packets (semantic addressing), energy consumption and network lifetime are remarkably better than when all of a sender neighbors are awoken indistinctly (broadcast addressing) and than when nodes duty cycle. Protocols using semantic addressing achieve network lifetimes that are 10x higher than when broadcast addressing is used and three orders of magnitude better than in duty cycle-based networks. We also observe that semantic addressing keeps data latency at bay, achieving end-to-end latency similar to that in networks with nodes with the radio always on
Performance Analysis of Sweep-Spread Carrier (S2C) Modulation for Underwater Communications
No full textIn the last decades, underwater acoustic communications have seen a growing development with a variety of research as well as commercial applications, dealing with channel distortions, multipath and Doppler effects typical underwater channels. A very robust modulation able to guarantee connectivity in harsh environments (where spectral efficient solutions such as OFDM can be prevented) is the so called sweep-spread carrier (S2C) modulation, which is based on the usage of a linearly time-varying carrier. Underwater modems based on S2C modulations have been patented and
successfully adopted in real-world deployments.
In this paper, we analyze the performance of S2C both in simulation and infield experiments, based on our own S2C implementation. We undertake extensive simulation experiments, quantitatively measuring the impact of a variety of modulation parameters (such as the sweep duration and the number of coded symbols per sweep), and under different channel characteristics (depth, range, Doppler speed, etc.). Moreover, we test the performances of the S2C modulation at sea, obtaining good results also in shallow waters
A channel aware adaptive modem for underwater acoustic communications
Full text linkAcoustic underwater channels are very challenging, because of limited bandwidth, long propagation delays, extended multipath, severe attenuation, rapid time variation and large Doppler shifts. A plethora of underwater communication techniques have been developed for dealing with such a complexity, mostly tailoring specific applications scenarios which can not be considered as one-size-fits-all solutions. Indeed, the design of environment-specific solutions is especially critical for modulations with high spectral efficiency, which are very sensitive to channel characteristics. In this paper, we design and implement a software-defined modem able to dynamically estimate the acoustic channel conditions, tune the parameters of a OFDM modulator as a function of the environment, or switch to a more robust JANUS/FSK modulator in case of harsh propagation conditions. The temporal variability of the channel behavior is summarized in terms of maximum delay spread and Doppler spread. We present a very efficient solution for deriving these parameters and discuss the limit conditions under which the OFDM modulator can work. In such scenarios, we also calibrate the prefix length and the number of sub-carriers for limiting the inter-symbol interference and signal distortions due to the Doppler effect. We validate our estimation and adaptation techniques by using both a custom-made simulator for time-varying underwater channels and the well-known Watermark simulator, as well as real in field experiments. Our results show that, for many practical cases, a dynamic adjustment of the prefix length and number of sub-carriers may enable the utilization of OFDM modulations in underwater communications, while in harsher environments JANUS can be used as a fall-back modulation
ALBA: an Adaptive Load Balanced Algorithm for Geographic Forwarding in Wireless Sensor Networks
No full textIn this paper we propose and analyze ALBA, an original packet forwarding protocol for ad hoc and sensor networks. ALBA follows an integrated approach that combines geographic routing and medium access control (MAC), exploiting the knowledge of node positions in order to achieve energy-efficient data forwarding. The scenario we consider is very critical for medium-high traffic, as contentions for channel access and the resulting collisions lead to performance degradation. To counter this effect, we leverage on network density, favoring the choice relay candidates that are not in overload. With our protocol, nodes strive to channelize traffic toward uncongested network regions, rather than just maximizing the advancement towards the final destination. We carry out extensive simulations that compare ALBA to GeRaF and MACRO, two recently proposed cross-layer approaches with similar goals. The results show that our design achieves very good delivery and latency performance, and can greatly limit energy consumption
Goodput Maximization in Opportunistic Spectrum Access Radio Links with Imperfect Spectrum Sensing and FEC-based Packet Protection
No full textWe consider a cognitive radio scenario where the communication between two secondary users (SUs) exploits opportunistic spectrum access (OSA) over a wireless channel licensed to primary users (PUs). Assuming a slotted MAC over a single frequency channel and imperfect spectrum sensing, we address the problem of determining the packet size and Forward Error Correction (FEC) coding rate that maximize the SU communication goodput, i.e., the amount of payload bits correctly received in the unit time. Assuming a Markovian model for the PU activity, a saturation regime for the SU, and periodic channel sensing, we find out the mean time between two consecutive packet transmissions and derive approximate analytical expressions, in closed form, which provide upper and lower bounds on the SUs goodput. Such expressions show the dependence of the SU goodput on packet size, FEC coding rate, signal to noise plus interference ratio, amount of resources allocated to sensing, packet overhead, and primary traffic statistics. We provide simulation results showing that the derived analytical expressions are very close to the actual system performance. We also evaluate the sensitivity of the optimal packet size and FEC coding rate pair to the operational conditions represented by the received power and the PU traffic load, showing that the optimal pair is very sensitive to the former, and only moderately affected by the latter
An optimization framework for joint sensor deployment, link scheduling and routing in underwater sensor networks
No full textUnderwater sensor networks are a very interesting case of wireless communication in extreme conditions. They exploit acoustic communication in the water and are nowadays used in surveillance and monitoring applications. These networks present very challenging aspects, such as low data rates and large delays, as well as the special propagation characteristics of the underwater medium. We propose an integer-linear programming approach to jointly optimize routing, link-scheduling and node placement in such a scenario. Accounting for these special aspects of underwater wireless communications leads to re-thinking traditional approaches; this results in original solutions, which highlight novel directions for further research in this area
Vulcan: A low-cost, low-power embedded visible light communication and networking platform
No full textVisible Light Communication (VLC) offers a key alternative to the spectrum-challenged Radio Frequency (RF)-based forms of data transmission by tapping an unutilized and unregulated frequency band. Carefully designed low-cost VLC devices have the potential to enable the Internet of Things (IoT) at scale by reducing the current RF spectrum congestion, which is one of the major obstacles to the pervasiveness of the IoT. Wide adoption of VLC devices is however hindered by their current shortcomings, including low data rate, very short range and inability to communicate in noisy environment. In this paper we describe a new software-defined VLC prototype named VuLCAN for Visible Light Communication And Networking that overcomes these limitations. VuLCAN is based on an ARM Cortex M7 core microcontroller with fast sampling analog-to-digital converter along with power-optimized Digital Signal Processing (DSP) libraries. Using BFSK modulation, the prototype achieves a data rate of 65 Kbps over a communication range of 4.5 m. VuLCAN also provides robust and reliable communications in highly illuminated environments (up to 800 lux) using only a low power Light Emitting Diode (LED), largely exceeding the capabilities of current state-of-the-art prototypes
A Data Compression Module for the SUNSET Platform
Full text linkIn the last two decades, visual data acquisition in underwater environments has dramatically increased due to the need to face a wide range of challenges that still require further research, including site monitoring, seabed anomaly detection, object detection and classification, and many others. Most of these activities require frequent data acquisition and processing over time, even at different altitudes, view angles, and perspectives. Recent improvements of small-scale Autonomous Underwater Vehicles (AUVs), in terms of navigation time, automatic control, and onboard processing, are making these submersible vehicles particularly suitable for activities as those reported above. Moreover, thanks to their cableless navigation, limited size, and agility, small-scale AUVs (hereinafter simply AUVs) can reach sites otherwise inaccessible with other kinds of underwater vehicles (e.g., medium and large AUVs). The payload capacity of current AUVs allows us to equip them with different vision sensors, including Red Green Blue (RGB) camera and Side Scan Sonar (SSS). In this context, an open issue remains the efficient transmission of visual data from AUV through an underwater acoustic network to allow a remote workstation an online and/or real-time data processing. In this paper, a data compression module for the SUNSET platform is presented. The module is composed of a set of novel algorithms that enables compression of RGB and SSS information with and without data loss. The module also implements some novel features, including progressive compression and Region Of Interest (ROI) selection; the first used to gradually transmit the image data (e.g., sites in which the acoustic transmission is a hard task), the second used to transmit, with higher quality than the rest of the image, the items contained in a specific area. Exhaustive experiments on RGB and SSS datasets prove the effectiveness of the presented module
- …
