Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carr...
Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carry a code at the bottom of the first page, provided that the per-copy fee indicated in the code is paid through the Copyright Clearance Center. The papers in this book comprise the proceedings of the meeting mentioned on the cover and title page. They reflect the authors' opinions and, in the interests of timely dissemination, are published as presented and without change. Their inclusion in this publication does not necessarily constitute endorsement by the editors or the Institute of Electrical and Electronics Engineers, Inc.
Is it possible to build ultra-low power wireless sensor networks (WSN) that exploit the inherent parallel and distributed nature of powerful message passing/inference algorithms, embrace ultra-low power communication ...
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ISBN:
(纸本)9781665439299
Is it possible to build ultra-low power wireless sensor networks (WSN) that exploit the inherent parallel and distributed nature of powerful message passing/inference algorithms, embrace ultra-low power communication principles and make autonomous, in-network decisions, solely powered by the environment? While edge and cloud computing emerge, this work points towards the opposite direction, inspired by the fact that ambient energy, either from radio frequency (RF), sun, motion, temperature or even living organisms, has fixed (on average) density per surface (or volume). It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, message passing problem. Examples from Gaussian Belief Propagation and Average Consensus are offered;ambient energy harvesting and availability are quantified, controling the probability of successful (or not) message passing. Such interrupted communication requires distributed algorithms robust to asynchrony, at the expense of increased overall delay. Simulation and experimental validation are offered in a WSN testbed with solar energy harvesting. Future work will focus on overall delay minimization.
Recently proposed applications for monitoring the behavior of real-world crowds with wireless sensor nodes rely on decentralized in-network aggregation. Although some of the aggregation algorithms for wireless sensor ...
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ISBN:
(纸本)9781479946181
Recently proposed applications for monitoring the behavior of real-world crowds with wireless sensor nodes rely on decentralized in-network aggregation. Although some of the aggregation algorithms for wireless sensor networks seem appealing for such applications, we are not aware of any deployments of these algorithms in real-world scenarios with crowd mobility. As a step toward filling this gap, we thus discuss our experiences with decentralized in-network aggregation from a few such deployments involving up to 177 nodes. We compare two main classes of algorithms for basic aggregates. We show that algorithms based on probabilistic, order- and duplicate-insensitive sketches outperform algorithms based on gradual variance reduction. To this end, however, they have to be adapted considerably to minimize the traffic, latency, and errors of the aggregation process, and to account for some real-world issues. In short, while the algorithms do have a potential for the envisioned crowd-monitoring applications, deploying them is not trivial.
Collection of the sensed data in a wireless sensor network at one or more sink(s) is a well studied problem and there are a lot of efficient solutions for a variety of wireless sensor network configurations and applic...
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ISBN:
(纸本)9781479946181
Collection of the sensed data in a wireless sensor network at one or more sink(s) is a well studied problem and there are a lot of efficient solutions for a variety of wireless sensor network configurations and application requirements. These methods are often optimized towards collection of the sensed data at a predetermined base station or sink. This inherently reduces the agility of the wireless sensor network as the flow of information is not easily changeable after the establishment of the routing and data collection algorithms. This paper presents an efficient data dissemination method based on the compressed sensing theory that allows each sensor node to take the role of a sink. Agile sink selection is especially advantageous in scenarios where the sink or the end user of the wireless sensor network is mobile. The proposed method allows availing the global state of the environment by fetching a small set of data from any arbitrary node. Our evaluations prove the better performance of our technique over existing methods. Also a comparison with an oracle-based approach gives sufficient experimental evidences of a nearly optimal performance of our method.
The deployment of embedded sensing devices on croplands and pastures is an enabling element for precision agriculture applications. Changing conditions (e.g., different crops being grown), however, may require the occ...
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ISBN:
(纸本)9781538654705
The deployment of embedded sensing devices on croplands and pastures is an enabling element for precision agriculture applications. Changing conditions (e.g., different crops being grown), however, may require the occasional reconfiguration of the resulting networks of wireless sensors, e.g., to modify data reporting rates or synchronize internal clocks. In this demo we showcase an opportunistic broadcast channel to forward such configuration messages to embedded systems. The transmitting station is realized by means of an electric fence energizer, a device frequently utilized in agricultural settings. On the receiver side, only little hardware efforts are required to capture the high-voltage pulses and decode transmitted configuration messages.
Many wireless sensor networks rely on synchronization protocols to correlate measurements on different nodes. In order to save power in these applications, we consider two stages for the nodes as synchronization times...
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ISBN:
(纸本)9781538654705
Many wireless sensor networks rely on synchronization protocols to correlate measurements on different nodes. In order to save power in these applications, we consider two stages for the nodes as synchronization timeslot and the synchronous task that can run on different clock frequencies. Implemented on a Bluetooth Low Energy (BLE) chip, decreasing the clock frequency from 16 MHz to 1 MHz results in 2x and 7.5x reduction in crystal oscillator and timer run currents, respectively. Experimental results show that when the synchronization timeslot runs on the 16 MHz clock and then the clock frequency reduces to 1 MHz for executing the task, synchronization accuracies are similar to the case where only the high frequency clock is used.
As a promising application in WSN, there is an anomaly detection using the sensor information. In the anomaly detection, to the acquired sensor information based on the abnormality of the water quality in rivers, dete...
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ISBN:
(纸本)9781467394697
As a promising application in WSN, there is an anomaly detection using the sensor information. In the anomaly detection, to the acquired sensor information based on the abnormality of the water quality in rivers, detects weather anomalies as familiar, it is to report to the user. Further, in the WSN, the problem sensor price and power consumption, it is difficult to provide all sensors required for anomaly detection in all nodes. Therefore, it is required to share the expensive sensors in the network. We propose an autonomous distributed WSN systems sharing a limited sensor resources at high speed between the nodes, with improved anomaly detection rate by the node in the WSN.
Wireless sensor networks (WSNs) are currently employed in a vast number of different applications ranging from home automation and health care to military systems. Although their application may vary greatly, WSNs sha...
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ISBN:
(纸本)9781479946181
Wireless sensor networks (WSNs) are currently employed in a vast number of different applications ranging from home automation and health care to military systems. Although their application may vary greatly, WSNs share a common set of characteristics such as a limited energy supply and simple hardware. A common issue related with the application of WSNs is sensor localization, for some types of applications it is important that the sensors know the relative or absolute position of other sensors in the network, such as surveillance of monitoring networks. If sensors are randomly placed they may resort a wide range of methods such as Global Navigation Satellite systems (GNSS) or received signal strength indicators (RSSI). In this work we present an alternative to relative sensor localization by employed a crossed dipole antenna in the reception and a known polarization in the transmission. The accuracy of the proposed methods is measured trough numerical simulations and results are presented.
The sensor Sharing Marketplace (SenShaMart) enables IoT applications to find IoT sensors, which are owned and managed by other parties, integrate them, and pay for using their data. To provide corresponding services t...
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ISBN:
(纸本)9798350339864
The sensor Sharing Marketplace (SenShaMart) enables IoT applications to find IoT sensors, which are owned and managed by other parties, integrate them, and pay for using their data. To provide corresponding services that implement that FAIR (Findable, Accessible, Interoperable, Reusable) principles of IoT, SenShaMart incorporates a specialized blockchain that manages all the information its services need to allow different parties in IoT to describe, query, integrate, pay for, and use IoT sensors and their data. The paper presents the SenShaMart's architecture, implementation, evaluation, and demonstration.
The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is ...
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ISBN:
(纸本)0769523315
The process of computing the physical locations of nodes in a wireless sensor network is known as localization. Self-localization is critical for large-scale sensor networks because manual or assisted localization is often impractical due to time requirements, economic constraints or inherent limitations of deployment scenarios. We have developed a service for reliably localizing wireless sensor networks in environments conducive to ranging errors by using a custom hardware-software solution for acoustic ranging and a family of self-localization algorithms. The ranging solution improves on previous work, extending the practical measurement range threefold (20-30m) while maintaining a distance-invariant median measurement error of about 1% of maximum range (33cm). The localization scheme is based on least squares scaling with soft constraints. Evaluation using ranging results obtained from sensor network field experiments shows that the localization scheme is resilient against large-magnitude ranging errors and sparse range measurements, both of which are common in large-scale outdoor sensor network deployments.
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