Edge computing established paradigms are prone to implicate solely powerful server-like edge nodes, in static or semistatic topologies, of centrally-controlled edge networks. In this paper, leveraging upon recent tech...
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ISBN:
(纸本)9781728143514
Edge computing established paradigms are prone to implicate solely powerful server-like edge nodes, in static or semistatic topologies, of centrally-controlled edge networks. In this paper, leveraging upon recent technological advancements and trends, we introduce a novel networking paradigm employing resources provided by independent crowd peers, within a zone of local proximity, to establish collaborative networks for edge computing. We call this paradigm the Crowdsourced Edge. We detail the architecture and characteristics of this novel paradigm, highlighting its unique characteristics and specific challenges, while also positioning it vis-a-vis the existing edge computing concretisations. Finally, we demonstrate the Crowdsourced Edge functionality by presenting an ongoing use case regarding a video-enhanced object search.
Human flow counting is a fundamental task in public space management. Counting flow correctly may help prevent overcrowding hazards and improve public safety. This study proposes an automated device-free flow counting...
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ISBN:
(纸本)9781509014590
Human flow counting is a fundamental task in public space management. Counting flow correctly may help prevent overcrowding hazards and improve public safety. This study proposes an automated device-free flow counting system by exploiting radio frequency irregularity in a wireless sensor network. As people pass through the line-of-sight between transmitters and receivers, radio frequency transmission is disturbed and received signal strength indicator (RSSI) fluctuates at the receiving ends. Using RSSI fluctuation series, the system infers flow size without patrons' carrying any special devices. A wireless sensor network with HBE-Zigbex motes (ieee 802.15.4) is set up to conduct experiments. Besides the mean and standard deviation of RSSI fluctuation series, Fourier spectral features are also employed as predictors of a machine learning algorithm. Experimental results show that spectral features improve the prediction accuracy significantly. The proposed method thus provides an alternative solution for the flow counting problem in addition to other video based solutions.
Wireless sensor and actuator network (WSAN) applications are used in many critical scenarios. For instance, upon receiving an over-threshold pressure value, the control station of a gas separation plant issues a comma...
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ISBN:
(纸本)9781479946181
Wireless sensor and actuator network (WSAN) applications are used in many critical scenarios. For instance, upon receiving an over-threshold pressure value, the control station of a gas separation plant issues a command to corresponding actuators to close gas valves to prevent a fire accident. In such control-loop systems, messages must be transported reliably within a tight deadline. This paper presents two components: a new network dimensioning method and a simple MAC protocol, to support control-loop systems in WSANs. The dimensioning method is used to specify the worst-case network topology, traffic and node forwarding rates prior to a network deployment. The MAC protocol is designed to ensure that the specifications and design assumptions are not violated in a subsequent deployment. The experimental evaluation clearly indicates that messages are delivered within the guaranteed delay bound.
In wireless sensor networks, data collection (or gathering) is the task of transmitting rounds of measurements of physical phenomena from the sensor nodes to a sink node. We study how to increase the efficiency of dat...
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ISBN:
(纸本)9781509014590
In wireless sensor networks, data collection (or gathering) is the task of transmitting rounds of measurements of physical phenomena from the sensor nodes to a sink node. We study how to increase the efficiency of data collection via supervised in-network classification of rounds of measurements. We assume that the end users of the data are interested only in rounds characterized by certain patterns. Hence the wireless sensor network uses classification to select the rounds of measurements that are transmitted to the base station. The energy consumption is potentially reduced by avoiding the transmission of rounds of measurements that are not of interest to the end users. Innetwork classification requires distributed feature extraction and transmission. Such tasks can be less or more energy expensive than the transmission of measurements without classification. We provide analytical results and simulations on real data to show requirements and key trade-offs for the design of in-network data classification systems that can improve the collection efficiency. Besides, we study the impact of spatial subsampling of the sensor data (a way to further decrease energy consumption) on the classification performance.
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.
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.
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.
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.
A wireless sensor network (WSN) is usually deployed in a field of interest (FoI) for detecting or monitoring some special events and then forwarding the aggregated data to the designated data center through sink nodes...
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ISBN:
(纸本)9781538639917
A wireless sensor network (WSN) is usually deployed in a field of interest (FoI) for detecting or monitoring some special events and then forwarding the aggregated data to the designated data center through sink nodes or gateways. Traditionally, the WSN requires the intensive deployment in which the extra sensor nodes are deployed to achieve the required coverage level. Fortunately, depending on the developments of the unmanned aerial vehicle (UAV) techniques, the UAV has been widely adopted in both military and civilian applications. Comparing with the traditional mobile sensor nodes, the UAV has much faster moving speed, longer deployment range and relatively longer serving time. Consequently, the UAV can be considered as a perfect carrier for the existing sensing equipment and used to form a UAV-based WSN (UWSN). In this paper, we theoretically analyse the coverage problem in the UWSN. Based on the integral geometry, we solve the aforementioned question. The experimental results further verifies our theoretical results.
In this paper, we present a distributed machine learning based intrusion detection system in Internet of Things (IoT) utilizing Blockchain technology. In particular, spectral partitioning is proposed to divide the IoT...
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ISBN:
(数字)9781728143514
ISBN:
(纸本)9781728143514
In this paper, we present a distributed machine learning based intrusion detection system in Internet of Things (IoT) utilizing Blockchain technology. In particular, spectral partitioning is proposed to divide the IoT network into autonomous systems (AS) enabling traffic monitoring for intrusion detection (ID) to be performed by the selected AS border area nodes in a distributed manner. The ID system is based on machine learning, where a support-vector machine algorithm is trained using prominent IoT data sets and detection of the attackers is provided. Furthermore, the integrity of the attackers' list is offered by utilizing Blockchain technology, which enables a distributed sharing of the attackers' information among the AS border area nodes of the Blockchain network. Simulations are performed to evaluate different aspects of the proposed IoT system and demonstrate the potential of integrating machine learning based ID to a distributed spectral partitioned Blockchain network.
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