scholarly journals Design and Analysis of Adaptive Hierarchical Low-Power Long-Range Networks

2018 ◽  
Vol 7 (4) ◽  
pp. 51 ◽  
Author(s):  
Dimitrios Amaxilatis ◽  
Ioannis Chatzigiannakis
Keyword(s):  
Low Power ◽  
Long Range ◽  
Real World ◽  
Large Scale ◽  
Network Capacity ◽  
Wireless Sensor ◽  
Mobile Nodes ◽  
Networking Technologies ◽  
Hierarchical Communication ◽  
Time Required

A new phase of evolution of Machine-to-Machine (M2M) communication has started where vertical Internet of Things (IoT) deployments dedicated to a single application domain gradually change to multi-purpose IoT infrastructures that service different applications across multiple industries. New networking technologies are being deployed operating over sub-GHz frequency bands that enable multi-tenant connectivity over long distances and increase network capacity by enforcing low transmission rates to increase network capacity. Such networking technologies allow cloud-based platforms to be connected with large numbers of IoT devices deployed several kilometres from the edges of the network. Despite the rapid uptake of Long-power Wide-area Networks (LPWANs), it remains unclear how to organize the wireless sensor network in a scaleable and adaptive way. This paper introduces a hierarchical communication scheme that utilizes the new capabilities of Long-Range Wireless Sensor Networking technologies by combining them with broadly used 802.11.4-based low-range low-power technologies. The design of the hierarchical scheme is presented in detail along with the technical details on the implementation in real-world hardware platforms. A platform-agnostic software firmware is produced that is evaluated in real-world large-scale testbeds. The performance of the networking scheme is evaluated through a series of experimental scenarios that generate environments with varying channel quality, failing nodes, and mobile nodes. The performance is evaluated in terms of the overall time required to organize the network and setup a hierarchy, the energy consumption and the overall lifetime of the network, as well as the ability to adapt to channel failures. The experimental analysis indicate that the combination of long-range and short-range networking technologies can lead to scalable solutions that can service concurrently multiple applications.

scholarly journals Reversible logic in pipelined low power vedic multiplier

2019 ◽  
Vol 16 (3) ◽  
pp. 1265
Author(s):  
Ansiya Eshack ◽  
S. Krishnakumar
Keyword(s):  
Low Power ◽  
Communication Systems ◽  
Large Scale ◽  
Optical Computing ◽  
Digital Signal ◽  
Logic Gates ◽  
Reversible Logic ◽  
Large Scale Integration ◽  
Time Required ◽  
Scale Integration

<span>With an ever growing demand for low-power devices, it is a general trend to search for ways to reduce the power consumption of a system. Multipliers are an important requirement in applications linked to Digital Signal Processing, Communication Systems, Optical Computing, Nanotechnology, Low-Power Very Large Scale Integration and Quantum Computing. Conventional mathematics makes multiplication a very long and time consuming process. The use of Vedic mathematics has led to great reduction in the time required for such calculations. The excessive use of Urdhava Tiryakbhyam sutra in multiplication surely proves its effectiveness and simplicity in this domain. This sutra supports the process of pipelining, a method employed in reduction of the power used by a system. Reversible logic has been gaining demand due to its low-power capabilities and is currently being used in many computing applications. The paper proposes two multiplier systems: one design employs the Urdhava Tiryakbhyam sutra along with pipelining and the second uses reversible logic gates into the first design. These proposed systems provide very less delay for result computation and low hardware utilization when compared to non-pipelined Vedic multipliers.</span>

scholarly journals The Art of Designing Remote IoT Devices—Technologies and Strategies for a Long Battery Life

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 913
Author(s):  
Gilles Callebaut ◽  
Guus Leenders ◽  
Jarne Van Mulders ◽  
Geoffrey Ottoy ◽  
Lieven De Strycker ◽  
...  
Keyword(s):  
Low Power ◽  
Long Range ◽  
Battery Life ◽  
Sensors And Actuators ◽  
Iot Applications ◽  
Rich Diversity ◽  
Low Energy Consumption ◽  
Networking Technologies ◽  
Enhance Efficiency ◽  
Iot Devices

Long-range wireless connectivity technologies for sensors and actuators open the door for a variety of new Internet of Things (IoT) applications. These technologies can be deployed to establish new monitoring capabilities and enhance efficiency of services in a rich diversity of domains. Low energy consumption is essential to enable battery-powered IoT nodes with a long autonomy. This paper explains the challenges posed by combining low-power and long-range connectivity. An energy breakdown demonstrates the dominance of transmit and sleep energy. The principles for achieving both low-power and wide-area are outlined, and the landscape of available networking technologies that are suited to connect remote IoT nodes is sketched. The typical anatomy of such a node is presented, and the subsystems are zoomed into. The art of designing remote IoT devices requires an application-oriented approach, where a meticulous design and smart operation are essential to grant a long battery life. In particular we demonstrate the importance of strategies such as “think before you talk” and “race to sleep”. As maintenance of IoT nodes is often cumbersome due to being deployed at hard to reach places, extending the battery life of these devices is critical. Moreover, the environmental impact of batteries further demonstrates the need for a longer battery life in order to reduce the number of batteries used.

scholarly journals K-Means Spreading Factor Allocation for Large-Scale LoRa Networks

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4723 ◽  
Author(s):  
Muhammad Asad Ullah ◽  
Junnaid Iqbal ◽  
Arliones Hoeller ◽  
Richard Souza ◽  
Hirley Alves
Keyword(s):  
Low Power ◽  
Long Range ◽  
Large Scale ◽  
Research Work ◽  
Wide Area ◽  
Area Network ◽  
Wide Area Network ◽  
Spreading Factor ◽  
Worst Case ◽  
Simulation Results

Low-power wide-area networks (LPWANs) are emerging rapidly as a fundamental Internet of Things (IoT) technology because of their low-power consumption, long-range connectivity, and ability to support massive numbers of users. With its high growth rate, Long-Range (LoRa) is becoming the most adopted LPWAN technology. This research work contributes to the problem of LoRa spreading factor (SF) allocation by proposing an algorithm on the basis of K-means clustering. We assess the network performance considering the outage probabilities of a large-scale unconfirmed-mode class-A LoRa Wide Area Network (LoRaWAN) model, without retransmissions. The proposed algorithm allows for different user distribution over SFs, thus rendering SF allocation flexible. Such distribution translates into network parameters that are application dependent. Simulation results consider different network scenarios and realistic parameters to illustrate how the distance from the gateway and the number of nodes in each SF affects transmission reliability. Theoretical and simulation results show that our SF allocation approach improves the network’s average coverage probability up to 5 percentage points when compared to the baseline model. Moreover, our results show a fairer network operation where the performance difference between the best- and worst-case nodes is significantly reduced. This happens because our method seeks to equalize the usage of each SF. We show that the worst-case performance in one deployment scenario can be enhanced by 1 . 53 times.

scholarly journals What is this Article about? Extreme Summarization with Topic-aware Convolutional Neural Networks

2019 ◽  
Vol 66 ◽  
pp. 243-278
Author(s):  
Shashi Narayan ◽  
Shay B. Cohen ◽  
Mirella Lapata
Keyword(s):  
Neural Networks ◽  
Long Range ◽  
Convolutional Neural Networks ◽  
Real World ◽  
Large Scale ◽  
State Of The Art ◽  
British Broadcasting Corporation ◽  
Document Summarization ◽  
Modeling Approach ◽  
Large Scale Dataset

We introduce "extreme summarization," a new single-document summarization task which aims at creating a short, one-sentence news summary answering the question "What is the article about?". We argue that extreme summarization, by nature, is not amenable to extractive strategies and requires an abstractive modeling approach. In the hope of driving research on this task further: (a) we collect a real-world, large scale dataset by harvesting online articles from the British Broadcasting Corporation (BBC); and (b) propose a novel abstractive model which is conditioned on the article's topics and based entirely on convolutional neural networks. We demonstrate experimentally that this architecture captures long-range dependencies in a document and recognizes pertinent content, outperforming an oracle extractive system and state-of-the-art abstractive approaches when evaluated automatically and by humans on the extreme summarization dataset.

scholarly journals Outdoor Node Localization Using Random Neural Networks for Large-Scale Urban IoT LoRa Networks

Algorithms ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 307
Author(s):  
Winfred Ingabire ◽  
Hadi Larijani ◽  
Ryan M. Gibson ◽  
Ayyaz-UI-Haq Qureshi
Keyword(s):  
Neural Networks ◽  
Long Range ◽  
Urban Areas ◽  
Large Scale ◽  
Low Cost ◽  
Wireless Sensor ◽  
Node Localization ◽  
Positioning Systems ◽  
Power Characteristics ◽  
Random Neural Networks

Accurate localization for wireless sensor end devices is critical, particularly for Internet of Things (IoT) location-based applications such as remote healthcare, where there is a need for quick response to emergency or maintenance services. Global Positioning Systems (GPS) are widely known for outdoor localization services; however, high-power consumption and hardware cost become a significant hindrance to dense wireless sensor networks in large-scale urban areas. Therefore, wireless technologies such as Long-Range Wide-Area Networks (LoRaWAN) are being investigated in different location-aware IoT applications due to having more advantages with low-cost, long-range, and low-power characteristics. Furthermore, various localization methods, including fingerprint localization techniques, are present in the literature but with different limitations. This study uses LoRaWAN Received Signal Strength Indicator (RSSI) values to predict the unknown X and Y position coordinates on a publicly available LoRaWAN dataset for Antwerp in Belgium using Random Neural Networks (RNN). The proposed localization system achieves an improved high-level accuracy for outdoor dense urban areas and outperforms the present conventional LoRa-based localization systems in other work, with a minimum mean localization error of 0.29 m.

scholarly journals Towards Improved Clustering and Routing Protocol for Wireless Sensor Networks

2020 ◽  
Author(s):  
Mohammad Alharbi ◽  
Mario Kolberg ◽  
Muhammad Zeeshan
Keyword(s):  
Large Scale ◽  
Network Connectivity ◽  
Network Capacity ◽  
Wireless Sensor ◽  
Transmission Range ◽  
Hop Count ◽  
Iot Applications ◽  
Battery Capacity ◽  
Alternate Routing ◽  
Network Backbone

Abstract Wireless sensor network (WSN)-based Internet of Things (IoT) applications suffer from issues including limited battery capacity, frequent disconnections due to multihop communication and a shorter transmission range. Researchers propose different but isolated clustering and routing solutions that are inefficient in terms of energy efficiency and network connectivity in IoT-based WSNs. In this work, we emphasize the importance of considering the context of IoT applications that have further requirements for dedicated data collection per node. We address two interlinked issues, clustering and routing, in a large-scale IoT-based WSN. We propose an improved clustering and routing (ICR) protocol to jointly solve both of these issues. Improved clustering and routing provide area-based clustering derived from the transmission range of network nodes. This clustering also develops a strong network backbone that provides fail-over-proof routing. An efficient routing path is achieved by finding the minimal hop count with the availability of alternate routing paths. The results are compared with state-of-the-art benchmark protocols, Joint Clustering and Routing (JCR), Low Energy Adaptive Hierarchical Clustering (LEACH) and other recent protocols. Theoretical and simulation results demonstrate reliable network topology, improved network lifetime, efficient node density management and improved overall network capacity.

scholarly journals A New Association Scheme for Handling Node Mobility in Cluster-Tree Wireless Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5694
Author(s):  
Rogério Casagrande ◽  
Ricardo Moraes ◽  
Carlos Montez ◽  
Francisco Vasques ◽  
Erico Leão
Keyword(s):  
Ieee 802.15.4 ◽  
Mobile Node ◽  
Wireless Sensor ◽  
Monitoring Systems ◽  
Node Mobility ◽  
Distributed Monitoring ◽  
Mobile Nodes ◽  
Handover Procedure ◽  
Communication Environments ◽  
Time Required

Node mobility in multi-hop communication environments is an important feature of Wireless Sensor Network (WSN)-based monitoring systems. It allows nodes to have freedom of movement, without being restricted to a single-hop communication range. In IEEE 802.15.4 WSNs, nodes are only able to transfer data messages after completing a connection with a coordinator through an association mechanism. Within this context, a handover procedure needs to be executed by a mobile node whenever there is a disconnection from a coordinator and the establishment of a connection to another one. Many applications, such as those found in health monitoring systems, strongly need support for node mobility without loss of data during the handover. However, it has been observed that the time required to execute the handover procedure is one of the main reasons why IEEE 802.15.4 cannot fully support mobility. This paper proposes an improvement to this procedure using a set of combined strategies, such as anticipation of both the handover mechanism and the scan phase enhancement. Simulations show that it is possible to reduce latency during the association and re-association processes, making it feasible to develop WSN-based distributed monitoring systems with mobile nodes and stringent time constraints.

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