scholarly journals Utilizing the Switching Stochasticity of HfO2/TiOx-Based ReRAM Devices and the Concept of Multiple Device Synapses for the Classification of Overlapping and Noisy Patterns

2021 ◽  
Vol 15 ◽  
Author(s):  
Christopher Bengel ◽  
Felix Cüppers ◽  
Melika Payvand ◽  
Regina Dittmann ◽  
Rainer Waser ◽  
...  
Keyword(s):  
Online Learning ◽  
Low Power ◽  
Physical Models ◽  
Parallel Operation ◽  
Learning Potential ◽  
Change Mechanism ◽  
Bipolar Switching ◽  
The Internet Of Things ◽  
Efficient Realization

With the arrival of the Internet of Things (IoT) and the challenges arising from Big Data, neuromorphic chip concepts are seen as key solutions for coping with the massive amount of unstructured data streams by moving the computation closer to the sensors, the so-called “edge computing.” Augmenting these chips with emerging memory technologies enables these edge devices with non-volatile and adaptive properties which are desirable for low power and online learning operations. However, an energy- and area-efficient realization of these systems requires disruptive hardware changes. Memristor-based solutions for these concepts are in the focus of research and industry due to their low-power and high-density online learning potential. Specifically, the filamentary-type valence change mechanism (VCM memories) have shown to be a promising candidate In consequence, physical models capturing a broad spectrum of experimentally observed features such as the pronounced cycle-to-cycle (c2c) and device-to-device (d2d) variability are required for accurate evaluation of the proposed concepts. In this study, we present an in-depth experimental analysis of d2d and c2c variability of filamentary-type bipolar switching HfO2/TiOx nano-sized crossbar devices and match the experimentally observed variabilities to our physically motivated JART VCM compact model. Based on this approach, we evaluate the concept of parallel operation of devices as a synapse both experimentally and theoretically. These parallel synapses form a synaptic array which is at the core of neuromorphic chips. We exploit the c2c variability of these devices for stochastic online learning which has shown to increase the effective bit precision of the devices. Finally, we demonstrate that stochastic switching features for a pattern classification task that can be employed in an online learning neural network.

scholarly journals Online Learning and Classification of EMG-Based Gestures on a Parallel Ultra-Low Power Platform Using Hyperdimensional Computing

2019 ◽  
Vol 13 (3) ◽  
pp. 516-528 ◽  
Author(s):  
Simone Benatti ◽  
Fabio Montagna ◽  
Victor Kartsch ◽  
Abbas Rahimi ◽  
Davide Rossi ◽  
...  
Keyword(s):  
Online Learning ◽  
Low Power ◽  
Ultra Low Power

scholarly journals A Complete Key Management Scheme for LoRaWAN v1.1

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2962
Author(s):  
Xingda Chen ◽  
Margaret Lech ◽  
Liuping Wang
Keyword(s):  
Low Power ◽  
Key Management ◽  
Wide Area Networks ◽  
Key Generation ◽  
Security Framework ◽  
Data Confidentiality ◽  
Backward Compatibility ◽  
Management Scheme ◽  
The Internet Of Things ◽  
Key Management Scheme

Security is one of the major concerns of the Internet of Things (IoT) wireless technologies. LoRaWAN is one of the emerging Low Power Wide Area Networks being developed for IoT applications. The latest LoRaWAN release v.1.1 has provided a security framework that includes data confidentiality protection, data integrity check, device authentication and key management. However, its key management part is only ambiguously defined. In this paper, a complete key management scheme is proposed for LoRaWAN. The scheme addresses key updating, key generation, key backup, and key backward compatibility. The proposed scheme was shown not only to enhance the current LoRaWAN standard, but also to meet the primary design consideration of LoRaWAN, i.e., low power consumption.

scholarly journals Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey

Technologies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 22
Author(s):  
Eljona Zanaj ◽  
Giuseppe Caso ◽  
Luca De Nardis ◽  
Alireza Mohammadpour ◽  
Özgü Alay ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Low Power ◽  
Energy Efficient ◽  
Wide Area ◽  
Wide Area Networks ◽  
The Internet ◽  
Extensive Review ◽  
Research Directions ◽  
The Internet Of Things

In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions.

A two-dimensional polymer memristor based on conformational change with tunable resistive switching behaviors

2021 ◽  
Author(s):  
Yaru Song ◽  
Guangyuan Feng ◽  
Lingli Wu ◽  
Enbing Zhang ◽  
Chenfang Sun ◽  
...  
Keyword(s):  
Low Power ◽  
Conformational Change ◽  
Resistive Switching ◽  
Two Dimensional ◽  
Change Mechanism

In this work, through rational monomer design we integrated the conformational change mechanism into a two-dimensional covalent polymer and implemented 3 different low-power memory behaviors on the same device by...

scholarly journals Adaptive Data Synchronization Algorithm for IoT-Oriented Low-Power Wide-Area Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4053 ◽  
Author(s):  
Andrea Petroni ◽  
Francesca Cuomo ◽  
Leonisio Schepis ◽  
Mauro Biagi ◽  
Marco Listanti ◽  
...  
Keyword(s):  
Low Power ◽  
Mobile Communications ◽  
Data Exchange ◽  
Energy Savings ◽  
Wide Area ◽  
Wide Area Networks ◽  
Battery Life ◽  
File Synchronization ◽  
The Internet Of Things

The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications.

scholarly journals Online Learning for Classification of Alzheimer Disease based on Cortical Thickness and Hippocampal Shape Analysis

2014 ◽  
Vol 20 (1) ◽  
pp. 61 ◽  
Author(s):  
Ga-Young Lee ◽  
Jeonghun Kim ◽  
Ju Han Kim ◽  
Kiwoong Kim ◽  
Joon-Kyung Seong
Keyword(s):  
Online Learning ◽  
Alzheimer Disease ◽  
Cortical Thickness ◽  
Shape Analysis

scholarly journals Worldwide Connectivity for the Internet of Things Through LoRaWAN

2019 ◽  
Vol 11 (3) ◽  
pp. 57 ◽  
Author(s):  
Lorenzo Vangelista ◽  
Marco Centenaro
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Cellular Network ◽  
Wide Area ◽  
The Internet ◽  
Area Network ◽  
Wide Area Network ◽  
Frequency Bands ◽  
The Moment ◽  
The Internet Of Things

The low-power wide-area network (LPWAN) paradigm is gradually gaining market acceptance. In particular, three prominent LPWAN technologies are emerging at the moment: LoRaWAN™ and SigFox™, which operate on unlicensed frequency bands, and NB-IoT, operating on licensed frequency bands. This paper deals with LoRaWAN™, and has the aim of describing a particularly interesting feature provided by the latest LoRaWAN™ specification—often neglected in the literature—i.e., the roaming capability between different operators of LoRaWAN™ networks, across the same country or even different countries. Recalling that LoRaWAN™ devices do not have a subscriber identification module (SIM) like cellular network terminals, at a first glance the implementation of roaming in LoRaWAN™ networks could seem intricate. The contribution of this paper consists in explaining the principles behind the implementation of a global LoRaWAN network, with particular focus on how to cope with the lack of the SIM in the architecture and how to realize roaming.

scholarly journals CRESS: Framework for Vulnerability Assessment of Attack Scenarios in Hardware Reverse Engineering

2021 ◽  
Author(s):  
Matthias Ludwig ◽  
Alexander Hepp ◽  
Michaela Brunner ◽  
Johanna Baehr
Keyword(s):  
Reverse Engineering ◽  
Autonomous Driving ◽  
The Internet ◽  
Changing Trends ◽  
Remediation Strategies ◽  
The Common ◽  
The One ◽  
Soft And Hardware ◽  
The Internet Of Things

Trust and security of microelectronic systems are a major driver for game-changing trends like autonomous driving or the internet of things. These trends are endangered by threats like soft- and hardware attacks or IP tampering -- wherein often hardware reverse engineering (RE) is involved for efficient attack planning. The constant publication of new RE-related scenarios and countermeasures renders a profound rating of these extremely difficult. Researchers and practitioners have no tools or framework which aid a common, consistent classification of these scenarios. In this work, this rating framework is introduced: the common reverse engineering scoring system (CRESS). The framework allows a general classification of published settings and renders them comparable. We introduce three metrics: exploitability, impact, and a timestamp. For these metrics, attributes are defined which allow a granular assessment of RE on the one hand, and attack requirements, consequences, and potential remediation strategies on the other. The system is demonstrated in detail via five case studies and common implications are discussed. We anticipate CRESS to evaluate possible vulnerabilities and to safeguard targets more proactively.

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