Edge/Fog Computing Technologies for IoT Infrastructure

The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices. Moreover, emerging IoT applications, such as augmented and virtual reality (AR/VR), intelligent transportation systems, and smart factories require ultra-low latency for data communication and processing. Fog/edge computing is a new computing paradigm where fully distributed fog/edge nodes located nearby end devices provide computing resources. By analyzing, filtering, and processing at local fog/edge resources instead of transferring tremendous data to the centralized cloud servers, fog/edge computing can reduce the processing delay and network traffic significantly. With these advantages, fog/edge computing is expected to be one of the key enabling technologies for building the IoT infrastructure. Aiming to explore the recent research and development on fog/edge computing technologies for building an IoT infrastructure, this book collected 10 articles. The selected articles cover diverse topics such as resource management, service provisioning, task offloading and scheduling, container orchestration, and security on edge/fog computing infrastructure, which can help to grasp recent trends, as well as state-of-the-art algorithms of fog/edge computing technologies

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine

5G and beyond networks

This chapter investigates the Network Layer aspects that will characterize the merger of the cellular paradigm and the IoT architectures, in the context of the evolution towards 5G-and-beyond, including some promising emerging services as Unmanned Aerial Vehicles or Base Stations, and V2X communications

Data bases and data base systems related to NASA's aerospace program. A bibliography with indexes

This bibliography lists 1778 reports, articles, and other documents introduced into the NASA scientific and technical information system, 1975 through 1980

Understanding Quantum Technologies 2022

Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma

Towards efficient horizontal federated learning

The advance of Machine Learning (ML) techniques has become the driving force in the development of Artificial Intelligence (AI) applications. However, it also brings about new problems as ML models and algorithms are more data-hungry than ever. First, the sources of data are often geographically distributed and thus gathering all the data for centralised training incurs heavy traffic and prohibitive communication costs. Second and more importantly, moving data out of local devices are now prohibited in many situations due to privacy concerns. As a promising solution, Federated Learning (FL) is a framework proposed by Google for learning from decentralised data without data sharing. Nonetheless, many challenges remain especially regarding how to facilitate efficient FL in different circumstances. The work presented in this thesis is mainly focused on optimising the efficiency of Horizontal Federated Learning, the most commonly used paradigm of FL, from three perspectives: i) redesigning the device– server synchronisation mechanism of FL for failure-tolerant collaborative training over unreliable, heterogeneous end devices (clients), ii) integrating FL with the Mobile Edge Computing (MEC) architecture to utilise the edge layer for robustness, resource efficiency and fast convergence, and iii) optimising the client selection policy in FL through the evaluation of clients’ training value based on the learnt representations of their associated data. Results of extensive experiments are presented to demonstrate the effectiveness of the proposed approaches. In addition to algorithm design and experimental observations, this thesis also discusses the research spectrum of FL and overviews its development in the industry including popular platforms, systems and emerging applications. Based on the work presented, key conclusions and insights are provided with a research outlook for the future study of FL

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

A cumulative index to the 1973 issues of Aeronautical engineering: A special bibliography

This publication is a cumulative index to the abstracts contained in NASA SP-7037 (28) through NASA SP-7037 (39) of Aeronautical Engineering: A Special Bibliography. NASA SP-7037 and its supplements have been compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). This cumulative index includes subject, personal author, corporate source, contract, and report number indexes