2,537 research outputs found
Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey
This paper provides a comprehensive review of the domain of physical layer
security in multiuser wireless networks. The essential premise of
physical-layer security is to enable the exchange of confidential messages over
a wireless medium in the presence of unauthorized eavesdroppers without relying
on higher-layer encryption. This can be achieved primarily in two ways: without
the need for a secret key by intelligently designing transmit coding
strategies, or by exploiting the wireless communication medium to develop
secret keys over public channels. The survey begins with an overview of the
foundations dating back to the pioneering work of Shannon and Wyner on
information-theoretic security. We then describe the evolution of secure
transmission strategies from point-to-point channels to multiple-antenna
systems, followed by generalizations to multiuser broadcast, multiple-access,
interference, and relay networks. Secret-key generation and establishment
protocols based on physical layer mechanisms are subsequently covered.
Approaches for secrecy based on channel coding design are then examined, along
with a description of inter-disciplinary approaches based on game theory and
stochastic geometry. The associated problem of physical-layer message
authentication is also introduced briefly. The survey concludes with
observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with
arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials,
201
Simulations of Large-scale WiFi-based Wireless Networks: Interdisciplinary Challenges and Applications
Wireless Fidelity (WiFi) is the fastest growing wireless technology to date.
In addition to providing wire-free connectivity to the Internet WiFi technology
also enables mobile devices to connect directly to each other and form highly
dynamic wireless adhoc networks. Such distributed networks can be used to
perform cooperative communication tasks such ad data routing and information
dissemination in the absence of a fixed infrastructure. Furthermore, adhoc
grids composed of wirelessly networked portable devices are emerging as a new
paradigm in grid computing. In this paper we review computational and
algorithmic challenges of high-fidelity simulations of such WiFi-based wireless
communication and computing networks, including scalable topology maintenance,
mobility modelling, parallelisation and synchronisation. We explore
similarities and differences between the simulations of these networks and
simulations of interacting many-particle systems, such as molecular dynamics
(MD) simulations. We show how the cell linked-list algorithm which we have
adapted from our MD simulations can be used to greatly improve the
computational performance of wireless network simulators in the presence of
mobility, and illustrate with an example from our simulation studies of worm
attacks on mobile wireless adhoc networks.Comment: Future Generation Computer Systems, Article in Pres
Trustworthy Edge Machine Learning: A Survey
The convergence of Edge Computing (EC) and Machine Learning (ML), known as
Edge Machine Learning (EML), has become a highly regarded research area by
utilizing distributed network resources to perform joint training and inference
in a cooperative manner. However, EML faces various challenges due to resource
constraints, heterogeneous network environments, and diverse service
requirements of different applications, which together affect the
trustworthiness of EML in the eyes of its stakeholders. This survey provides a
comprehensive summary of definitions, attributes, frameworks, techniques, and
solutions for trustworthy EML. Specifically, we first emphasize the importance
of trustworthy EML within the context of Sixth-Generation (6G) networks. We
then discuss the necessity of trustworthiness from the perspective of
challenges encountered during deployment and real-world application scenarios.
Subsequently, we provide a preliminary definition of trustworthy EML and
explore its key attributes. Following this, we introduce fundamental frameworks
and enabling technologies for trustworthy EML systems, and provide an in-depth
literature review of the latest solutions to enhance trustworthiness of EML.
Finally, we discuss corresponding research challenges and open issues.Comment: 27 pages, 7 figures, 10 table
NASA space station automation: AI-based technology review
Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures
Smart Wireless Sensor Networks
The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks
Towards Fairness-Aware Federated Learning
Recent advances in Federated Learning (FL) have brought large-scale
collaborative machine learning opportunities for massively distributed clients
with performance and data privacy guarantees. However, most current works focus
on the interest of the central controller in FL,and overlook the interests of
the FL clients. This may result in unfair treatment of clients which
discourages them from actively participating in the learning process and
damages the sustainability of the FL ecosystem. Therefore, the topic of
ensuring fairness in FL is attracting a great deal of research interest. In
recent years, diverse Fairness-Aware FL (FAFL) approaches have been proposed in
an effort to achieve fairness in FL from different perspectives. However, there
is no comprehensive survey which helps readers gain insight into this
interdisciplinary field. This paper aims to provide such a survey. By examining
the fundamental and simplifying assumptions, as well as the notions of fairness
adopted by existing literature in this field, we propose a taxonomy of FAFL
approaches covering major steps in FL, including client selection,
optimization, contribution evaluation and incentive distribution. In addition,
we discuss the main metrics for experimentally evaluating the performance of
FAFL approaches, and suggest promising future research directions towards
fairness-aware federated learning.Comment: 16 pages, 4 figure
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