7,805 research outputs found
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
Recommended from our members
Physical layer security for wireless-powered ambient backscatter cooperative communication networks
Low power consumption and high spectrum efficiency as the great challenges for multi-device access to Internet-of-Things (IoT) have put forward stringent requirements on the future intelligent network. Ambient backscatter communication (ABcom) is regarded as a promising technology to cope with the two challenges, where backscatter device (BD) can reflect ambient radio frequency (RF) signals without additional bandwidth. However, minimalist structural design of BD makes ABcom security vulnerable in wireless propagation environments. By virtue of this fact, this paper considers the physical layer security (PLS) of a wireless-powered ambient backscatter cooperative communication network threatened by an eavesdropper, where the BD with nonlinear energy harvesting model cooperates with decode-and-forward (DF) relay for secure communication. The PLS performance is investigated by deriving the secrecy outage probability (SOP) and secrecy energy efficiency (SEE). Specifically, the closed-form and asymptotic expressions of SOP are derived as well as the secrecy diversity order for the first time. As an energy-constrained device, balancing power consumption and security is major concern for BD, thus the SEE of the proposed network is studied. The results from numerical analysis show that the performance improvement of SOP and SEE is impacted by system parameters, including transmit power, secrecy rate threshold, reflection efficiency and distance between the source and BD, which provide guidance on balancing security and energy efficiency in ambient backscatter cooperative relay networks
Performance Analysis and Comparison of Non-ideal Wireless PBFT and RAFT Consensus Networks in 6G Communications
Due to advantages in security and privacy, blockchain is considered a key
enabling technology to support 6G communications. Practical Byzantine Fault
Tolerance (PBFT) and RAFT are seen as the most applicable consensus mechanisms
(CMs) in blockchain-enabled wireless networks. However, previous studies on
PBFT and RAFT rarely consider the channel performance of the physical layer,
such as path loss and channel fading, resulting in research results that are
far from real networks. Additionally, 6G communications will widely deploy
high-frequency signals such as terahertz (THz) and millimeter wave (mmWave),
while performances of PBFT and RAFT are still unknown when these signals are
transmitted in wireless PBFT or RAFT networks. Therefore, it is urgent to study
the performance of non-ideal wireless PBFT and RAFT networks with THz and
mmWave signals, to better make PBFT and RAFT play a role in the 6G era. In this
paper, we study and compare the performance of THz and mmWave signals in
non-ideal wireless PBFT and RAFT networks, considering Rayleigh Fading (RF) and
close-in Free Space (FS) reference distance path loss. Performance is evaluated
by five metrics: consensus success rate, latency, throughput, reliability gain,
and energy consumption. Meanwhile, we find and derive that there is a maximum
distance between two nodes that can make CMs inevitably successful, and it is
named the active distance of CMs. The research results not only analyze the
performance of non-ideal wireless PBFT and RAFT networks, but also provide
important references for the future transmission of THz and mmWave signals in
PBFT and RAFT networks.Comment: arXiv admin note: substantial text overlap with arXiv:2303.1575
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence
Interference mitigation in LiFi networks
Due to the increasing demand for wireless data, the radio frequency (RF) spectrum has
become a very limited resource. Alternative approaches are under investigation to support
the future growth in data traffic and next-generation high-speed wireless communication
systems. Techniques such as massive multiple-input multiple-output (MIMO), millimeter
wave (mmWave) communications and light-fidelity (LiFi) are being explored. Among
these technologies, LiFi is a novel bi-directional, high-speed and fully networked wireless
communication technology. However, inter-cell interference (ICI) can significantly restrict the
system performance of LiFi attocell networks. This thesis focuses on interference mitigation
in LiFi attocell networks.
The angle diversity receiver (ADR) is one solution to address the issue of ICI as well as
frequency reuse in LiFi attocell networks. With the property of high concentration gain and
narrow field of view (FOV), the ADR is very beneficial for interference mitigation. However,
the optimum structure of the ADR has not been investigated. This motivates us to propose the
optimum structures for the ADRs in order to fully exploit the performance gain. The impact
of random device orientation and diffuse link signal propagation are taken into consideration.
The performance comparison between the select best combining (SBC) and maximum ratio
combining (MRC) is carried out under different noise levels. In addition, the double source
(DS) system, where each LiFi access point (AP) consists of two sources transmitting the same
information signals but with opposite polarity, is proven to outperform the single source (SS)
system under certain conditions.
Then, to overcome issues around ICI, random device orientation and link blockage, hybrid
LiFi/WiFi networks (HLWNs) are considered. In this thesis, dynamic load balancing (LB)
considering handover in HLWNs is studied. The orientation-based random waypoint (ORWP)
mobility model is considered to provide a more realistic framework to evaluate the performance
of HLWNs. Based on the low-pass filtering effect of the LiFi channel, we firstly propose
an orthogonal frequency division multiple access (OFDMA)-based resource allocation (RA)
method in LiFi systems. Also, an enhanced evolutionary game theory (EGT)-based LB scheme
with handover in HLWNs is proposed.
Finally, due to the characteristic of high directivity and narrow beams, a vertical-cavity
surface-emitting laser (VCSEL) array transmission system has been proposed to mitigate
ICI. In order to support mobile users, two beam activation methods are proposed. The
beam activation based on the corner-cube retroreflector (CCR) can achieve low power
consumption and almost-zero delay, allowing real-time beam activation for high-speed users.
The mechanism based on the omnidirectional transmitter (ODTx) is suitable for low-speed
users and very robust to random orientation
Educating Sub-Saharan Africa:Assessing Mobile Application Use in a Higher Learning Engineering Programme
In the institution where I teach, insufficient laboratory equipment for engineering education pushed students to learn via mobile phones or devices. Using mobile technologies to learn and practice is not the issue, but the more important question lies in finding out where and how they use mobile tools for learning. Through the lens of Kearney et al.’s (2012) pedagogical model, using authenticity, personalisation, and collaboration as constructs, this case study adopts a mixed-method approach to investigate the mobile learning activities of students and find out their experiences of what works and what does not work. Four questions are borne out of the over-arching research question, ‘How do students studying at a University in Nigeria perceive mobile learning in electrical and electronic engineering education?’ The first three questions are answered from qualitative, interview data analysed using thematic analysis. The fourth question investigates their collaborations on two mobile social networks using social network and message analysis. The study found how students’ mobile learning relates to the real-world practice of engineering and explained ways of adapting and overcoming the mobile tools’ limitations, and the nature of the collaborations that the students adopted, naturally, when they learn in mobile social networks. It found that mobile engineering learning can be possibly located in an offline mobile zone. It also demonstrates that investigating the effectiveness of mobile learning in the mobile social environment is possible by examining users’ interactions. The study shows how mobile learning personalisation that leads to impactful engineering learning can be achieved. The study shows how to manage most interface and technical challenges associated with mobile engineering learning and provides a new guide for educators on where and how mobile learning can be harnessed. And it revealed how engineering education can be successfully implemented through mobile tools
Estudo do IPFS como protocolo de distribuição de conteúdos em redes veiculares
Over the last few years, vehicular ad-hoc networks (VANETs) have been the
focus of great progress due to the interest in autonomous vehicles and in
distributing content not only between vehicles, but also to the Cloud. Performing
a download/upload to/from a vehicle typically requires the existence
of a cellular connection, but the costs associated with mobile data transfers
in hundreds or thousands of vehicles quickly become prohibitive. A VANET
allows the costs to be several orders of magnitude lower - while keeping the
same large volumes of data - because it is strongly based in the communication
between vehicles (nodes of the network) and the infrastructure.
The InterPlanetary File System (IPFS) is a protocol for storing and distributing
content, where information is addressed by its content, instead of
its location. It was created in 2014 and it seeks to connect all computing
devices with the same system of files, comparable to a BitTorrent swarm
exchanging Git objects. It has been tested and deployed in wired networks,
but never in an environment where nodes have intermittent connectivity,
such as a VANET. This work focuses on understanding IPFS, how/if it can
be applied to the vehicular network context, and comparing it with other
content distribution protocols.
In this dissertation, IPFS has been tested in a small and controlled network
to understand its working applicability to VANETs. Issues such as neighbor
discoverability times and poor hashing performance have been addressed.
To compare IPFS with other protocols (such as Veniam’s proprietary solution
or BitTorrent) in a relevant way and in a large scale, an emulation platform
was created. The tests in this emulator were performed in different times of
the day, with a variable number of files and file sizes. Emulated results show
that IPFS is on par with Veniam’s custom V2V protocol built specifically for
V2V, and greatly outperforms BitTorrent regarding neighbor discoverability
and data transfers.
An analysis of IPFS’ performance in a real scenario was also conducted, using
a subset of STCP’s vehicular network in Oporto, with the support of
Veniam. Results from these tests show that IPFS can be used as a content
dissemination protocol, showing it is up to the challenge provided by a
constantly changing network topology, and achieving throughputs up to 2.8
MB/s, values similar or in some cases even better than Veniam’s proprietary
solution.Nos últimos anos, as redes veiculares (VANETs) têm sido o foco de grandes
avanços devido ao interesse em veÃculos autónomos e em distribuir conteúdos,
não só entre veÃculos mas também para a "nuvem" (Cloud). Tipicamente,
fazer um download/upload de/para um veÃculo exige a utilização
de uma ligação celular (SIM), mas os custos associados a fazer transferências
com dados móveis em centenas ou milhares de veÃculos rapidamente se
tornam proibitivos. Uma VANET permite que estes custos sejam consideravelmente
inferiores - mantendo o mesmo volume de dados - pois é fortemente
baseada na comunicação entre veÃculos (nós da rede) e a infraestrutura.
O InterPlanetary File System (IPFS - "sistema de ficheiros interplanetário")
é um protocolo de armazenamento e distribuição de conteúdos, onde a informação
é endereçada pelo conteúdo, em vez da sua localização. Foi criado
em 2014 e tem como objetivo ligar todos os dispositivos de computação num
só sistema de ficheiros, comparável a um swarm BitTorrent a trocar objetos
Git. Já foi testado e usado em redes com fios, mas nunca num ambiente
onde os nós têm conetividade intermitente, tal como numa VANET. Este
trabalho tem como foco perceber o IPFS, como/se pode ser aplicado ao
contexto de rede veicular e compará-lo a outros protocolos de distribuição
de conteúdos.
Numa primeira fase o IPFS foi testado numa pequena rede controlada, de
forma a perceber a sua aplicabilidade às VANETs, e resolver os seus primeiros
problemas como os tempos elevados de descoberta de vizinhos e o fraco desempenho
de hashing.
De modo a poder comparar o IPFS com outros protocolos (tais como a
solução proprietária da Veniam ou o BitTorrent) de forma relevante e em
grande escala, foi criada uma plataforma de emulação. Os testes neste emulador
foram efetuados usando registos de mobilidade e conetividade veicular
de alturas diferentes de um dia, com um número variável de ficheiros e
tamanhos de ficheiros. Os resultados destes testes mostram que o IPFS está
a par do protocolo V2V da Veniam (desenvolvido especificamente para V2V
e VANETs), e que o IPFS é significativamente melhor que o BitTorrent no
que toca ao tempo de descoberta de vizinhos e transferência de informação.
Uma análise do desempenho do IPFS em cenário real também foi efetuada,
usando um pequeno conjunto de nós da rede veicular da STCP no Porto,
com o apoio da Veniam. Os resultados destes testes demonstram que o
IPFS pode ser usado como protocolo de disseminação de conteúdos numa
VANET, mostrando-se adequado a uma topologia constantemente sob alteração,
e alcançando débitos até 2.8 MB/s, valores parecidos ou nalguns
casos superiores aos do protocolo proprietário da Veniam.Mestrado em Engenharia de Computadores e Telemátic
AI-driven blind signature classification for IoT connectivity: a deep learning approach
Non-orthogonal multiple access (NOMA) promises to fulfill the fast-growing connectivities in future Internet of Things (IoT) using abundant multiple-access signatures. While explicitly notifying the utilized NOMA signatures causes large signaling cost, blind signature classification naturally becomes a low-cost option. To accomplish signature classification for NOMA, we study both likelihood- and feature-based methods. A likelihood-based method is firstly proposed and showed to be optimal in the asymptotic limit of the observations, despite high computational complexity. While feature-based classification methods promise low complexity, efficient features are non-trivial to be manually designed. To this end, we resort to artificial intelligence (AI) for deep learning-based automatic feature extraction. Specifically, our proposed deep neural network for signature classification, namely DeepClassifier, establishes on the insights gained from the likelihood-based method, which contains two stages to respectively deal with a single observation and aggregate the classification results of an observation sequence. The first stage utilizes an iterative structure where each layer employs a memory-extended network to explicitly exploit the knowledge of signature pool. The second stage incorporates the straight-through channels within a deep recurrent structure to avoid information loss of previous observations. Experiments show that DeepClassifier approaches the optimal likelihood-based method with a reduction of 90% complexity
- …