860 research outputs found
IEEE Access special section editorial: Artificial intelligence enabled networking
With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS)
Guest editorial : intelligent ubiquitous computing and advanced learning systems for biomedical engineering
The health monitoring for disease diagnosis and prognosis in
a desired smart medical structure is realized by interpreting the
health data. The advances in sensor technologies and biomedical
data acquisition tools have led to a new era of big data,
where different sensors collect massive amounts of medical data
every day. This Special Issue explores the latest development
in emerging technologies of biomedical engineering, including
big medical data, artificial intelligence, cloud/fog computing,
federated learning, ubiquitous computing and communication,
internet of things, wireless technologies, and security
and privacy. The biological wearable sensors can enhance the
decision-making and early disease diagnosis processes by intelligently
investigating and collecting large amounts of biomedical
data (i.e. big health data). Hence, there is a need for scalable
advanced learning, and intelligent algorithms that lead to reliable
and interoperable solutions to make effective decisions in
emergency medicine technologies. The optimization algorithms
can be used in order to acquire the sensor data from multiple
sources for fast and accurate health monitoring.peer-reviewe
Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0
This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordCritical infrastructure systems are vital to underpin
the functioning of a society and economy. Due to ever-increasing
number of Internet-connected Internet-of-Things (IoTs) / Industrial IoT (IIoT), and high volume of data generated and collected,
security and scalability are becoming burning concerns for
critical infrastructures in industry 4.0. The blockchain technology
is essentially a distributed and secure ledger that records all
the transactions into a hierarchically expanding chain of blocks.
Edge computing brings the cloud capabilities closer to the
computation tasks. The convergence of blockchain and edge
computing paradigms can overcome the existing security and
scalability issues. In this paper, we first introduce the IoT/IIoT
critical infrastructure in industry 4.0, and then we briefly present
the blockchain and edge computing paradigms. After that, we
show how the convergence of these two paradigms can enable
secure and scalable critical infrastructures. Then, we provide a
survey on state-of-the-art for security and privacy, and scalability
of IoT/IIoT critical infrastructures. A list of potential research
challenges and open issues in this area is also provided, which
can be used as useful resources to guide future research.Engineering and Physical Sciences Research Council (EPSRC
Minimum Throughput Maximization for Multi-UAV Enabled WPCN: A Deep Reinforcement Learning Method
This paper investigates joint unmanned aerial vehicle (UAV) trajectory planning and time resource allocation for minimum throughput maximization in a multiple UAV-enabled wireless powered communication network (WPCN). In particular, the UAVs perform as base stations (BS) to broadcast energy signals in the downlink to charge IoT devices, while the IoT devices send their independent information in the uplink by utilizing the collected energy. The formulated throughput optimization problem which involves joint optimization of 3D path design and channel resource assignment with the constraint of flight speed of UAVs and uplink transmit power of IoT devices, is not convex and thus is extremely difficult to solve directly. We take advantage of the multi-agent deep Q learning (DQL) strategy and propose a novel algorithm to tackle this problem. Simulation results indicate that the proposed DQL-based algorithm significantly improve performance gain in terms of minimum throughput maximization compared with the conventional WPCN scheme
The concept of collaborative engineering: a systematic literature review
Collaborative engineering is not a new subject but it assumes a new importance in the Industry 4.0 (I4.0). There are other concepts frequently mismatched with collaboration. Thus, the main objective of this paper is to put forward a collaborative engineering concept, along its sub concepts, supported by an extensive systematic literature review. A critical analysis and discussion about the fundamental importance of learning, and the central human role in collaboration, in the I4.0, is presented, based on the main insights brought through the literature review. This study also enables to realize about the importance of collaboration in the current digitalization era, along with the importance of recent approaches and technology for enabling or promoting collaboration. Main current practices of human centered and autonomous machine-machine approaches and applications of collaboration in engineering, namely in manufacturing and management, are presented, along
with main difficulties and further open research opportunities on collaboration.This work was supported by the Fundação para a Ciência e a Tecnologia [UIDB/00319/2020,
UIDB/50014/2020, and EXPL/EME-SIS/1224/2021]
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Mundane is the New Radical: The Resurgence of Energy Megaprojects and Implications for the Global South [Opinion]
Modular architecture providing convergent and ubiquitous intelligent connectivity for networks beyond 2030
The transition of the networks to support forthcoming beyond 5G (B5G) and 6G services introduces a number of important architectural challenges that force an evolution of existing operational frameworks. Current networks have introduced technical paradigms such as network virtualization, programmability and slicing, being a trend known as network softwarization. Forthcoming B5G and 6G services imposing stringent requirements will motivate a new radical change, augmenting those paradigms with the idea of smartness, pursuing an overall optimization on the usage of network and compute resources in a zero-trust environment. This paper presents a modular architecture under the concept of Convergent and UBiquitous Intelligent Connectivity (CUBIC), conceived to facilitate the aforementioned transition. CUBIC intends to investigate and innovate on the usage, combination and development of novel technologies to accompany the migration of existing networks towards Convergent and Ubiquitous Intelligent Connectivity (CUBIC) solutions, leveraging Artificial Intelligence (AI) mechanisms and Machine Learning (ML) tools in a totally secure environment
Intergenerational interpretation of the Internet of Things
This report investigates how different generations within a household interpret individual members’ data generated by the Internet of Things (IoT). Adopting a mixed methods approach, we are interested in interpretations of the IoT by teenagers, their parents and grandparents, and how they understand and interact with the kinds of data that might be generated by IoT devices.
The first part of this document is a technical review that outlines the key existing and envisaged technologies that make up the IoT. It explores the definition and scope of the Internet of Things. Hardware, networking, intelligent objects and Human-Computer Interaction implications are all discussed in detail.
The second section focuses on the human perspective, looking at psychological and sociological issues relating to the interpretation of information generated by the IoT. Areas such as privacy, data ambiguity, ageism, and confirmation bias are explored.
The third section brings both aspects together, examining how technical and social aspects of the IoT interact in four specific application domains: energy monitoring, groceries and shopping, physical gaming, and sharing experiences. This section also presents three household scenarios developed to communicate and explore the complexities of integrating IoT technologies into family life.
The final section draws together all the findings and suggests future research
Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities
Smart cities demand resources for rich immersive sensing, ubiquitous
communications, powerful computing, large storage, and high intelligence
(SCCSI) to support various kinds of applications, such as public safety,
connected and autonomous driving, smart and connected health, and smart living.
At the same time, it is widely recognized that vehicles such as autonomous
cars, equipped with significantly powerful SCCSI capabilities, will become
ubiquitous in future smart cities. By observing the convergence of these two
trends, this article advocates the use of vehicles to build a cost-effective
service network, called the Vehicle as a Service (VaaS) paradigm, where
vehicles empowered with SCCSI capability form a web of mobile servers and
communicators to provide SCCSI services in smart cities. Towards this
direction, we first examine the potential use cases in smart cities and
possible upgrades required for the transition from traditional vehicular ad hoc
networks (VANETs) to VaaS. Then, we will introduce the system architecture of
the VaaS paradigm and discuss how it can provide SCCSI services in future smart
cities, respectively. At last, we identify the open problems of this paradigm
and future research directions, including architectural design, service
provisioning, incentive design, and security & privacy. We expect that this
paper paves the way towards developing a cost-effective and sustainable
approach for building smart cities.Comment: 32 pages, 11 figure
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