3,865 research outputs found
Responsibility and non-repudiation in resource-constrained Internet of Things scenarios
The proliferation and popularity of smart
autonomous systems necessitates the development
of methods and models for ensuring the effective
identification of their owners and controllers. The aim
of this paper is to critically discuss the responsibility of
Things and their impact on human affairs. This starts
with an in-depth analysis of IoT Characteristics such
as Autonomy, Ubiquity and Pervasiveness. We argue
that Things governed by a controller should have an
identifiable relationship between the two parties and
that authentication and non-repudiation are essential
characteristics in all IoT scenarios which require
trustworthy communications. However, resources can
be a problem, for instance, many Things are designed
to perform in low-powered hardware. Hence, we also
propose a protocol to demonstrate how we can achieve the
authenticity of participating Things in a connectionless
and resource-constrained environment
Clarifying fog computing and networking: 10 questions and answers
Fog computing is an end-to-end horizontal architecture that distributes computing, storage, control, and networking functions closer to users along the cloud-to-thing continuum. The word “edge” may carry different meanings. A common usage of the term refers to the edge network as opposed to the core network, with equipment such as edge routers, base stations, and home gateways. In that sense, there are several differences between fog and edge. First, fog is inclusive of cloud, core, metro, edge, clients, and things. The fog architecture will further enable pooling, orchestrating, managing, and securing the resources and functions distributed in the cloud, anywhere along the cloud-to-thing continuum, and on the things to support end-to-end services and applications. Second, fog seeks to realize a seamless continuum of computing services from the cloud to the things rather than treating the network edges as isolated computing platforms. Third, fog envisions a horizontal platform that will support the common fog computing functions for multiple industries and application domains, including but not limited to traditional telco services. Fourth, a dominant part of edge is mobile edge, whereas the fog computing architecture will be flexible enough to work over wireline as well as wireless networks
Foundations of Infrastructure CPS
Infrastructures have been around as long as urban
centers, supporting a society’s needs for its planning, operation,
and safety. As we move deeper into the 21st century, these
infrastructures are becoming smart – they monitor themselves,
communicate, and most importantly self-govern, which we denote
as Infrastructure CPS. Cyber-physical systems are now becoming
increasingly prevalent and possibly even mainstream. With the
basics of CPS in place, such as stability, robustness, and reliability
properties at a systems level, and hybrid, switched, and eventtriggered
properties at a network level, we believe that the time
is right to go to the next step, Infrastructure CPS, which forms
the focus of the proposed tutorial. We discuss three different
foundations, (i) Human Empowerment, (ii) Transactive Control,
and (iii) Resilience. This will be followed by two examples, one
on the nexus between power and communication infrastructure,
and the other between natural gas and electricity, both of which
have been investigated extensively of late, and are emerging to
be apt illustrations of Infrastructure CPS
Self-Evolving Integrated Vertical Heterogeneous Networks
6G and beyond networks tend towards fully intelligent and adaptive design in
order to provide better operational agility in maintaining universal wireless
access and supporting a wide range of services and use cases while dealing with
network complexity efficiently. Such enhanced network agility will require
developing a self-evolving capability in designing both the network
architecture and resource management to intelligently utilize resources, reduce
operational costs, and achieve the coveted quality of service (QoS). To enable
this capability, the necessity of considering an integrated vertical
heterogeneous network (VHetNet) architecture appears to be inevitable due to
its high inherent agility. Moreover, employing an intelligent framework is
another crucial requirement for self-evolving networks to deal with real-time
network optimization problems. Hence, in this work, to provide a better insight
on network architecture design in support of self-evolving networks, we
highlight the merits of integrated VHetNet architecture while proposing an
intelligent framework for self-evolving integrated vertical heterogeneous
networks (SEI-VHetNets). The impact of the challenges associated with
SEI-VHetNet architecture, on network management is also studied considering a
generalized network model. Furthermore, the current literature on network
management of integrated VHetNets along with the recent advancements in
artificial intelligence (AI)/machine learning (ML) solutions are discussed.
Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are
identified. Finally, the potential future research directions for advancing the
autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table
- …