931 research outputs found
A threat based approach to computational offloading for collaborative cruise control
The interaction between discrete components of Internet of Things (IoT) and Intelligent Transportation Systems (ITS) is vital for a collaborative system. The secure and reliable use of Cruise Control (CC) with Cloud and Edge Cloud to achieve complete autonomy for a vehicle is a key component and a major challenge for ITS. This research unravels the complications that arise when Adaptive Cruise Control (ACC) is incorporated into a collaborative environment. It mainly answers the question of where to securely compute Collaborative Cruise Control’s (CCC) data in a connected environment. To address this, the paper initially reviews previous research in the domain of Vehicular Cloud, ITS architecture, related threat modelling approaches, and secure implementations of ACC. An overview application model for CCC is developed for performing a threat analysis with the purpose of investigating the reasons why a vehicle suffers collision. Through the use of interviews, the research analyses and suggests the location of computational data by creating a taxonomy between the Edge Cloud, Cloud and the On-board Unit (OBU) while validating the model
New Threats for Old Manufacturing Problems: Secure IoT-Enabled Monitoring of Legacy Production Machinery
The digitization of manufacturing through the introduction of Industrie 4.0 technologies creates additional business opportunities and technical challenges. The integration of such technologies on legacy production machinery can upgrade them to become part of the digital and smart manufacturing environment. A typical example is that of industrial monitoring and maintenance, which can benefit from internet of things (IoT) solutions. This paper presents the development of an-IoT-enabled monitoring solution for machine tools as part of a remote maintenance approach. While the technical challenges pertaining to the development and integration of such solutions in a manufacturing environment have been the subject of relevant research in the literature, the corresponding new security challenges arising from the introduction of such technologies have not received equal attention. Failure to adequately handle such issues is a key barrier to the adoption of such solutions by industry. This paper aims to assess and classify the security aspects of integrating IoT technology with monitoring systems in manufacturing environments and propose a systematic view of relevant vulnerabilities and threats by taking an IoT architecture point of view. Our analysis has led to proposing a novel modular approach for secure IoT-enabled monitoring for legacy production machinery. The introduced approach is implemented on a case study of machine tool monitoring, highlighting key findings and issues for further research
Socially Beneficial Metaverse: Framework, Technologies, Applications, and Challenges
In recent years, the maturation of emerging technologies such as Virtual
Reality, Digital twins, and Blockchain has accelerated the realization of the
metaverse. As a virtual world independent of the real world, the metaverse will
provide users with a variety of virtual activities that bring great convenience
to society. In addition, the metaverse can facilitate digital twins, which
offers transformative possibilities for the industry. Thus, the metaverse has
attracted the attention of the industry, and a huge amount of capital is about
to be invested. However, the development of the metaverse is still in its
infancy and little research has been undertaken so far. We describe the
development of the metaverse. Next, we introduce the architecture of the
socially beneficial metaverse (SB-Metaverse) and we focus on the technologies
that support the operation of SB-Metaverse. In addition, we also present the
applications of SB-Metaverse. Finally, we discuss several challenges faced by
SB-Metaverse which must be addressed in the future.Comment: 28 pages, 6 figures, 3 table
From Traditional Adaptive Data Caching to Adaptive Context Caching: A Survey
Context data is in demand more than ever with the rapid increase in the
development of many context-aware Internet of Things applications. Research in
context and context-awareness is being conducted to broaden its applicability
in light of many practical and technical challenges. One of the challenges is
improving performance when responding to large number of context queries.
Context Management Platforms that infer and deliver context to applications
measure this problem using Quality of Service (QoS) parameters. Although
caching is a proven way to improve QoS, transiency of context and features such
as variability, heterogeneity of context queries pose an additional real-time
cost management problem. This paper presents a critical survey of
state-of-the-art in adaptive data caching with the objective of developing a
body of knowledge in cost- and performance-efficient adaptive caching
strategies. We comprehensively survey a large number of research publications
and evaluate, compare, and contrast different techniques, policies, approaches,
and schemes in adaptive caching. Our critical analysis is motivated by the
focus on adaptively caching context as a core research problem. A formal
definition for adaptive context caching is then proposed, followed by
identified features and requirements of a well-designed, objective optimal
adaptive context caching strategy.Comment: This paper is currently under review with ACM Computing Surveys
Journal at this time of publishing in arxiv.or
Efficient Exchange of Metadata Information in Geo-Distributed Fog Systems
Metadata information is crucial for efficient geo-distributed fog computing
systems. Many existing solutions for metadata exchange overlook geo-awareness
or lack adequate failure tolerance, which are vital in such systems. To address
this, we propose HFCS, a novel hybrid communication system that combines
hierarchical and peer-to-peer elements, along with edge pools. HFCS utilizes a
gossip protocol for dynamic metadata exchange.
In simulation, we investigate the impact of node density and edge pool size
on HFCS performance. We observe a significant performance improvement for
clustered node distributions, aligning well with real-world scenarios.
Additionally, we compare HFCS with a hierarchical system and a peer-to-peer
broadcast approach. HFCS outperforms both in task fulfillment at the cost of an
average 16\% detected failures due to its peer-to-peer structures
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