79,701 research outputs found
Federated Embedded Systems – a review of the literature in related fields
This report is concerned with the vision of smart interconnected objects, a vision that has attracted much attention lately. In this paper, embedded, interconnected, open, and heterogeneous control systems are in focus, formally referred to as Federated Embedded Systems. To place FES into a context, a review of some related research directions is presented. This review includes such concepts as systems of systems, cyber-physical systems, ubiquitous
computing, internet of things, and multi-agent systems. Interestingly, the reviewed fields seem to overlap with each other in an increasing number of ways
Big Data and the Internet of Things
Advances in sensing and computing capabilities are making it possible to
embed increasing computing power in small devices. This has enabled the sensing
devices not just to passively capture data at very high resolution but also to
take sophisticated actions in response. Combined with advances in
communication, this is resulting in an ecosystem of highly interconnected
devices referred to as the Internet of Things - IoT. In conjunction, the
advances in machine learning have allowed building models on this ever
increasing amounts of data. Consequently, devices all the way from heavy assets
such as aircraft engines to wearables such as health monitors can all now not
only generate massive amounts of data but can draw back on aggregate analytics
to "improve" their performance over time. Big data analytics has been
identified as a key enabler for the IoT. In this chapter, we discuss various
avenues of the IoT where big data analytics either is already making a
significant impact or is on the cusp of doing so. We also discuss social
implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski
(eds.) Big Data Analysis: New algorithms for a new society, Springer Series
on Studies in Big Data, to appea
AMISEC: Leveraging Redundancy and Adaptability to Secure AmI Applications
Security in Ambient Intelligence (AmI) poses too many challenges due to the inherently insecure nature of wireless sensor nodes. However, there are two characteristics of these environments that can be used effectively to prevent, detect, and confine attacks: redundancy and continuous adaptation. In this article we propose a global strategy and a system architecture to cope with security issues in AmI applications at different levels. Unlike in previous approaches, we assume an individual wireless node is vulnerable. We present an agent-based architecture with supporting services that is proven to be adequate to detect and confine common attacks. Decisions at different levels are supported by a trust-based framework with good and bad reputation feedback while maintaining resistance to bad-mouthing attacks. We also propose a set of services that can be used to handle identification, authentication, and authorization in intelligent ambients. The resulting approach takes into account practical issues, such as resource limitation, bandwidth optimization, and scalability
Research Agenda in Intelligent Infrastructure to Enhance Disaster Management, Community Resilience and Public Safety
Modern societies can be understood as the intersection of four interdependent
systems: (1) the natural environment of geography, climate and weather; (2) the
built environment of cities, engineered systems, and physical infrastructure;
(3) the social environment of human populations, communities and socio-economic
activities; and (4) an information ecosystem that overlays the other three
domains and provides the means for understanding, interacting with, and
managing the relationships between the natural, built, and human environments.
As the nation and its communities become more connected, networked and
technologically sophisticated, new challenges and opportunities arise that
demand a rethinking of current approaches to public safety and emergency
management. Addressing the current and future challenges requires an equally
sophisticated program of research, technology development, and strategic
planning. The design and integration of intelligent infrastructure-including
embedded sensors, the Internet of Things (IoT), advanced wireless information
technologies, real-time data capture and analysis, and machine-learning-based
decision support-holds the potential to greatly enhance public safety,
emergency management, disaster recovery, and overall community resilience,
while addressing new and emerging threats to public safety and security.
Ultimately, the objective of this program of research and development is to
save lives, reduce risk and disaster impacts, permit efficient use of material
and social resources, and protect quality of life and economic stability across
entire regions.Comment: A Computing Community Consortium (CCC) white paper, 4 page
Recommended from our members
Towards a Security, Privacy, Dependability, Interoperability Framework for the Internet of Things
A popular application of ambient intelligence systems constitutes of assisting living services on smart buildings. As intelligence is imported in embedded equipment, the system becomes able to provide smart services (e.g. control lights, airconditioning, provide energy management services etc.). IoT is the main enabler of such environments. However, the interconnection of these cyber-physical systems and the processing of personal data raise serious security and privacy issues. In this paper we present a framework that can guarantee Security, Privacy, Dependability and Interoperability (SPDI) in IoT. Taking advantage of the underlying IoT deployment, the proposed framework not only implements the requested smart functionality but also provide modelling and administration that can guarantee those SPDI properties. Moreover, we provide an application example of the framework in a smart building scenario
- …