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Predictive intelligence to the edge through approximate collaborative context reasoning
2017
Applied intelligence (Boston)
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Such novel approximate reasoning paradigm is achieved through a contextualized, collaborative belief-driven clustering process, where clusters of devices are formed according to their belief on the presence ...
Keywords Collaborative event inference · Federated reasoning · Edge predictive intelligence · Optimal stopping theory · Adaptive vector quantization · Type-2 fuzzy logic inference Appl Intell (2018) 48 ...
The energy consumption C c refers to the Predictive intelligence to the edge through approximate collaborative context reasoning communication overhead cost for nodes during the clustering eras due to ...
doi:10.1007/s10489-017-1032-y
fatcat:j23gdptrjfaadc5tr5eertunla
Leveraging Edge Computing through Collaborative Machine Learning
2017
2017 5th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)
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The Internet of Things (IoT) offers the ability to analyze and predict our surroundings through sensor networks at the network edge. ...
To facilitate this predictive functionality, Edge Computing (EC) applications are developed by considering: power consumption, network lifetime and quality of context inference. ...
Using incremental machine learning on the network edge, our methodology exploits the relationship of the context collected to extract knowledge and predict new context. ...
doi:10.1109/ficloudw.2017.72
dblp:conf/ficloud/PortelliA17
fatcat:qsssrhgmxfg5lazgax4dsc3uka
The link prediction problem for social networks
2003
Proceedings of the twelfth international conference on Information and knowledge management - CIKM '03
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We formalize this question as the link prediction problem, and develop approaches to link prediction based on measures for analyzing the "proximity" of nodes in a network. ...
Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? ...
We thank Paul Ginsparg for generously providing the bibliographic data from the arXiv. ...
doi:10.1145/956863.956972
dblp:conf/cikm/Liben-NowellK03
fatcat:n5mxjlhgyjdpdmvwqsnxo75gfa
The link prediction problem for social networks
2003
Proceedings of the twelfth international conference on Information and knowledge management - CIKM '03
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We formalize this question as the link prediction problem, and develop approaches to link prediction based on measures for analyzing the "proximity" of nodes in a network. ...
Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? ...
We thank Paul Ginsparg for generously providing the bibliographic data from the arXiv. ...
doi:10.1145/956958.956972
fatcat:tj47bh7ctzehlmd3qn4gzzylxy
Guest Editorial Special Issue on Edge Intelligence for Sustainable Smart Environments
2022
IEEE Transactions on Green Communications and Networking
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user needs through a more sustainable use of environmental resources; (iii) based on predictions performed by Edge Intelligence algorithms, data and computation can be brought closer to the sites where ...
Edge Intelligence derives from the convergence of Edge Computing with the exploitation of artificial intelligence methodologies and cognitive technologies, involving sensing/actuation, learning and reasoning ...
doi:10.1109/tgcn.2022.3148565
fatcat:b4uruwbajbfrphj2mj5k6q32xy
Intelligent Computing: The Latest Advances, Challenges and Future
[article]
2022
arXiv
pre-print
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Intelligent computing is still in its infancy and an abundance of innovations in the theories, systems, and applications of intelligent computing are expected to occur soon. ...
Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive ...
He used that model to make predictions, reason, and act. ...
arXiv:2211.11281v1
fatcat:e2dtzov2v5bthboxdtdb4i6tiy
Correction to: Predictive intelligence to the edge: impact on edge analytics
2017
Evolving Systems
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Our idea is based on the capability of the edge nodes to (1) monitor the evolution of the sensed time series contextual data, (2) locally determine (through prediction) whether to disseminate contextual ...
We propose a lightweight, distributed, predictive intelligence mechanism that supports communication efficient aggregation and predictive modeling within the edge network. ...
to SANs and ENs to collaboratively support edge analytics. ...
doi:10.1007/s12530-017-9210-z
fatcat:m4m57npzpjhljnvznipuiukhhe
Predictive intelligence to the edge: impact on edge analytics
2017
Evolving Systems
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Our idea is based on the capability of the edge nodes to (1) monitor the evolution of the sensed time series contextual data, (2) locally determine (through prediction) whether to disseminate contextual ...
We propose a lightweight, distributed, predictive intelligence mechanism that supports communication efficient aggregation and predictive modeling within the edge network. ...
to SANs and ENs to collaboratively support edge analytics. ...
doi:10.1007/s12530-017-9190-z
fatcat:qfcv34btffhnvdvum36x6wq2ee
Intelligent Sensing Scheduling for Mobile Target Tracking Wireless Sensor Networks
[article]
2021
arXiv
pre-print
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To address the problems, this paper proposes a new hierarchical target tracking structure based on Edge Intelligence (EI) technology. ...
The structure integrates the computing resource of both mobile nodes and edge servers to provide efficient computation capability for real-time target tracking. ...
#
Mobile node with
computing capacity
Invading target
with context, image,
and video
Sensing link
transmission link
(static node to
mobile node)
Intelligent cloudlet
Intelligent edge ...
arXiv:2108.01885v1
fatcat:5y6dzkotfrcsjfgbka7osgo63q
Deep Learning for Edge Computing Applications: A State-of-the-art Survey
2020
IEEE Access
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Meanwhile, these devices will generate massive amounts of valuable data at the network edge, calling for not only instant data processing but also intelligent data analysis in order to fully unleash the ...
Fortunately, the emerging edge computing sheds a light on the issue by pushing the data processing from the remote network core to the local network edge, remarkably reducing the latency and improving ...
efficiency.
3) CONTEXT-AWARE SERVICE Context-aware computing [25] is playing an important role in IoT and edge computing applications, since good modeling and reasoning of collected data can highly ...
doi:10.1109/access.2020.2982411
fatcat:43atfhktujbuxns2bsl2cfpnay
Editorial: Data-Driven Cognitive Manufacturing—Applications in Predictive Maintenance and Zero Defect Manufacturing
2021
Frontiers in Computer Science
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The Industrial Internet of Things (IIoT) and associated computing continuum Cloud and Edge Technologies and Industrial AI (Artificial Intelligence) provide valuable data for Predictive Maintenance and ...
All of the above is making the smart maintenance and manufacturing development with increasing "cognitive" and "predictive" characteristics to augment the human-machine collaboration. ...
AUTHOR CONTRIBUTIONS All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication. ...
doi:10.3389/fcomp.2020.633850
doaj:fd39552cfb6349d0a5662811216b2fed
fatcat:f64k2nynpne2jjlflx7ssc7lji
The link-prediction problem for social networks
2007
Journal of the American Society for Information Science and Technology
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We formalize this question as the linkprediction problem, and we develop approaches to link prediction based on measures for analyzing the "proximity" of nodes in a network. ...
Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? ...
We thank Paul Ginsparg for generously providing the bibliographic data from the arXiv. An ...
doi:10.1002/asi.20591
fatcat:hgdlaifdcjeotcaiosmm7v7wra
Toward Collaborative Intelligence in IoV Systems: Recent Advances and Open Issues
2022
Sensors
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We discuss existing studies about enabling collaborative intelligence in IoV systems by focusing on collaborative communications, collaborative computing, and collaborative machine learning approaches. ...
While a large number of interesting IoV applications are expected, it is more challenging to design an efficient IoV system compared with conventional Internet of Things (IoT) applications due to the mobility ...
The future service demand is predicted after predicting the future traffic flow through the deep spatiotemporal residual network. (2) Initialize the edge content caching scheme according to the above selection ...
doi:10.3390/s22186995
pmid:36146341
pmcid:PMC9503948
fatcat:ukgdnfjodvbjjgf6fha2cbq5xu
A Context-aware Task Offloading Scheme in Collaborative Vehicular Edge Computing Systems
2021
KSII Transactions on Internet and Information Systems
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Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency ...
On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. ...
Resource Prediction In context-aware collaborative vehicular edge computing networks, the SDN controller can monitor MEC servers load changes in real time. ...
doi:10.3837/tiis.2021.02.001
fatcat:qw4y3a2t5ndwnmrfxs36dmwzjy
Internet of Robotic Things Intelligent Connectivity and Platforms
2020
Frontiers in Robotics and AI
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IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and ...
The emergence of "intelligent things" (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration ...
As the computing power of the edge increases, edge intelligence becomes common, and intelligent edge plays an important supporting role to improve the performance of edge intelligence. ...
doi:10.3389/frobt.2020.00104
pmid:33501271
pmcid:PMC7805974
fatcat:oejpeyynjndnxcq7jsdcotv7ua
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