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An SDN-Enabled Resource Orchestration for Industrial IoT in Collaborative Edge-Cloud Networks

Jude Okwuibe, Juuso Haavisto, Ivana Kovacevic, Erkki Harjula, Ijaz Ahmad, Johirul Islam, Mika Ylianttila
2021 IEEE Access  
ACKNOWLEDGMENT This research work was supported by Academy of Finland, under the projects: 6G Flagship and DigiHealth Projects (grants 318927, 326291) and by the AI Enhanced Mobile Edge Computing project  ...  , funded by the Future Makers program of Jane and Aatos Erkko Foundation and Technology Industries of Finland Centennial Foundation.  ...  Edge computing can provide several desired features for IoT scenarios, such as local pre-processing and filtering of raw data to reduce network burden and avoid unnecessary propagation of sensitive raw  ... 
doi:10.1109/access.2021.3105944 fatcat:fvysjtp54rdr7mzffmutqkxpcq

Special Issue on Methods and Infrastructures for Data Mining at the Edge of Internet of Things

Giancarlo Fortino, Rajkumar Buyya, Min Chen, Francisco Herrera
2021 IEEE Internet of Things Journal  
We hope that this special issue will serve as a useful reference for researchers, scientists, engineers, and academics in the field of data mining and machine learning at the "edge" of the IoT.  ...  We would like to express our sincere thanks to all the authors for submitting their papers and to the reviewers for their valuable comments and suggestions that significantly enhanced the quality of these  ...  In this special issue, new data mining approaches particularly tailored for the IoT scenario were investigated, in particular with respect to the promising and emerging novel distributed computing paradigm  ... 
doi:10.1109/jiot.2021.3075304 fatcat:ulaytitbj5aqfnvv5ewybffrey

Ensemble-Based Network Edge Processing

Ioan Petri, Ali Reza Zamani, Daniel Balouek-Thomert, Omer Rana, Yacine Rezgui, Manish Parashar
2018 2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)  
The suggested approach is however general in scope and can be used in other similar application domains.  ...  A scenario based on energy profiling within a fisheries plant is used to illustrate the use of an edge ensemble.  ...  Acknowledgements: The research presented in this work is supported by EU INTEREG piSCES project, Smart Cluster Energy System for Fish Processing Industries.  ... 
doi:10.1109/ucc.2018.00022 dblp:conf/ucc/PetriZBRRP18 fatcat:cvtzbbwhgvho3fwbgweai5qula

An Energy-Efficient Partial Data Offloading-Based Priority Rate Controller Technique in Edge-Based IoT Network to Improve QoS

Malvinder Singh Bali, Kamali Gupta, Shalli Rani, Rajnish Ratna, Mohammad Farukh Hashmi
2022 Wireless Communications and Mobile Computing  
To counter this problem, a data offloading-based heuristic technique using edge computing is proposed in IIoT-based applications.  ...  As a result, data offloading has become a popular issue in academic and industrial sectors, specifically for traffic-intensive applications that can benefit from offloading to local edge and cloud infrastructure  ...  The challenge addressed in this research is to use a partial data offloading approach in an IoT network based on edge computing to reduce data traffic in the industrial IoT sector.  ... 
doi:10.1155/2022/4288663 fatcat:2aae6pdnyndbnlhy2dmpn57vh4

Deep Learning for Edge Computing Applications: A State-of-the-art Survey

Fangxin Wang, Miao Zhang, Xiangxiang Wang, Xiaoqiang Ma, Jiangchuan Liu
2020 IEEE Access  
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  ...  The convergence of edge computing and deep learning is believed to bring new possibilities to both interdisciplinary researches and industrial applications.  ...  Last but not least, data processing at the network edge can effectively reduce traffic at the backbone network so as to alleviate the network pressure.  ... 
doi:10.1109/access.2020.2982411 fatcat:43atfhktujbuxns2bsl2cfpnay

Towards In-Transit Analytics for Industry 4.0

Richard Hill, James Devitt, Ashiq Anjum, Muhammad Ali
2017 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)  
Industry 4.0, or Digital Manufacturing, is a vision of inter-connected services to facilitate innovation in the manufacturing sector.  ...  A fundamental requirement of innovation is the ability to be able to visualise manufacturing data, in order to discover new insight for increased competitive advantage.  ...  In-Transit Analytics Edge computing Edge computing is a design approach whereby data processing capabilities are distributed across the whole of a network infrastructure.  ... 
doi:10.1109/ithings-greencom-cpscom-smartdata.2017.124 dblp:conf/ithings/HillDAA17 fatcat:7b33ff3oazg2lgdodt7yk7njny

Towards In-Transit Analytics for Industry 4.0 [article]

Richard Hill, James Devitt, Ashiq Anjum, Muhammad Ali
2017 arXiv   pre-print
Industry 4.0, or Digital Manufacturing, is a vision of inter-connected services to facilitate innovation in the manufacturing sector.  ...  A fundamental requirement of innovation is the ability to be able to visualise manufacturing data, in order to discover new insight for increased competitive advantage.  ...  In-Transit Analytics Edge computing Edge computing is a design approach whereby data processing capabilities are distributed across the whole of a network infrastructure.  ... 
arXiv:1710.04121v1 fatcat:flkejodkbfb7hbmxfbhymvns34

Investigating and Modelling of Task Offloading Latency in Edge-Cloud Environment

Jaber Almutairi, Mohammad Aldossary
2021 Computers Materials & Continua  
Therefore, this paper presents an Edge-Cloud system architecture that supports scheduling offloading tasks of IoT applications in order to minimize the enormous amount of transmitting data in the network  ...  Also, it introduces the offloading latency models to investigate the delay of different offloading scenarios/schemes and explores the effect of computational and communication demand on each one.  ...  Also, it explores the effect of computational and communication for each offloading scenario/scheme, which are: (1) offloading to the local edge, (2) offloading to the local edge with the cloud and (3)  ... 
doi:10.32604/cmc.2021.018145 fatcat:46pbuzurxzgx5nj5mu7vksu2tq

A Survey of Architecture, Framework and Algorithms for Resource Management in Edge Computing

S. Premkumar, A. Sigappi
2020 EAI Endorsed Transactions on Energy Web  
Edge computing is an imminent computing methodology that deploys the decentralized resources present at the edge of the network to make data processing within the proximity of user devices like smartphones  ...  in edge computing.  ...  Solver approach is focussed at processing costs and reducing network. ii.  ... 
doi:10.4108/eai.23-12-2020.167788 fatcat:vcok5rac35gajhvgtxcclawuje

Managing the far-Edge: are today's centralized solutions a good fit?

Gabriele Baldoni, Luca Cominardi, Milan Groshev, Antonio De la Oliva, Angelo Corsaro
2021 Zenodo  
Edge computing has established itself as the foundation for next-generation mobile networks, IT infrastructure, and industrial systems thanks to promised low network latency, computation offloading, and  ...  Results show that mainstream Edge solutions require powerful centralized controllers and always-on connectivity, making them unsuitable for highly decentralized scenarios in the far-Edge where stable and  ...  This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-DIVE (grant no. 859881) and by the H2020 European collaborative research project DAEMON (grant no. 101017109  ... 
doi:10.5281/zenodo.4923689 fatcat:rgcdt7ef4nepnc5vfeaf3w4hku

A Classification of the Enabling Techniques for Low Latency and Reliable Communications in 5G and Beyond: AI-Enabled Edge Caching

Lilian C. Mutalemwa, Seokjoo Shin
2020 IEEE Access  
In [83] , an edge learning system was developed for networked intelligent applications to effectively reduce network traffic and inference latency.  ...  In [130] , DL for IoT was used in edge computing environment to improve the learning performance and reduce the network traffic.  ... 
doi:10.1109/access.2020.3037357 fatcat:khkeuvo6ujanhp42y2k372n5u4

A Survey of State-of-the-art on Edge Computing: Theoretical Models, Technologies, Directions, and Development Paths

Bin Liu, Zhongqiang Luo, Hongbo Chen, Chengjie Li
2022 IEEE Access  
To fill this gap, by identifying and classifying, we carry out an in-depth survey of the latest high-quality literatures related to the theoretical discoveries in edge computing(EC) and the fusion of EC  ...  Edge computing theory and technology will bring substantial innovation and incentive, as well as a large number of application scenarios in different fields, such as edge computing assisted smart city,  ...  address reliability in edge scenarios, how to perform secure authentication, how to reduce transport latency, etc.  ... 
doi:10.1109/access.2022.3176106 fatcat:7l3p2ug5dfb6pl6qvw7liuzayu

Simulating Fog and Edge Computing Scenarios: An Overview and Research Challenges

Sergej Svorobej, Patricia Takako Endo, Malika Bendechache, Christos Filelis-Papadopoulos, Konstantinos Giannoutakis, George Gravvanis, Dimitrios Tzovaras, James Byrne, Theo Lynn
2019 Future Internet  
This paper provides an overview of challenges posed by fog and edge computing in relation to simulation.  ...  The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other.  ...  From the cloud perspective, deciding whether to cache or process the data offload is one way to alleviate network congestion and reduce data transfer costs; from an edge device perspective, offloading  ... 
doi:10.3390/fi11030055 fatcat:jevpfskmqrffnk2ovmwwju2prm

A Review on Edge Computing in Smart Energy by means of a Systematic Mapping Study

Inés Sittón-Candanedo, Ricardo S. Alonso, Óscar García, Ana B. Gil, Sara Rodríguez-González
2019 Electronics  
Edge Computing is included in this new technology group. Objective: To investigate developments that involve the use of Edge Computing and that provide solutions to Smart Energy problems.  ...  In the future, such architectures will overcome current problems, becoming highly energy-efficient, cost-effective, and capacitated to process and respond in real-time.  ...  The aim of these approaches is to effectively manage the use of energy and reducing consumption.  ... 
doi:10.3390/electronics9010048 fatcat:qgdsqcvn7nflbmgp2ddwoxm4lq

An Edge-based Architecture to Support Efficient Applications for Healthcare Industry 4.0

Pasquale Pace, Gianluca Aloi, Raffaele Gravina, Giuseppe Caliciuri, Giancarlo Fortino, Antonio Liotta
2018 IEEE Transactions on Industrial Informatics  
Edge computing paradigm has attracted many interests in the last few years as a valid alternative to the standard Cloud-based approaches to reduce the interaction timing and the huge amount of data coming  ...  In the next future, Edge-based approaches will be essential to support time-dependent applications in the Industry 4.0 context; thus, the paper proposes BodyEdge, a novel architecture well suited for human-centric  ...  that Cloud computing is not an efficient way to process data when data are produced at the edge of the network [5] .  ... 
doi:10.1109/tii.2018.2843169 fatcat:plm6ktytdvfl7gqyjelnrjlil4
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