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Labeling Privacy Protection SVM Using Privileged Information for COVID-19 Diagnosis

Edge/fog computing works at the local area network level or devices connected to the sensor or the gateway close to the sensor. These nodes are located in different degrees of proximity to the user, while the data processing and storage are distributed among multiple nodes. In healthcare applications in the Internet of things, when data is transmitted through insecure channels, its privacy and security are the main issues. In recent years, learning from label proportion methods, represented by inverse calibration (InvCal) method, have tried to predict the class label based on class label proportions in certain groups. For privacy protection, the class label of the sample is often sensitive and invisible. As a compromise, only the proportion of class labels in certain groups can be used in these methods. However, due to their weak labeling scheme, their classification performance is often unsatisfactory. In this article, a labeling privacy protection support vector machine using privileged information, called LPP-SVM-PI, is proposed to promote the accuracy of the classifier in infectious disease diagnosis. Based on the framework of the InvCal method, besides using the proportion information of the class label, the idea of learning using privileged information is also introduced to capture the additional information of groups. The slack variables in LPP-SVM-PI are represented as correcting function and projected into the correcting space so that the hidden information of training samples in groups is captured by relaxing the constraints of the classification model. The solution of LPP-SVM-PI can be transformed into a classic quadratic programming problem. The experimental dataset is collected from the Coronavirus disease 2019 (COVID-19) transcription polymerase chain reaction at Hospital Israelita Albert Einstein in Brazil. In the experiment, LPP-SVM-PI is efficiently applied for COVID-19 diagnosis.

Introduction To The Special Section On Edge/Fog Computing For Infectious Disease Intelligence

Fog computing with iot device’s data security management using density control weighted election and extensible authentication protocol, a survey on privacy preservation in fog-enabled internet of things.

Despite the rapid growth and advancement in the Internet of Things (IoT ), there are critical challenges that need to be addressed before the full adoption of the IoT. Data privacy is one of the hurdles towards the adoption of IoT as there might be potential misuse of users’ data and their identity in IoT applications. Several researchers have proposed different approaches to reduce privacy risks. However, most of the existing solutions still suffer from various drawbacks, such as huge bandwidth utilization and network latency, heavyweight cryptosystems, and policies that are applied on sensor devices and in the cloud. To address these issues, fog computing has been introduced for IoT network edges providing low latency, computation, and storage services. In this survey, we comprehensively review and classify privacy requirements for an in-depth understanding of privacy implications in IoT applications. Based on the classification, we highlight ongoing research efforts and limitations of the existing privacy-preservation techniques and map the existing IoT schemes with Fog-enabled IoT schemes to elaborate on the benefits and improvements that Fog-enabled IoT can bring to preserve data privacy in IoT applications. Lastly, we enumerate key research challenges and point out future research directions.

S×C4IoT: A Security-by-contract Framework for Dynamic Evolving IoT Devices

The Internet of Things (IoT) revolutionised the way devices, and human beings, cooperate and interact. The interconnectivity and mobility brought by IoT devices led to extremely variable networks, as well as unpredictable information flows. In turn, security proved to be a serious issue for the IoT, far more serious than it has been in the past for other technologies. We claim that IoT devices need detailed descriptions of their behaviour to achieve secure default configurations, sufficient security configurability, and self-configurability. In this article, we propose S×C4IoT, a framework that addresses these issues by combining two paradigms: Security by Contract (S×C) and Fog computing. First, we summarise the necessary background such as the basic S×C definitions. Then, we describe how devices interact within S×C4IoT and how our framework manages the dynamic evolution that naturally result from IoT devices life-cycles. Furthermore, we show that S×C4IoT can allow legacy S×C-noncompliant devices to participate with an S×C network, we illustrate two different integration approaches, and we show how they fit into S×C4IoT. Last, we implement the framework as a proof-of-concept. We show the feasibility of S×C4IoT and we run different experiments to evaluate its impact in terms of communication and storage space overhead.

A Holistic View on Resource Management in Serverless Computing Environments: Taxonomy and Future Directions

Serverless computing has emerged as an attractive deployment option for cloud applications in recent times. The unique features of this computing model include rapid auto-scaling, strong isolation, fine-grained billing options and access to a massive service ecosystem which autonomously handles resource management decisions. This model is increasingly being explored for deployments in geographically distributed edge and fog computing networks as well, due to these characteristics. Effective management of computing resources has always gained a lot of attention among researchers. The need to automate the entire process of resource provisioning, allocation, scheduling, monitoring and scaling, has resulted in the need for specialized focus on resource management under the serverless model. In this article, we identify the major aspects covering the broader concept of resource management in serverless environments and propose a taxonomy of elements which influence these aspects, encompassing characteristics of system design, workload attributes and stakeholder expectations. We take a holistic view on serverless environments deployed across edge, fog and cloud computing networks. We also analyse existing works discussing aspects of serverless resource management using this taxonomy. This article further identifies gaps in literature and highlights future research directions for improving capabilities of this computing model.

Exploration of Intelligent Manufacturing Methods for Complex Products Driven by Multisource Data

In order to improve the multisource data-driven fusion effect in the intelligent manufacturing process of complex products, based on the proposed adaptive fog computing architecture, this paper takes into account the efficient processing of complex product intelligent manufacturing services within the framework and the rational utilization of fog computing layer resources to establish a fog computing resource scheduling model. Moreover, this paper proposes a fog computing architecture for intelligent manufacturing services for complex products. The architecture adopts a three-layer fog computing framework, which can reasonably provide three types of services in the field of intelligent manufacturing. In addition, this study combines experimental research to verify the intelligent model of this article and counts the experimental results. From the analysis of experimental data, it can be seen that the complex product intelligent manufacturing system based on multisource data driven proposed in this paper meets the data fusion requirements of complex product intelligent manufacturing.

A Data-driven Platform for Simulating Vehicular Fog Computing Environment

<div>Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of compute-intensive vehicular applications such as cooperative driving. Concerning the spatio-temporal variation in the vehicular traffic flows and the demand for edge computing capacity generated by connected vehicles, vehicular fog computing (VFC) has been proposed as a cost-efficient deployment model that complements stationary fog nodes with mobile ones carried by moving vehicles. Accessing the feasibility and the applicability of such hybrid topology, and further planning and managing the networking and computing resources at the edge, require deep understanding of the spatio-temporal variations in the demand and the supply of edge computing capacity as well as the trade-offs between achievable Quality-of-Services and potential deployment and operating costs. To meet such requirements, we propose in this paper an open platform for simulating the VFC environment and for evaluating the performance and cost efficiency of capacity planning and resource allocation strategies under diverse physical conditions and business strategies. Compared with the existing edge/fog computing simulators, our platform supports the mobility of fog nodes and provides a realistic modeling of vehicular networking with the 5G and beyond network in the urban environment. We demonstrate the functionality of the platform using city-scale VFC capacity planning as example. The simulation results provide insights on the feasibility of different deployment strategies from both technical and financial perspectives.</div>

ICN‐Fog Computing for IoT‐Based Healthcare

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Computer Science > Distributed, Parallel, and Cluster Computing

Title: edge, fog, and cloud computing : an overview on challenges and applications.

Abstract: With the rapid growth of the Internet of Things (IoT) and a wide range of mobile devices, the conventional cloud computing paradigm faces significant challenges (high latency, bandwidth cost, etc.). Motivated by those constraints and concerns for the future of the IoT, modern architectures are gearing toward distributing the cloud computational resources to remote locations where most end-devices are located. Edge and fog computing are considered as the key enablers for applications where centralized cloud-based solutions are not suitable. In this paper, we review the high-level definition of edge, fog, cloud computing, and their configurations in various IoT scenarios. We further discuss their interactions and collaborations in many applications such as cloud offloading, smart cities, health care, and smart agriculture. Though there are still challenges in the development of such distributed systems, early research to tackle those limitations have also surfaced.

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Fog Computing or Cloud Computing: a Study

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Secure Edge and Fog Computing Enabled AI for IoT and Smart Cities

Includes selected Papers from International Conference on Advanced Computing & Next-Generation Communication (ICACNGC 2022)

• Ahmed A. Abd El-Latif   ORCID: https://orcid.org/0000-0002-5068-2033 0 ,
• Lo’ai Tawalbeh   ORCID: https://orcid.org/0000-0002-2294-9829 1 ,
• Yassine Maleh 2 ,
• Brij B. Gupta 3

Center of Excellence in Quantum and Intelligent Computing, Prince Sultan University, Riyadh, Saudi Arabia

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Texas A&M University, San Antonio, USA

Sultan Moulay Slimane University, Settat, Morocco

Department of electrical and computer engineering, lebanese american university, beirut, lebanon.

• Discusses, evaluates, and improves approaches in data protections in IoT and edge/ fog computing
• Lays a foundation of the core concepts and principles of IoT and 5G security for edge/ fog computing
• Includes selected papers from ICACNGC 2022

Part of the book series: EAI/Springer Innovations in Communication and Computing (EAISICC)

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Table of contents (19 chapters)

Front matter, ai enabled smart city iot system using edge/fog computing, multilevel edge computing system for autonomous vehicles.

• Mohammed Saleh Ali Muthanna, Dmitry Elkin, Semyon Likhtin, A. M. Al-Sveiti Malik

UAV-Based Edge Computing System for Smart City Applications

• Mehdhar S. A. M. Al-gaashani, Alexander Speransky, Muthana Ali Salem, Alexey Tselykh

Organization of Smart City Services Based on Microservice Architecture

• Mohammed Saleh Ali Muthanna, Dmitry Elkin, Semyon Likhtin, Ammar Muthanna

Pseudo-Random Error-Correcting Codes in Network Coding

• Sergey Vladimirov

Proactive Management in Smart City: Transport Convoys

• Pletnev Yaroslav

Federated Learning for Linux Malware Detection: An Experimental Study

• Tran Duc Le, Phuc Hao Do, Duc Tai Nguyen, Van Thang Phung, Cong Danh Nguyen, Truong Duy Dinh

Delay Prediction in M2M Networks Using the Deep Learning Approach

• Ali R. Abdellah, Malik Alsweity, Mohamed H. Essai, Ammar Muthanna, Andrey Koucheryavy

Energy-Efficient Beam Shaping in MIMO System Using Machine Learning

• Aigul R. Absalyamova, Anna V. Voronkova, Ekaterina A. Lopukhova, Elizaveta P. Grakhova, Rosalina V. Ishakova, Grigoriy S. Voronkov

Channel Cluster Configuration Selection Method for IEEE 802.11 Network Planning

• Anton Vikulov, Alexander Paramonov

Service Migration Algorithm for UAV Recharge Zones in Future 6G Network

• Vadim Kovolenko, Abdelhamied A. Ateya, Ammar Muthanna, Andrey Koucheryavy

FedBA: Non-IID Federated Learning Framework in UAV Networks

• Pei Li, Zhijun Liu, Luyi Chang, Jialiang Peng, Yi Wu

Fog/Edge Computing Security Issues

Big data analytics for secure edge-based manufacturing internet of things (miot).

• Lo’ai Tawalbeh, Swathi Lakkineni, Fadi Muheidat, Ummugul Bulut, Ahmed A. Abd El-latif

Artificial Intelligence-Based Secure Edge Computing Systems for IoTDs and Smart Cities: A Survey

• Muhammad Asim, Chen Junhong, Liu Wenyin, Ahmed A. Abd El-Latif

Machine Learning Techniques for Secure Edge SDN

• Yassine Maleh, Abdelkebir Sahid, Ahmed A. Abd El-Latif, Karim Ouazzane

Machine Learning–Based Identity and Access Management for Cloud Security

• Harun Jamil, Abid Ali, Meryem Ammi, Ruslan Kirichek, Mohammed Saleh Ali Muthanna, Faisal Jamil

Spatial Data of Smart Cities: Trust

• Alexandr Shestakov, Alexey Nesterov

Smart City Infrastructure Projects: Spatial Data of Risks

• Kristina Frolova

This book gathers recent research in security and privacy to discuss, evaluate, and improve the novel approaches of data protection in IoT and edge and fog computing. The primary focus of the book addresses security mechanisms in IoT and edge/ fog computing, advanced secure deployments for large scaled edge/ fog computing, and new efficient data security strategy of IoT and edge/ fog computing. The book lays a foundation of the core concepts and principles of IoT and 5G security, walking the reader through the fundamental ideas. This book is aimed at researchers, graduate students, and engineers in the fields of secure IoT and edge/ fog computing. The book also presents selected papers from International Conference on Advanced Computing & Next-Generation Communication (ICACNGC 2022).

• Trust in social networks in edge/fog computing
• Security policy in IoT and edge/fog computing
• Security in cloud computing in IoT and edge/fog computing
• Privacy in parallel in IoT and edge/fog computing
• edge computing

Ahmed A. Abd El-Latif

Texas A&M University, San Antonio, USA

Lo’ai Tawalbeh

Yassine Maleh

Brij B. Gupta

Ahmed A. Abd El-Latif  (SMIEEE, MACM) received the B.Sc. degree with honour rank in Mathematics and Computer Science in 2005 and M.Sc. degree in Computer Science in 2010, all from Menoufia University, Egypt. He received his Ph. D. degree in Computer Science & Technology at Harbin Institute of Technology (H.I.T), Harbin, P. R. China in 2013. He is an associate professor of Computer Science at Menoufia University, Egypt, and at EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Saudi Arabia. In more than 17 years of his professional experience, he published over 260 papers in journals/conferences including 10 books with over 8800 citations. He was also selected in the 2022, 2021 and 2020 Stanford University's ranking of the world's top 2% scientists. He involved in government and international funded R&D projects related to the widespread use of artificial intelligence for 5G/6G networks. He received many awards, State Encouragement Award in Engineering Sciences 2016, Arab Republic of Egypt; the best Ph.D. student award from Harbin Institute of Technology, China 2013; Young scientific award, Menoufia University, Egypt 2014. He is a fellow at Academy of Scientific Research and Technology, Egypt. His areas of interests are Cybersecurity, 5G/6G Wireless Networks, Post-Quantum Cryptography, Artificial Intelligence of Things, AI-Based Image Processing, Information Hiding, Dynamical systems (Discrete-time models: Chaotic systems and Quantum Walks). He is the leader of mega grant program "Research of network technologies with ultra-low latency and ultra-high density based on the widespread use of artificial intelligence for 6G networks". Dr. Abd El-Latif is the chair/co-chair of many Scopus/ EI conferences. He is the EIC of International Journal of Information Security and Privacy, and series editor of Advances in Cybersecurity Management. Also, academic editor/ associate editor for set of indexedjournals (Scopus journals' quartile ranking).

Lo’ai Tawalbeh (IEEE SM) completed his PhD degree in Electrical & Computer Engineering from Oregon State University in 2004, and MSc in 2002 from the same university with GPA 4/4. Dr. Tawalbeh is currently an Associate professor at the department of Computing and Cyber Security at Texas A&M University-San Antonio. Before that he was a visiting researcher at University of California-Santa Barbra. Since 2005 he taught/developed more than 25 courses in different disciplines of computer engineering and science with focus on cyber security for the undergraduate/graduate programs at: NewYork Institute of Technology (NYIT), DePaul’s University, and Jordan University of Science and Technology. Dr. Tawalbeh won many research grants and awards with over than 2 Million USD. He has over 80 research publications in refereed international Journals and conferences.

Yassine Maleh  is an associate professor of cybersecurityand IT governance at Sultan Moulay Slimane University, Morocco. He is a PhD in computer sciences, since 2017. He is the founding chair of IEEE Consultant Network Morocco and founding president of the African Research Center of Information Technology  Cybersecurity. He is a senior member of IEEE and a member of the International Association of Engineers IAENG and The Machine Intelligence Research Labs. Dr Maleh has made contributions in the fields of information security and privacy, Internet of things security, wireless and constrained networks security. His research interests include information security and privacy, Internet of things, networks security, information system, and IT governance. He has published over than 100 papers (book chapters, international journals, and conferences/workshops), 17edited books, and 3 authored books. He is the editor-in-chief of the  International Journal of Information Security and Privacy, and the   International Journal of Smart Security Technologies  (IJSST). He serves as an associate editor for IEEE Access (2019 Impact Factor 4.098), the  International Journal of Digital Crime and Forensics  (IJDCF), and the  International Journal of Information Security and Privacy  (IJISP). He is a series editor of Advances in Cybersecurity Management, by CRC Taylor & Francis. He was also a guest editor of a special issue on  Recent Advances on Cyber Security and Privacy for Cloud-of-Things of the International Journal of Digital Crime and Forensics  (IJDCF), Volume 10, Issue 3, July–September 2019. He has served and continues to serve on executive and technical program committees and as a reviewer of numerous international conferences and journals such as Elsevier Ad Hoc Networks, IEEE Network Magazine, IEEE Sensor Journal, ICT Express, and Springer Cluster Computing. He was the Publicity chair of BCCA 2019 and the General Chair of the MLBDACP 19 symposium and ICI2C’21 Conference. He received Publons Top 1% reviewer award for the years 2018 and 2019. 

Brij B. Gupta received PhD degree from Indian Institute of Technology Roorkee, India in the area of Information and Cyber Security. In 2009, he was selected for Canadian Commonwealth Scholarship awarded by Government of Canada. He published more than 250 research papers in International Journals and Conferences of high repute. His biography was selected and published in the 30th Edition of Marquis Who's Who in the World, 2012. Dr. Gupta also received Young Faculty research fellowship award from Ministry of Electronics and Information Technology, government of India in 2017. He is also working as principal investigator of various R&D projects. He served as associate editor of IEEE Access, IEEE TII, IJICS, etc. He is also serving as reviewer for Journals of IEEE, Springer, Wiley, Taylor & Francis, etc. He was also visiting researcher with Yamaguchi University, Japan, with Deakin University, Australia and with Swinburne University of Technology, Australia during January, 2015 and 2018, July 2017, and Mar-Apr. 2018, respectively. Moreover, he was also visiting Professor in University of Murcia, Spain in Jun.- Jul., 2018. Additionally, he was visiting professor with Temple university, USA and Staffordshire University, UK during June, 2019 and July 2020, respectively. At present, Dr. Gupta is working as Assistant Professor in the Department of Computer Engineering, National Institute of Technology Kurukshetra India. His research interest includes Information security, Cyber Security, Cloud Computing, Web security, Intrusion detection and Phishing.

Book Title : Secure Edge and Fog Computing Enabled AI for IoT and Smart Cities

Book Subtitle : Includes selected Papers from International Conference on Advanced Computing & Next-Generation Communication (ICACNGC 2022)

Editors : Ahmed A. Abd El-Latif, Lo’ai Tawalbeh, Yassine Maleh, Brij B. Gupta

Series Title : EAI/Springer Innovations in Communication and Computing

DOI : https://doi.org/10.1007/978-3-031-51097-7

Publisher : Springer Cham

eBook Packages : Engineering , Engineering (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

Hardcover ISBN : 978-3-031-51096-0 Published: 20 March 2024

Softcover ISBN : 978-3-031-51099-1 Due: 20 April 2024

eBook ISBN : 978-3-031-51097-7 Published: 19 March 2024

Series ISSN : 2522-8595

Series E-ISSN : 2522-8609

Edition Number : 1

Number of Pages : XVII, 256

Number of Illustrations : 14 b/w illustrations, 81 illustrations in colour

Topics : Communications Engineering, Networks , Systems and Data Security , Security Science and Technology , Information Systems and Communication Service

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IEEE ICFEC 2022

6th IEEE International Conference on Fog and Edge Computing 2022

In Conjunction with CCGrid 2022

18-19 May, 2022 Taormina (Messina), Italy

Registrations Open!

Conference starts in.

LOCATION: Taormina (Messina)

Conference Date: 18-19 May, 2022

Breakout and Networking Session

Billions of devices and sensors ranging from user gadgets to more complex The number of Internet-of-Things (IoT) devices is predicted to reach 38.6 billion by 2025. These connected devices, ranging from user devices to more complex systems, such as vehicles and power grids, are equipped with sensing, actuating, communication, processing, and storage capabilities, and they generate huge amounts of data of various types. However, the need to operate the scale of heterogeneous IoT devices while being performance-efficient in real-time is challenging. Typically, the data generated by the IoT devices are transferred to and processed centrally by services hosted on geographically distant clouds. This is untenable given the communication latency incurred and the ingress bandwidth demand.

A new and disruptive paradigm spear-headed by academics and industry experts is taking shape so that applications can leverage resources located at the edge of the network and along the continuum between the cloud and the edge. These edge resources may be geographically or in the network topology closer to IoT devices, such as home routers, gateways, or more substantial micro data centers. Edge resources may be used to offload selected services from the cloud to accelerate an application or to host edge-native applications. The paradigm within which the edge is harnessed is referred to as "Fog/Edge computing".

The Fog/Edge computing paradigm is expected to improve the agility of service deployments, to allow the usage of opportunistic and cheap computing, and to leverage the network latency and bandwidth diversities between these resources. Numerous challenges arise when using edge resources, which require the re-examination of operating systems, virtualization and containers, and middleware techniques for fabric management. New abstractions and extensions to current programming and storage models are necessary to allow developers to design novel applications that can benefit from massively distributed and data-driven edge systems. Addressing security, privacy, and trust of the edge resources is of paramount importance while managing the resources and context of mobile, transient and hardware-constrained resources. The integration of edge computing and 5G will also bring new opportunities and unique challenges. Enabling machine/deep learning at the edge is critical for many applications. Lastly, emerging domains like autonomous vehicles and smart health need to be supported by fog and edge resources.

Call for Papers

Download the PDF call for papers here

The IEEE International Conference on Fog and Edge Computing seeks to attract high-quality contributions covering both theory and practice over systems research and emerging domain-specific applications related to next-generation distributed systems that use the edge and the fog. Some representative topics of interest include, but are not limited to:

• Data centers and infrastructures for fog/edge computing
• Mobility management in fog/edge computing
• Distributed and federated machine learning in the fog and on the edge
• 5G and fog/edge computing
• Middleware and runtime systems for fog/edge infrastructures
• Programming models for fog/edge computing
• Storage and data management platforms for fog/edge
• Scheduling and resource management for fog/edge infrastructures
• Security, privacy, trust and provenance issues in fog/edge computing
• Distributed consensus and blockchains at the edge and in the fog
• Modelling and simulation of fog/edge environments
• Performance monitoring and metering of fog/edge infrastructures
• Innovative, latency-sensitive and locality-critical applications of fog/edge computing
• Paper submissions: January 7, 2022 January 14, 2022 [11:59 pm AoE] (Firm deadline)
• Notifications: February 20, 2022
• Camera-ready due: March 6, 2022

Paper Submission

IEEE ICFEC 2022 solicits research papers describing novel and previously unpublished scientific contributions to the field of fog and edge computing.

Two different types of papers can be submitted:

• Regular papers (8 pages IEEE double-column format)
• Short papers (5 pages IEEE double-column format)

Regular papers should describe novel and previously unpublished scientific contributions to the field of fog and edge computing. Each regular paper is limited to 8 pages, including tables, figures, and references.

Short papers aim at presenting novel work in progress, novel applications, and novel industry perspectives in the field of fog and edge computing. Each short paper is limited to 5 pages, including tables, figures, and references. Short papers will also be peer-reviewed, however, they will be evaluated with a focus on the potential for establishing new ideas and for sparking the interest of participants.

All papers must be written in English. Manuscripts must include a title, an abstract, and a list of 4-6 keywords. All papers must be prepared in the IEEE double-column proceedings format. Please see: https://www.ieee.org/conferences/publishing/templates.html

IEEE ICFEC 2022 applies a single-blind review policy. All submitted papers will be peer-reviewed by at least three members of the program committee.

Accepted Papers and Program

May 18, 2022, session i: networking aspects [10:15 am - 11:15 am] chair: stefan schulte, session ii: machine learning and data streams [11:45 am - 1:15 pm] chair: radu prodan, session iii: online session [4:30 pm - 6:00 pm] chair: lena mashayekhy, may 19, 2022, session iv: resource allocation [9:00 am - 11:00 am] chair: lorenzo carnevale, session v: miscellaneous topics [11:30 am - 1:00 pm] chair: antonino galletta, note: all icfec presentations will take place in room c.

All accepted papers will be published by IEEE Computer Society Press (EI-Index) and included in the IEEE Digital Library. For publication, each accepted paper is required to be registered by one of its authors, and at least one author is required to attend and present the paper at the conference for the paper to be included in the final technical program and the IEEE Digital Library.

Organization

Icfec 2022 committees, general chairs:.

• Yogesh Simmhan , Indian Institute of Science, India
• Blesson Varghese , Queen's University Belfast, UK

Program Chairs:

• Stefan Schulte , Hamburg University of Technology, Germany
• Lena Mashayekhy , University of Delaware, USA

Steering Committee:

• Rajkumar Buyya , University of Melbourne, Australia
• Adrian Lebre , INRIA, France
• Omer Rana , Cardiff University, UK
• Haiying Shen , University of Virginia, USA
• Anthony Simonet , iExec Blockchain Tech, France
• Massimo Villari , University of Messina, Italy

Publicity Chairs:

• Luiz F. Bittencourt , University of Campinas, Brazil
• Antonino Galletta , University of Messina, Italy
• Bahman Javadi , Western Sydney University, Australia
• Zhuozhao Li , Southern University of Science and Technology, China
• Chenxi Qiu , University of North Texas, USA
• Dixit Bhatta , University of Delaware, USA

Program Committee:

• Atakan Aral, University of Vienna
• Christian Becker, University of Mannheim
• David Bermbach, TU Berlin
• Luiz F. Bittencourt University of Campinas
• Valeria Cardellini, University of Roma "Tor Vergata"
• Lucy Cherkasova, ARM Research
• Alexandre da Silva Veith, University of Toronto
• Luca Davoli, University of Parma
• Schahram Dustdar, Vienna University of Technology
• Khalid Elgazzar, University of Louisiana at Lafayette
• Maria Fazio, University of Messina
• Valerio Frascolla, Intel
• Sukhpal Singh Gill, Queen Mary University of London
• Aniruddha Gokhale, Vanderbilt University
• Daniel Grosu, Wayne State University
• Vasileios Karagiannis, Siemens

Program Committee (continued):

• Hana Khamfroush, University of Kentucky
• Boris Koldehofe, University of Groningen
• Chandra Krintz, UC Santa Barbara
• Adrien Lèbre, Inria/Ecole des Mines
• Laurent Lemarchand, Lab-STICC UBO UEB
• Sérgio I. Lopes, ESTG/IPVC
• Kwangsung Oh, University of Nebraska at Omaha
• Panos Patros, University of Waikato
• Guillaume Pierre, Univ Rennes, Inria, CNRS, IRISA
• Padmanabhan Pillai, Intel
• Radu Prodan, University of Klagenfurt
• Ivan Rodero, Rutgers University
• Olena Skarlat, A1 Austria Telekom Group, Austria
• Hong-Linh Truong, Aalto University
• Lin Wang, Vrije Universiteit Amsterdam
• Shiqiang Wang, IBM

We thank our generous sponsors.

© Copyright: ICFEC 2022

fog computing IEEE PAPER 2022

Fog computing ieee paper 2021.

Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the Internet backbone

Fog computing is a decentralized computing infrastructure in which data, compute, storage and applications are located somewhere between the data source and the cloud. Like edge computing, fog computing brings the advantages and power of the cloud closer to where data is created and acted upon.

Fog computing uses the concept of ‘fog nodes. ‘ These fog nodes are located closer to the data source and have higher processing and storage capabilities. Fog nodes can process the data far quicker than sending the request to the cloud for centralized processing

Fog computing helps to create low-latency network connections between devices and their analytics endpoints. This architecture, in turn, reduces the amount of bandwidth needed when compared to the cloud. It can also be used in scenarios where there is no bandwidth connection needed to transfer data.

Application management in fog computing environments: A taxonomy, review and future directions free download The Internet of Things (IoT) paradigm is being rapidly adopted for the creation of smart environments in various domains. The IoT-enabled cyber-physical systems associated with smart city, healthcare, Industry 4.0 and Agtech handle a huge volume of data and require

Classification of optimization problems in fog computing free download Fog computing combines cloud services with geographically distributed resources near the network edge to offer computational offloading possibilities to end devices, featuring low latency. Optimization of various metrics (latency, bandwidth, energy consumption etc.) plays In recent decade, the number of devices involved with the Internet of Things (IoT) phenomena has increased dramatically. Parallel to this, fog computing paradigm has been introduced in order to support the computational demand of latency-sensitive and real-timeA key application of the Internet of Things (IoT) paradigm lies within industrial contexts. Indeed, the emerging Industrial Internet of Things (IIoT), commonly referred to as Industry 4.0, promises to revolutionize production and manufacturing through the use of large

Design and application of fog computing and Internet of Things service platform for smart city free download Fog computing and Internet of Things technology play a prominent role in the construction of smart cities, which can greatly promote the exchange and management of urban information. Emerging network technologies such as fog computing and the Internet of

A secure authenticated and key exchange scheme for fog computing free download Fog computing architecture is used in various environments such as smart manufacturing, vehicular ad hoc networks. However, as an extension of cloud computing inheriting security challenges of cloud computing is inevitable. Recently, Jia et al. proposed an authenticated Fog computing is an emerging paradigm in provisioning computing and storage resources for the Internet-of-Things (IoT) devices. In a fog computing system, all devices can offload their data or computationally intensive tasks to nearby fog nodes, instead of to the distant As the extension of cloud computing and a foundation of IoT, fog computing is experiencing fast prosperity because of its potential to mitigate some troublesome issues, such as network congestion, latency, and local autonomy. However, privacy issues and the subsequent

On the classification of fog computing applications: A machine learning perspective free download Currently, Internet applications running on mobile devices generate a massive amount of data that can be transmitted to a Cloud for processing. However, one fundamental limitation of a Cloud is the connectivity with end devices. Fog computing overcomes this limitation and Powered by a number of smart devices distributed throughout the whole network, the Internet of Things (IoT) is supposed to provide services computing for massive data from devices. Fog computing an extension of cloud-based IoT-oriented solutions, has emerged

COMITMENT: A fog computing trust management approach free download As an extension of cloud computing fog computing is considered to be relatively more secure than cloud computing due to data being transiently maintained and analyzed on local fog nodes closer to data sources. However, there exist several security and privacy Industrial cyber-physical-social systems (CPSSs), a prominent data-driven paradigm, tightly couple and coordinat social space into cyber-physical systems (CPSs) within industrial environments. With the proliferation of cloud- fog computing cloud- fog computing becomes Abstract Edge/ Fog Computing enables mobility support, location awareness and low latency by offloading cloud resources and services to the edge. Researchers and practitioners have embraced Edge/ Fog Computing as a new approach that has the potential for a profound

Blockchain and fog computing for cyberphysical systems: The case of smart industry free download Blockchain and fog computing are being evaluated as potential support for software and a wide spectrum of critical applications. This article presents the knowledge of blockchain and fog computing required to improve cyberphysical systems. Emerging challenges and issues

Network-aware optimization of distributed learning for fog computing free download Fog computing promises to enable machine learning tasks to scale to large amounts of data by distributing processing across connected devices. Two key challenges to achieving this are (i) heterogeneity in devices compute resources and (ii) topology constraints on which

Comparison of alternative architectures in fog computing free download Since the proliferation of fog computing various distributed architectures have been proposed to extend the cloud to the edge of the network. However, so far there exists no study that compares different fog computing architectures, and produces quantitative results

MAFC: Multi-agent fog computing model for healthcare critical tasks management free download In healthcare applications, numerous sensors and devices produce massive amounts of data which are the focus of critical tasks. Their management at the edge of the network can be done by Fog computing implementation. However, Fog Nodes suffer from lake of

QoS-aware service provisioning in fog computing free download Fog computing has emerged as a complementary solution to address the issues faced in cloud computing . While fog computing allows us to better handle time/delay-sensitive Internet of Everything (IoE) applications (eg smart grids and adversarial environment), there Currently, technology greatly benefits the area of healthcare. Modern computers can quickly process a large volume of patient health records. Due to recent advances in the area of Internet of Things and healthcare, patient data can be dispersed in multiple locations. As a Load scheduling has been a major challenge in distributed fog computing environments for meeting the demands of decision-making in real-time. This research proposes an quantumized approach for scheduling heterogeneous tasks in fog computingbased

Fog computing systems: State of the art, research issues and future trends free download Many future innovative computing services will use Fog Computing Systems (FCS), integrated with Internet of Things (IoT) resources. These new services, built on the convergence of several distinct technologies, need to fulfil time-sensitive functions, provide

ABDKS: attribute-based encryption with dynamic keyword search in fog computing free download Attribute-based encryption with keyword search (ABKS) achieves both fine-grained access control and keyword search. However, in the previous ABKS schemes, the search algorithm requires that each keyword between the target keyword set and the ciphertext keyword set With the advent of new technologies, such as software-defined networks (SDN) and fog computing and the development of communication technology and the vehicular industry, there has been a remarkable growth in intelligent transportation systems (ITS) in recent Fog Computing (FC) utilizes the resources close to the edge of the network. It supports real time applications such as healthcare, industrial systems, and intelligent traffic signs. FC needs data to be cached in various intermediate nodes to be easily found by the network

Securing communication between fog computing and iot using constrained application protocol (coap): A survey free download Nowadays, cloud computing and IoT devices are widely used and involved in our life. However, the current cloud computing paradigm still have some limitation mainly related to the latency, location, and mobility. Thus, to overcome such limitations, Fog Computing was

A novel fog computing approach for minimization of latency in healthcare using machine learning free download In the recent scenario, the most challenging requirements are to handle the massive generation of multimedia data from the Internet of Things (IoT) devices which becomes very difficult to handle only through the cloud. Fog computing technology emerges as an Abstract Global-scale Internet of Things (IoT) applications commonly process a huge amount of data and quickly provide useful information (to users) and instructions to monitor or control the physical world; most of these services are required to be of low latency while satisfyingAs most vehicles remain parked 95% of its time, this suggests that leveraging the use of On- board Units (OBUs) in parked vehicles would provide communication and computation services to other mobile and fixed nodes for delivery of services such as multimedia

Fog computing for healthcare 4.0 environments free download Over the last few decades, we have witnessed various trends in industry standards and applications. For example, Industry 1.0 focused on mechanical engineering and automation, whereas Industry 2.0 focused on electrical energy. The third generation is Industry 3.0

A novel trust mechanism based on Fog Computing in Sensor Cloud System free download Tian Wanga,b, Guangxue Zhanga, MD Zakirul Alam Bhuiyanc, Anfeng Liud, Weijia Jiae, Mande Xief,* a College of Computer Science and Technology, Huaqiao University, Xiamen, Fujian, China b School of Computer Science and Educational Software, Guangzhou University

Fog computing : security challenges and countermeasures free download Innovative technologies such as cloud computing systems provide global cooperative services for end users and medium-large companies. Fog computing extends cloud computing storage networking and computing capabilities to edge and backbone servers onFog computing has become a popular concept in the application of internet of things (IoT). With the superiority in better service providing, the edge cloud has become an attractive solution to IoT networks. The data outsourcing scheme of IoT devices demands privacy Tool condition monitoring (TCM) during the manufacturing process is of great significance for ensuring product quality and plays an important role in intelligent manufacturing. Current TCM systems deployed in the local device or cloud computing environment unable meet the Abstract The potent concept of fog computing is currently attracting many researchers as it brings cloud services closer to the end-user Despite its compelling advantages, fog computing is still an evolving paradigm that demands further research

Fog computing mitigate limitations of cloud computing free download In todays world, cloud computing is the most exciting and advanced technology. It came into existence with lots of advantages, but cloud-only computing has some disadvantages also like latency in real-time data processing, network congestion, less bandwidth utilization, fault Currently, technology greatly benefits the area of healthcare. Modern computers can quickly process a large volume of patient health records. Due to recent advances in the area of Internet of Things and healthcare, patient data can be dispersed in multiple locations. As a Load scheduling has been a major challenge in distributed fog computing environments for meeting the demands of decision-making in real-time. This research proposes an quantumized approach for scheduling heterogeneous tasks in fog computingbased

Fog computing mitigate limitations of cloud computing free download In todays world, cloud computing is the most exciting and advanced technology. It came into existence with lots of advantages, but cloud-only computing has some disadvantages also like latency in real-time data processing, network congestion, less bandwidth utilization, fault

Digital Certificate Verification Scheme for Smart Grid using Fog Computing (FONICA). Sustainability 202 1 2549 free download Smart Grid (SG) infrastructure is an energy network connected with computer networks for communication over the internet and intranets. The revolution of SGs has also introduced new avenues of security threats. Although Digital Certificates provide countermeasures

PF-BVM: A Privacy-aware Fogenhanced Blockchain Validation Mechanism. free download Keywords: Privacy, Fog Computing Blockchain, IoT, Validation, Trust. Abstract Fog computing is one of the recently emerged paradigms that needs to be improved to serve Internet of Things (IoT) environments of the future. In

Resource Management Techniques in Vehicular Fog Computing : A Brief Survey free download Fog Computing is a promising solution designed to address the delay and the overuse of radio resources required for cloud access. To reduce latency and optimize the bandwidth usage, the cloud is to be placed on the network edge. This definition has recently been

Anti-Leakage Client-Side Deduplication with Ownership Management in Fog Computing . free download In commercial fog computing block-level client-side deduplication (BC-Dedu) can be used to save storage space and network bandwidth. However, the existing BC-Dedu schemes cannot support ownership management, which leads to the degradation of forward and

Fog Computing : A New Model Of Internet Based Computing free download Fog computing is a new model in the field of information and communication technology. Fog computing is also known as fog network or fogging. It is an extension of cloud computing and helps to increase the working speed of it. Fog computing works in-between

An Efficient Impersonation Attack Detection Method in Fog Computing free download Fog computing paradigm extends computing communication, storage, and network resources to the networks edge. As the fog layer is located between cloud and end-users, it can provide more convenience and timely services to end-users. However, in fog computing

Scheduling in Fog Computing : A Survey free download Fog computing provides computation, storage and network services for smart manufacturing. However, in a smart factory, the task requests, terminal devices and fog nodes have very strong heterogeneity, such as the different task characteristics of terminal equipment: fault

HEALTHCARE USING FOG COMPUTING WITH EDGE DEVICES free download ABSTRACT The Fog Computing (FC) is a developing processing innovation expects to bring distributed computing highlights near edge gadgets. The methodology is to diminish idleness necessity for medicinal services Internet-of-Things (IoT), edge gadgets. Medicinal

Proposed Methods for Establishing Load Balancing in Fog Computing : A Survey free download Activating application programs among millions of devices in the Internet of things in fog computing needs edge networks. Cloud and data fog computing provide computation, storage and application service for endusers. One of the significant features of fog

An analysis of standardized data for fog computing storage capacity using non-relational database free download Computer applications nowadays relies on physical storage either to store the computation information or for the application itself. As the application become more complex and being used day after day, the data will be growing causing issue with lack of free space especially

AN INVESTIGATION OF DIGITAL FORENSICS FOR SHAMOON ATTACK BEHAVIOUR IN FOG COMPUTING AND THREAT INTELLIGENCE FOR INCIDENT free download Cyber related crimes are increasing nowadays. Thus digital forensics has been employed in solving cybercrimes. Several researches have been done where they have analysed cyber related attacks, malware types, etc. Researches based on studying and analysing Advanced

Reinforcement Learning System for Application Placement in Fog Computing Environment free download The technology of the Internet and mobile devices led the rapid development of cloud computing and IoT. As a result, problems such as data growth and real-time sensitive data processing face the technological limitations of cloud computing . To solve these problems, a

A Comprehensive Method on Fog Computing using Internet-of-Things free download The Internet of Things (IoT) characterizes a significant transformation of the way in which our todays world is expected to interact. IoT is an emerging technology connecting the users towards number of things namely smart phones, smart TV, smart electronic goods like Air

PARTICLE SWARM OPTIMIZATION FOR DECTECTION AND CLASSIFICATION OF APT ATTACK IN FOG COMPUTING ENVIROMENT (IDF-FPSO) free download The hough there are several approaches to detect the malware attacks in cloud, the detection techniques could not be applied in FOG based environment. This is because of its possession of distinct features. As FOG computing has been evolving, it is mandatory to

Introduction to the Minitrack on Internet of Things Security: CyberAssurance for Edge, Software Defined, and Fog Computing Systems free download T Brooks, SK Chin Proceedings of the 54th Hawaii International 128.171.57.22 The objective of this mini-track is to increase the visibility of current research and emergent trends in Cyber-Assurance theory, application, embedded security and machine-learning for the Internet of Things (IoT), software-defined networks (SDN)/network function virtualization

A Study on Review and Analysis of Cloud, Fog and Edge Computing Platforms free download Now a days the need for data is rapidly increasing globally at faster rate, it is necessary to deal with data safely In order to deal with data, we require some of the services like cloud and fog computing . These two computing platforms provide firms to run the communication With the rapid growth of Internet-of-Things (IoT) applications, data volumes have been considerably increased. The processing resources of IoT nodes cannot cope with such huge workloads. Processing parts of the workload in clouds could solve this problem, but the

A Systematic Literature Review on Fog Computing free download The growth and usage of Fog computing is drastically growing in the field of cloud-based solutions. Rather than the required services provided by the Cloud to the Internet of Things (IoT) systems Fog has been used in variety of services. Fog Computing moves the storage

APPLICATION OF IMAGE PROCESSING IN FOG COMPUTING free download Abstract The Internet of Things devices incorporate sensors for sensing and sending data, and Cloud infrastructure, for data analysis. Instead of using Cloud infrastructure, Fog computing could be also used as it brings the data analysis closer to the sensing area. In

Security and Privacy issues of Fog Computing free download Fog processing is a promising registering worldview that extends distributed computing to the edge of systems. Like cloud computing yet with unmistakable attributes, haze registering faces new security, whats more, security challenges other than those acquired from

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