Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.9
Journals
Sensors
Special Issues
Advanced Management of Fog/Edge Networks and IoT Sensors Devices
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Advanced Management of Fog/Edge Networks and IoT Sensors Devices

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 8502

Special Issue Editor

Dr. Rocío Pérez de Prado

E-Mail Website
Guest Editor
Department of Telecommunication Engineering, University of Jaén, 23071 Jaén, Spain
Interests: consumption; data centers; scientific workflows; machine learning; soft computing; artificial intelligence; optical communications; cloud computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, an efficient interplay of the different computing and storage capabilities of Fog/Edge networks and IoT sensor devices is a fundamental challenge that needs to be overcome in order to give rise to the highly-demanded integrated services. In spite of the advances in the separate areas of Fog/Edge Networks (typically associated with Cloud infrastructures) and IoT sensor devices, research in the interplay between these areas is still in its initial stages, and we have a long way to go to achieve their global management and harnessing. Particularly, the incorporation and design of intelligent strategies in the management, analysis, and use of the interconnection and planning of networks by Soft-Computing, Big Data or Machine Learning must be regarded as especially important for a deep transformation of and advancement in current associated technologies. The objective of this Special Issue is to support the study, analysis, and implementation of diverse enabling advances in the field of Fog/Edge networks and IoT sensor devices and their interconnection, such as the improvement of virtualization of applications and microservices in IoT sensor devices and Fog/Edge systems, the compatible integration of containers with the main function and performance of containers in IoT sensor devices and Fog/Edge equipment, the security in Fog/Edge and IoT device transactions with Blockchain technology, the improvement of lightweight virtualization systems for deployment in low-performance nodes, such as sensor devices of Fog/Edge networks and IoT or end users, energy reduction in the different layers of a Fog/Edge and IoT network through knowledge-based strategies, accelerating workflow processing in Fog systems, distributed data storage and Big Data tools, intelligent scheduling for container allocation, etc.

Topics to be covered include but are not limited to the following:

  • IoT sensor devices
  • Fog Computing
  • Edge Computing
  • Cloud Computing
  • Fog/Edge and IoT Networks Interplay
  • Content delivery networks
  • Soft-computing
  • Big Data
  • Machine learning
  • Virtualization
  • Containers
  • Scheduling
  • Blockchain
  • Energy consumption in computing distributed networks
  • Latency-aware application in distributed networks

Dr. Rocío Pérez de Prado
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

18 pages, 2498 KiB  
Article
A Hybrid Spider Monkey and Hierarchical Particle Swarm Optimization Approach for Intrusion Detection on Internet of Things
by Sandhya Ethala and Annapurani Kumarappan
Sensors 2022, 22(21), 8566; https://doi.org/10.3390/s22218566 - 07 Nov 2022
Cited by 7 | Viewed by 1677
Abstract
The Internet of Things (IoT) network integrates physical objects such as sensors, networks, and electronics with software to collect and exchange data. Physical objects with a unique IP address communicate with external entities over the internet to exchange data in the network. Due [...] Read more.
The Internet of Things (IoT) network integrates physical objects such as sensors, networks, and electronics with software to collect and exchange data. Physical objects with a unique IP address communicate with external entities over the internet to exchange data in the network. Due to a lack of security measures, these network entities are vulnerable to severe attacks. To address this, an efficient security mechanism for dealing with the threat and detecting attacks is necessary. The proposed hybrid optimization approach combines Spider Monkey Optimization (SMO) and Hierarchical Particle Swarm Optimization (HPSO) to handle the huge amount of intrusion data classification problems and improve detection accuracy by minimizing false alarm rates. After finding the best optimum values, the Random Forest Classifier (RFC) was used to classify attacks from the NSL-KDD and UNSW-NB 15 datasets. The SVM model obtained accuracy of 91.82%, DT of 98.99%, and RFC of 99.13%, and the proposed model obtained 99.175% for the NSL-KDD dataset. Similarly, SVM obtained accuracy of 85.88%, DT of 88.87%, RFC of 91.65%, and the proposed model obtained 99.18% for the UNSW NB-15 dataset. The proposed model achieved accuracy of 99.175% for the NSL-KDD dataset which is higher than the state-of-the-art techniques such as DNN of 97.72% and Ensemble Learning at 85.2%. Full article
(This article belongs to the Special Issue Advanced Management of Fog/Edge Networks and IoT Sensors Devices)
►▼ Show Figures

Figure 1

Review

Jump to: Research

21 pages, 3453 KiB  
Review
Smart Containers Schedulers for Microservices Provision in Cloud-Fog-IoT Networks. Challenges and Opportunities
by Rocío Pérez de Prado, Sebastián García-Galán, José Enrique Muñoz-Expósito, Adam Marchewka and Nicolás Ruiz-Reyes
Sensors 2020, 20(6), 1714; https://doi.org/10.3390/s20061714 - 19 Mar 2020
Cited by 16 | Viewed by 5331
Abstract
Docker containers are the lightweight-virtualization technology prevailing today for the provision of microservices. This work raises and discusses two main challenges in Docker containers’ scheduling in cloud-fog-internet of things (IoT) networks. First, the convenience to integrate intelligent containers’ schedulers based on soft-computing in [...] Read more.
Docker containers are the lightweight-virtualization technology prevailing today for the provision of microservices. This work raises and discusses two main challenges in Docker containers’ scheduling in cloud-fog-internet of things (IoT) networks. First, the convenience to integrate intelligent containers’ schedulers based on soft-computing in the dominant open-source containers’ management platforms: Docker Swarm, Google Kubernetes and Apache Mesos. Secondly, the need for specific intelligent containers’ schedulers for the different interfaces in cloud-fog-IoT networks: cloud-to-fog, fog-to-IoT and cloud-to-fog. The goal of this work is to support the optimal allocation of microservices provided by the main cloud service providers today and used by millions of users worldwide in applications such as smart health, content delivery networks, smart health, etc. Particularly, the improvement is studied in terms of quality of service (QoS) parameters such as latency, load balance, energy consumption and runtime, based on the analysis of previous works and implementations. Moreover, the scientific-technical impact of smart containers’ scheduling in the market is also discussed, showing the possible repercussion of the raised opportunities in the research line. Full article
(This article belongs to the Special Issue Advanced Management of Fog/Edge Networks and IoT Sensors Devices)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop