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Mobile Fog/Cloud Computing: Open Challenges

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

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 2196

Special Issue Editors


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Guest Editor
Department of Communications Engineering, University of Cantabria, 39005 Santander, Spain
Interests: network coding; WLAN and WPAN technologies; TCP/IP performance analysis over wireless networks; multi-hop and ad hoc network techniques and protocols; wireless sensor networks
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Guest Editor
Department - IoT Digital Platforms, Data Analytics & Artificial Intelligence, Ikerlan
Interests: IoT and IIoT, reliable communications, network coding, QoS, real-time CPS integration in the IoT, Cloud and Fog-based architectures, Artificial Intelligence, data analytics, Edge computing and 5G

Special Issue Information

Dear Colleagues,

The advent of the so-called Industry 4.0 has fostered new business opportunities, but it also poses new and challenging requirements, such as low latency communications and highly reliable systems. IIoT (Industrial Internet of Things) communications would likely exploit new wireless technologies (5G), but then would also require architectures that appropriately support them. Besides pure communication requirements, the use of fog and cloud computing looms as a potential solution to dynamically allocate computational load as required by the various applications that will keep. In this sense, the combination of fog and cloud computing represents a potential solution, since it can dynamically allocate the workload depending on the specific needs of each application. Several challenges need to be faced, such as e2e connectivity considering multiple source/destinations, performance modeling, virtualization techniques, workload allocation, security, etc.

In this Special Issue, we seek submissions of high-quality technical papers reporting original research that has not been previously published, and is not currently submitted for consideration elsewhere, on topics including, but not limited to:

  • Multi cloud/fog architectures
  • Security for mobile fog/cloud computing
  • Connectivity for mobile fog/cloud computing
  • Modeling of mobile fog/cloud computing
  • Performance evaluation of mobile fog/cloud computing
  • Experimental testbeds and plarforms
  • Use of virtualization tecniques for mobile fog/cloud computing
  • IIoT over mobile fog/cloud computing
  • Advanced analytics on fog/cloud architectures
  • Artificial Intelligence in fog/cloud architectures

Dr. Ramón Agüero
Dr. Josu Bilbao
Guest Editors

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 (1 paper)

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17 pages, 2985 KiB  
Article
MoHRiPA—An Architecture for Hybrid Resources Management of Private Cloud Environments
by Gabriel Tomiatti Andreazi, Júlio Cezar Estrella, Sarita Mazzini Bruschi, Roger Immich, Daniel Guidoni, Lourenço Alves Pereira Júnior and Rodolfo Ipolito Meneguette
Sensors 2021, 21(20), 6857; https://doi.org/10.3390/s21206857 - 15 Oct 2021
Cited by 2 | Viewed by 1464
Abstract
The high demand for data processing in web applications has grown in recent years due to the increased computing infrastructure supply as a service in a cloud computing ecosystem. This ecosystem offers benefits such as broad network access, elasticity, and resource sharing, among [...] Read more.
The high demand for data processing in web applications has grown in recent years due to the increased computing infrastructure supply as a service in a cloud computing ecosystem. This ecosystem offers benefits such as broad network access, elasticity, and resource sharing, among others. However, properly exploiting these benefits requires optimized provisioning of computational resources in the target infrastructure. Several studies in the literature improve the quality of this management, which involves enhancing the scalability of the infrastructure, either through cost management policies or strategies aimed at resource scaling. However, few studies adequately explore performance evaluation mechanisms. In this context, we present the MoHRiPA—Management of Hybrid Resources in Private cloud Architecture. MoHRiPA has a modular design encompassing scheduling algorithms, virtualization tools, and monitoring tools. The proposed architecture solution allows assessing the overall system’s performance by using complete factorial planning to identify the general behavior of architecture under high demand of requests. It also evaluates workload behavior, the number of virtualized resources, and provides an elastic resource manager. A composite metric is also proposed and adopted as a criterion for resource scaling. This work presents a performance evaluation by using formal techniques, which analyses the scheduling algorithms of architecture and the experiment bottlenecks analysis, average response time, and latency. In summary, the proposed MoHRiPA mapping resources algorithm (HashRefresh) showed significant improvement results than the analyzed competitor, decreasing about 7% percent in the uniform average compared to ListSheduling (LS). Full article
(This article belongs to the Special Issue Mobile Fog/Cloud Computing: Open Challenges)
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