sensors-logo

Journal Browser

Journal Browser

Edge and Fog Computing for Internet of Things Systems II

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

Deadline for manuscript submissions: closed (15 August 2023) | Viewed by 3088

Special Issue Editors


E-Mail Website
Guest Editor
Department of Computer Science and Engineering, Santa Clara University, Santa Clara, CA, USA
Interests: wireless networking and security mechanisms for internet of things systems; edge and fog computing (SDN, virtualization technologies, resource allocation); traffic flow and channel access control methods using machine learning and scheduling; empirical, simulation-based, and theoretical performance evaluation of IoT systems; mobile computing and energy-efficient software development; design and interfacing of hardware platforms for energy measurement and calibration of IoT devices
Special Issues, Collections and Topics in MDPI journals
Department of Computer Science and Engineering, Santa Clara University, Santa Clara, CA, USA
Interests: trust, security, and privacy issues for internet of things systems; machine learning and AI in edge/fog devices; secure and energy-efficient edge computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Employing edge and fog computing for building IoT systems is essential considering the massive amount of data generated by sensing devices, the delay requirements of IoT applications, the high burden of data processing on cloud platforms, and the need to take immediate action against security threats. By pushing processing and storage closer to IoT devices, it is possible to reduce the amount of data sent to the cloud, while also reducing communication delay. To this end, new data aggregation and processing methods are required to distribute computation across the edge to the cloud continuum. Edge and fog computing can also be used to facilitate communication and resource discovery and enhance the security of IoT devices. New architectures are required to facilitate the communication between IoT devices and servers, depending on the type of application. From the data analytics point of view, efficient and scalable data processing at the edge or task offloading to trustworthy edge/fog nodes is critical to avoid significant delays and network congestion. Meanwhile, the massive and rapidly increasing amount of resource-constrained IoT edge devices has also significantly extended the attack surface, creating new challenges to ensuring data privacy and communication security against emerging threats and establishing trust among multiple communication parties.

In this Special Issue, the following topics are of particular interest:

  • Sensor data processing by edge/fog;
  • Architectures for building edge/fog system;
  • Network function virtualization;
  • Traffic control and traffic shaping;
  • Allocation of computation and communication resources;
  • Edge/fog computing applications, such as healthcare, smart homes, smart cities, and intelligent transportation;
  • Multi-layer collaboration from edge to the cloud;
  • Security, privacy, and trust issues;
  • Secure communication across the edge to cloud continuum;
  • Energy-efficient solutions for edge and fog computing;
  • Signal processing and artificial intelligence.

Dr. Behnam Dezfouli
Dr. Yuhong Liu
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.

Related Special Issue

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

23 pages, 625 KiB  
Article
Performance Evaluation of Container Orchestration Tools in Edge Computing Environments
by Ivan Čilić, Petar Krivić, Ivana Podnar Žarko and Mario Kušek
Sensors 2023, 23(8), 4008; https://doi.org/10.3390/s23084008 - 15 Apr 2023
Cited by 3 | Viewed by 2693
Abstract
Edge computing is a viable approach to improve service delivery and performance parameters by extending the cloud with resources placed closer to a given service environment. Numerous research papers in the literature have already identified the key benefits of this architectural approach. However, [...] Read more.
Edge computing is a viable approach to improve service delivery and performance parameters by extending the cloud with resources placed closer to a given service environment. Numerous research papers in the literature have already identified the key benefits of this architectural approach. However, most results are based on simulations performed in closed network environments. This paper aims to analyze the existing implementations of processing environments containing edge resources, taking into account the targeted quality of service (QoS) parameters and the utilized orchestration platforms. Based on this analysis, the most popular edge orchestration platforms are evaluated in terms of their workflow that allows the inclusion of remote devices in the processing environment and their ability to adapt the logic of the scheduling algorithms to improve the targeted QoS attributes. The experimental results compare the performance of the platforms and show the current state of their readiness for edge computing in real network and execution environments. These findings suggest that Kubernetes and its distributions have the potential to provide effective scheduling across the resources on the network’s edge. However, some challenges still have to be addressed to completely adapt these tools for such a dynamic and distributed execution environment as edge computing implies. Full article
(This article belongs to the Special Issue Edge and Fog Computing for Internet of Things Systems II)
Show Figures

Figure 1

Back to TopTop