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Edge Computing for the Internet of Things (IoT)
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Edge Computing for the Internet of Things (IoT)

A special issue of Journal of Sensor and Actuator Networks (ISSN 2224-2708). This special issue belongs to the section "Communications and Networking".

Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 15060

Special Issue Editors

Dr. Xiang Su

E-Mail Website
Guest Editor
Department of Computer Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway
Interests: Internet of Things; edge and fog computing; networking; distributed systems
Special Issues, Collections and Topics in MDPI journals
Dr. Hao Ran Chi

E-Mail Website
Guest Editor
Wireless Systems, Instituto de Telecomunicações and Universidade de Aveiro, Aveiro, Portugal
Interests: 5G (and beyond); IoT development; machine learning; cloud/edge computing; eHealth; optimization modeling

Special Issue Information

Dear Colleagues,

Edge computing is an emerging paradigm that complements cloud computing, with low transmission latency, physically short distance to users, and relatively high privacy protection, which prevents data aggregation relative to centralized computing resources. The Internet of Things (IoT) has enabled physical access between edge/cloud computing and the ambient environment.

However, the conceived user densification towards 6G simultaneously brings challenges and opportunities for future edge computing and (pervasive) IoT development. For instance, corresponding configurations and designs for heterogeneous networks that fuse IoT devices, edge computing, and cloud computing demand significant research efforts with respect to emerging scenarios and applications in 5G/6G. Moreover, boosted pervasive artificial intelligence (AI), softwarization, and virtualization also lead edge computing for IoT to embrace complicated data management process in order to achieve service-level agreement (SLA) or further optimal solutions.

This Special Issue focuses on tackling the corresponding problems for edge computing and IoT technologies, considering the emerging challenges and opportunities raised by cutting-edge communication and computing technologies. We encourage papers in all areas related to this topic, including software architectures, systems, IoT devices, and edge computing (including fog computing, multi-access edge computing, cloudlet, etc.). The papers solicited by this Special Issue cover numerous topics of interest that include but are not limited to the following:

  • Theoretical modeling, analysis, and development for edge computing for IoT;
  • Data management (including decision support, resource allocation, and planning, etc.) for edge computing for IoT;
  • Network configuration and protocol development for edge computing for IoT;
  • Integrated hierarchical system development for the densification of edge computing, IoT, and cloud computing;
  • Softwarization and virtualization based on edge computing for IoT;
  • Embedded AI in edge computing for IoT;
  • Security and privacy strategy for edge computing for IoT;
  • Emerging applications related to edge computing for IoT in 5G beyond 5G and 6G;
  • Integrated testbed and case studies with data analytics for edge computing for IoT.

We welcome your contributions!

Dr. Xiang Su
Dr. Hao Ran Chi
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. Journal of Sensor and Actuator Networks 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 2000 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.

Keywords

  • edge computing
  • Internet of Things (IoT)
  • cloud computing
  • 5G beyond/6G
  • fog computing
  • Big Data
  • cyber-physical systems

Published Papers (4 papers)

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Editorial

Jump to: Research, Review

4 pages, 195 KiB  
Editorial
Editorial: Edge Computing for the Internet of Things
by Hao Ran Chi
J. Sens. Actuator Netw. 2023, 12(1), 17; https://doi.org/10.3390/jsan12010017 - 15 Feb 2023
Cited by 2 | Viewed by 2001
Abstract
Fifth-generation mobile networks (5G) promise higher flexibility compared with 4G, while also fulfilling the service-level agreement (SLA) [...] Full article
(This article belongs to the Special Issue Edge Computing for the Internet of Things (IoT))

Research

Jump to: Editorial, Review

15 pages, 1962 KiB  
Article
Effective One-Class Classifier Model for Memory Dump Malware Detection
by Mahmoud Al-Qudah, Zein Ashi, Mohammad Alnabhan and Qasem Abu Al-Haija
J. Sens. Actuator Netw. 2023, 12(1), 5; https://doi.org/10.3390/jsan12010005 - 17 Jan 2023
Cited by 13 | Viewed by 2581
Abstract
Malware complexity is rapidly increasing, causing catastrophic impacts on computer systems. Memory dump malware is gaining increased attention due to its ability to expose plaintext passwords or key encryption files. This paper presents an enhanced classification model based on One class SVM (OCSVM) [...] Read more.
Malware complexity is rapidly increasing, causing catastrophic impacts on computer systems. Memory dump malware is gaining increased attention due to its ability to expose plaintext passwords or key encryption files. This paper presents an enhanced classification model based on One class SVM (OCSVM) classifier that can identify any deviation from the normal memory dump file patterns and detect it as malware. The proposed model integrates OCSVM and Principal Component Analysis (PCA) for increased model sensitivity and efficiency. An up-to-date dataset known as “MALMEMANALYSIS-2022” was utilized during the evaluation phase of this study. The accuracy achieved by the traditional one-class classification (TOCC) model was 55%, compared to 99.4% in the one-class classification with the PCA (OCC-PCA) model. Such results have confirmed the improved performance achieved by the proposed model. Full article
(This article belongs to the Special Issue Edge Computing for the Internet of Things (IoT))
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17 pages, 3304 KiB  
Article
Fog Computing, Cloud Computing and IoT Environment: Advanced Broker Management System
by Mohammed Al Masarweh, Tariq Alwada’n and Waleed Afandi
J. Sens. Actuator Netw. 2022, 11(4), 84; https://doi.org/10.3390/jsan11040084 - 09 Dec 2022
Cited by 7 | Viewed by 4214
Abstract
Cloud computing is a massive amount of dynamic ad distributed resources that are delivered on request to clients over the Internet. Typical centralized cloud computing models may have difficulty dealing with challenges caused by IoT applications, such as network failure, latency, and capacity [...] Read more.
Cloud computing is a massive amount of dynamic ad distributed resources that are delivered on request to clients over the Internet. Typical centralized cloud computing models may have difficulty dealing with challenges caused by IoT applications, such as network failure, latency, and capacity constraints. One of the introduced methods to solve these challenges is fog computing which makes the cloud closer to IoT devices. A system for dynamic congestion management brokerage is presented in this paper. With this proposed system, the IoT quality of service (QoS) requirements as defined by the service-level agreement (SLA) can be met as the massive amount of cloud requests come from the fog broker layer. In addition, a forwarding policy is introduced which helps the cloud service broker to select and forward the high-priority requests to the appropriate cloud resources from fog brokers and cloud users. This proposed idea is influenced by the weighted fair queuing (WFQ) Cisco queuing mechanism to simplify the management and control of the congestion that may possibly take place at the cloud service broker side. The system proposed in this paper is evaluated using iFogSim and CloudSim tools, and the results demonstrate that it improves IoT (QoS) compliance, while also avoiding cloud SLA violations. Full article
(This article belongs to the Special Issue Edge Computing for the Internet of Things (IoT))
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Review

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46 pages, 2308 KiB  
Review
Mobile Edge Computing in Space-Air-Ground Integrated Networks: Architectures, Key Technologies and Challenges
by Yuan Qiu, Jianwei Niu, Xinzhong Zhu, Kuntuo Zhu, Yiming Yao, Beibei Ren and Tao Ren
J. Sens. Actuator Netw. 2022, 11(4), 57; https://doi.org/10.3390/jsan11040057 - 22 Sep 2022
Cited by 7 | Viewed by 5460
Abstract
Space-air-ground integrated networks (SAGIN) provide seamless global coverage and cross-domain interconnection for the ubiquitous users in heterogeneous networks, which greatly promote the rapid development of intelligent mobile devices and applications. However, for mobile devices with limited computation capability and energy budgets, it is [...] Read more.
Space-air-ground integrated networks (SAGIN) provide seamless global coverage and cross-domain interconnection for the ubiquitous users in heterogeneous networks, which greatly promote the rapid development of intelligent mobile devices and applications. However, for mobile devices with limited computation capability and energy budgets, it is still a serious challenge to meet the stringent delay and energy requirements of computation-intensive ubiquitous mobile applications. Therefore, in view of the significant success in ground mobile networks, the introduction of mobile edge computing (MEC) in SAGIN has become a promising technology to solve the challenge. By deploying computing, cache, and communication resources in the edge of mobile networks, SAGIN MEC provides both low latency, high bandwidth, and wide coverage, substantially improving the quality of services for mobile applications. There are still many unprecedented challenges, due to its high dynamic, heterogeneous and complex time-varying topology. Therefore, efficient MEC deployment, resource management, and scheduling optimization in SAGIN are of great significance. However, most existing surveys only focus on either the network architecture and system model, or the analysis of specific technologies of computation offloading, without a complete description of the key MEC technologies for SAGIN. Motivated by this, this paper first presents a SAGIN network system architecture and service framework, followed by the descriptions of its characteristics and advantages. Then, the MEC deployment, network resources, edge intelligence, optimization objectives and key algorithms in SAGIN are discussed in detail. Finally, potential problems and challenges of MEC in SAGIN are discussed for future work. Full article
(This article belongs to the Special Issue Edge Computing for the Internet of Things (IoT))
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