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Intelligent Centralized and Distributed Secure Edge Computing for Internet of Things Applications Ⅱ

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (10 December 2022) | Viewed by 5075

Special Issue Editors

Prof. Dr. Jihoon Lee

E-Mail Website
Guest Editor
Department of Smart Information and Telecommunication Engineering, Sangmyung University, Cheonan-si, Republic of Korea
Interests: wireless networks; future internet; mobile-oriented information-centric networking; virtual reality (VR) streaming; mobile edge computing (MEC); network security; secure M2M; software-defined networking
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wonjong Noh

E-Mail Website
Guest Editor
School of Software, Hallym University, Chuncheon-si, Gangwon-do, Korea
Interests: network capacity; network optimization; stochastic QoS guarantee; machine learning; information theory
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Daeyoub Kim

E-Mail Website
Guest Editor
Dept. of Information Security, Suwon University, Hwaseong-si, Korea
Interests: secure edge computing; future internet security; ML-based security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

At present, the patterns of application services, networks, and computing are changing very rapidly. First, the rapid improvement of networks and end-systems has led to changes in services from simple applications to a variety of intelligent multimedia applications. Second, improved ubiquitous interoperability and convergence technologies have led to changes in networks, from cellular- and Wi-Fi-based networks to heterogeneous networks including all-IP, device-to-device, ad-hoc, sensor networks, and Internet of Things (IoT). Lastly, new software-defined radio, resource virtualization, and network security technologies have led to user-oriented computing platforms. With these changes, edge computing and cloud computing have become active research areas. Moreover, various smart IoT services such as networked games, smart healthcare, home automation, virtual reality (VR) multimedia, and artificial intelligent (AI) robots are becoming efficient. For the best provision of smart IoT services with edge and cloud computing environments, efficient and intelligent centralized and distributed computing algorithms should be developed.

This Special Issue “Intelligent Centralized and Distributed Secure Edge Computing for Internet of Things Applications II” aims (i) to reflect recent developments in intelligent distributed and centralized controls and algorithms for edge and cloud computing-based IoT (ECI) services, and (ii) to identify critical issues and propose new guidelines that enable the development of future ECI services.

Submissions are expected to focus on both the theoretical aspects and the algorithm and application development of centralized and distributed edge and cloud computing. New ideas proposing disruptive approaches are also welcome.

Topics of interest include, but are not limited to, the following areas:

  • Standardization of edge and cloud computing architectures
  • Computing architectures, frameworks, platforms, and protocols
  • Machine learning for edge and cloud computing
  • Optimization, control, and automation in edge and cloud computing
  • Low-latency communication and networking in edge and cloud computing
  • New edge and cloud computing architecture for data sensing and processing
  • 5G communication architecture and protocols for edge and cloud paradigms
  • Interoperability and mobility for edge and cloud connectivity
  • Big data analytics in edge and cloud paradigms
  • Incentive models or techniques for data processing in edge and cloud paradigms
  • Social IoT in edge and cloud paradigms
  • Security and privacy issues in edge and cloud computing systems
  • Dynamic resource, service, and context management for edge and cloud computing applications
  • Simulation and emulation platforms for edge and cloud computing
  • Algorithms and techniques for computation offloading in edge and cloud paradigms
  • Quality of service provision in edge and cloud paradigms
  • Semantic edge and cloud computing
  • Consumer-centric emerging applications and services in edge and cloud computing
  • Industrial edge and cloud computing
  • Multiparty access control in edge and cloud computing assisted with evolving IoT
  • Middleware for privacy protection in IoT applications

We hope that this Special Issue acts as a roadmap for all developers and users of the centralized and distributed edge and cloud computing platform.

Prof. Dr. Jihoon Lee
Prof. Wonjong Noh
Prof. Dr. Daeyoub Kim
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. Applied Sciences 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 2400 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.

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Published Papers (2 papers)

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16 pages, 421 KiB  
Article
Efficient Data Delivery Scheme for Large-Scale Microservices in Distributed Cloud Environment
by Van-Nam Pham, Md. Delowar Hossain, Ga-Won Lee and Eui-Nam Huh
Appl. Sci. 2023, 13(2), 886; https://doi.org/10.3390/app13020886 - 9 Jan 2023
Cited by 4 | Viewed by 2505
Abstract
The edge computing paradigm has emerged as a new scope within the domain of the Internet of Things (IoT) by bringing cloud services to the network edge in order to construct distributed architectures. To efficiently deploy latency-sensitive and bandwidth-hungry IoT application services, edge [...] Read more.
The edge computing paradigm has emerged as a new scope within the domain of the Internet of Things (IoT) by bringing cloud services to the network edge in order to construct distributed architectures. To efficiently deploy latency-sensitive and bandwidth-hungry IoT application services, edge computing paradigms make use of devices on the network periphery that are distributed and resource-constrained. On the other hand, microservice architectures are becoming increasingly popular for developing IoT applications owing to their maintainability and scalability advantages. Providing an efficient communication medium for large-scale microservice-based IoT applications constructed from small and independent services to cooperate to deliver value-added services remains a challenge. This paper introduces an event-driven communication medium that takes advantage of Edge–Cloud publish/subscribe brokers for microservice-based IoT applications at scale. Using the interaction model, the involved microservices can collaborate and exchange data through triggered events flexibly and efficiently without changing their underlying business logic. In the proposed model, edge brokers are grouped according to their similarities in event channels and the proximity of their geolocations, reducing the data delivery latency. Moreover, in the proposed system a technique is designed to construct a broker-based utility matrix with constraints in order to strike a balance between delay, relay traffic, and scalability while arranging brokers into proper clusters for efficient data delivery. Rigorous simulation results prove that the proposed publish/subscribe model can provide an efficient interaction medium for microservice-based IoT applications to collaborate and exchange data with low latency, modest relay traffic, and high scalability at scale. Full article
(This article belongs to the Special Issue Intelligent Centralized and Distributed Secure Edge Computing for Internet of Things Applications Ⅱ)
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12 pages, 2423 KiB  
Article
The Shortest Verification Path of the MHT Scheme for Verifying Distributed Data
by Daeyoub Kim and Jihoon Lee
Appl. Sci. 2022, 12(21), 11194; https://doi.org/10.3390/app122111194 - 4 Nov 2022
Viewed by 1634
Abstract
One of the most common approaches for enhancing network performance is to retrieve data from nearby data holders that have previously obtained the desired data, not only from the original data source itself. In this case, since a data receiver cannot identify a [...] Read more.
One of the most common approaches for enhancing network performance is to retrieve data from nearby data holders that have previously obtained the desired data, not only from the original data source itself. In this case, since a data receiver cannot identify a practical data sender, it is necessary to verify both the received data and the data sender. Moreover, a data sender generally fragments the data into several small segments and sends them. Therefore, if these segments are retrieved from multiple unknown senders, the receiver must verify every segment to safely use the data. MHT (Merkle hash tree) is suitable for efficiently verifying the set of segments shared in the network. NDN (named-data networking) and Bitcoin utilize MHT to verify transmitted data. However, a data authentication scheme based on the MHT has an inefficient factor that repeatedly computes the same node values of the MHT and are repeatedly computed. The larger the size of the MHT is, the greater the number of calculation iterations. Therefore, as a result, the authentication scheme’s inefficiency is also more severe. When a sender transmits data consisting of many segments through NDN, the data authentication time may take longer than the data transmission time. Hence, in this paper, the degree of the MHT’s inefficiency and the pattern of the iterated operation of the MHT are analyzed first. The proposed improvement is to find repeatedly used node values, store them internally, and use the stored node values without recalculation when required to reuse them. For that process, a rule to select such node values is given. Additionally, when verifying the leaf node value of the MHT, the MHT-based authentication scheme asks a verifier to compute all node values on the path from the leaf node to the root node of the MHT. This paper demonstrates the proposed shortest path selection for verifying the leaf node value. The proposed scheme, using saved node values and the shortest path, reduces the computational overhead of the MHT and improves service latency. It has been proven from performance evaluations that the proposed scheme decreases the computational overhead by more than one-third if the number of segments is more than 1024. Full article
(This article belongs to the Special Issue Intelligent Centralized and Distributed Secure Edge Computing for Internet of Things Applications Ⅱ)
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