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Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 16170

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Special Issue Editor

Prof. Dr. Byung-Seo Kim

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Department of Software and Communications Energy, Hongik University, Sejongro 2639, Republic of Korea
Interests: wireless networks and communications; WSN; wireless ICN; edge computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 9th International Conference on Green and Human Information Technology (ICGHIT 2021) will be held on 13–15 January, 2021, in Jeju Island, Korea (http://icghit.org/ ). The 9th International Conference on Green and Human Information Technology is a unique global conference for researchers, industry professionals, and academics who are interested in the latest developments in green and human information technology. The goal of ICGHIT is to form a platform to seek the advancement of green technology and human-related IT in an interdisciplinary manner. The main topics of the conference are green information technology, communication and IoT, computer and network security, multimedia and signal processing, control and intelligent systems, and SW/HW design, architecture, and development. Centering on the main topics, ICGHIT will provide an exciting program: hands-on experience-based tutorial sessions and special sessions covering research issues and directions with applications from both theoretical and practical viewpoints. The conference will also include plenary sessions, technical sessions, and workshops with special sessions. Highly qualified papers selected from ICGHIT 2021 will be invited to this Special Issue for publication. However, the Special Issue also welcomes submissions from researchers which fit into the scope as shown below. The topics of this Special Issue include but are not limited to: green information technology; green technology and energy saving; green computing and green IT convergence and applications; energy harvest-based communications and networking; technologies for network sustainability communications and networks for IoT and 5G and beyond; communications and networks for massive IoT and 5G; optical and visual light communication; ad-hoc and sensor networks; M2M/IoT and ubiquitous computing; NFV, SDN, ICN, network slicing; AI and ML-based technologies; computer and network security; block-chain-based networking and applications; distributed PKI; applied cryptography; security in big data and cloud computing; security for future internet architecture (SDN, ICN, etc.); control and intelligent systems; automatic control and neural and fuzzy networks; artificial intelligence and HCI; intelligent robotics and transportation and HRI; brain science and bioengineering networks; SW/HW design, architecture, and applications; architecture and protocols; sustainable sensor networks; information-centric sensor networks; blockchain-based secure sensor networks; AI-based self-evolving sensor networks; sensor/RFID circuit design; system on chip (SoC); IC system for communication.

Dr. Byung-Seo Kim
Guest Editor

Manuscript Submission Information

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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.

Keywords

green information technology
communication and IoT
computer and network security
multimedia and signal processing
control and intelligent systems
SW/HW design
architecture and development

Published Papers (7 papers)

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Editorial

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4 pages, 158 KiB

Open AccessEditorial

Emerging Technologies for Next-Generation Applied Science Systems

by Byung-Seo Kim

Appl. Sci. 2022, 12(4), 1801; https://0-doi-org.brum.beds.ac.uk/10.3390/app12041801 - 09 Feb 2022

Cited by 1 | Viewed by 979

Abstract

In the past decade, unlike other industries, Information Technology has been substantially advanced and improved [...] Full article

(This article belongs to the Special Issue Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021)

Research

Jump to: Editorial

11 pages, 2541 KiB

Open AccessArticle

A Fog Computing Architecture with Multi-Layer for Computing-Intensive IoT Applications

by Muhammad Muneeb, Kwang-Man Ko and Young-Hoon Park

Appl. Sci. 2021, 11(24), 11585; https://0-doi-org.brum.beds.ac.uk/10.3390/app112411585 - 07 Dec 2021

Cited by 17 | Viewed by 2504

Abstract

The emergence of new technologies and the era of IoT which will be based on compute-intensive applications. These applications will increase the traffic volume of today’s network infrastructure and will impact more on emerging Fifth Generation (5G) system. Research is going in many details, such as how to provide automation in managing and configuring data analysis tasks over cloud and edges, and to achieve minimum latency and bandwidth consumption with optimizing task allocation. The major challenge for researchers is to push the artificial intelligence to the edge to fully discover the potential of the fog computing paradigm. There are existing intelligence-based fog computing frameworks for IoT based applications, but research on Edge-Artificial Intelligence (Edge-AI) is still in its initial stage. Therefore, we chose to focus on data analytics and offloading in our proposed architecture. To address these problems, we have proposed a prototype of our architecture, which is a multi-layered architecture for data analysis between cloud and fog computing layers to perform latency- sensitive analysis with low latency. The main goal of this research is to use this multi-layer fog computing platform for enhancement of data analysis system based on IoT devices in real-time. Our research based on the policy of the OpenFog Consortium which will offer the good outcomes, but also surveillance and data analysis functionalities. We presented through case studies that our proposed prototype architecture outperformed the cloud-only environment in delay-time, network usage, and energy consumption. Full article

(This article belongs to the Special Issue Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021)

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15 pages, 1064 KiB

Open AccessArticle

Efficiently Supporting Online Privacy-Preserving Data Publishing in a Distributed Computing Environment

by Jong Wook Kim

Appl. Sci. 2021, 11(22), 10740; https://0-doi-org.brum.beds.ac.uk/10.3390/app112210740 - 14 Nov 2021

Cited by 1 | Viewed by 1500

Abstract

There has recently been an increasing need for the collection and sharing of microdata containing information regarding an individual entity. Because microdata typically contain sensitive information on an individual, releasing it directly for public use may violate existing privacy requirements. Thus, extensive studies have been conducted on privacy-preserving data publishing (PPDP), which ensures that any microdata released satisfy the privacy policy requirements. Most existing privacy-preserving data publishing algorithms consider a scenario in which a data publisher, receiving a request for the release of data containing personal information, anonymizes the data prior to publishing—a process that is usually conducted offline. However, with the increasing demand for the sharing of data among various parties, it is more desirable to integrate the data anonymization functionality into existing systems that are capable of supporting online query processing. Thus, we developed a novel scheme that is able to efficiently anonymize the query results on the fly, and thus support efficient online privacy-preserving data publishing. In particular, given a user’s query, the proposed approach effectively estimates the generalization level of each quasi-identifier attribute, thereby achieving the k-anonymity property in the query result datasets based on the statistical information without applying k-anonymity on all actual datasets, which is a costly procedure. The experiment results show that, through the proposed method, significant gains in processing time can be achieved. Full article

(This article belongs to the Special Issue Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021)

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15 pages, 1471 KiB

Open AccessArticle

Secure Outsourced Blockchain-Based Medical Data Sharing System Using Proxy Re-Encryption

by Young-Hoon Park, Yejin Kim, Shin-Ok Lee and Kwangman Ko

Appl. Sci. 2021, 11(20), 9422; https://0-doi-org.brum.beds.ac.uk/10.3390/app11209422 - 11 Oct 2021

Cited by 10 | Viewed by 2439

Abstract

The security and privacy of electronic health records (EHRs) have received considerable attention from healthcare workers and researchers. To ensure security, various encryption and decryption schemes as well as key management protocols have been developed. However, owing to sharing and scalability issues, additional security technologies have been proposed. Nonetheless, these technologies cause other problems, such as efficiency issues. Blockchain-based EHR management systems have been proposed to overcome computational overhead. However, because most blockchain systems are installed by outsourcing companies, EHRs may be leaked to the company. Hence, we herein propose a blockchain-based EHR management scheme with proxy re-encryption. In this scheme, we set a proxy server that re-encrypts the ciphertext between file servers, thereby solving EHR sharing issues. Furthermore, because the server is separated from the blockchain system, the outsourcing company cannot manipulate the server or access the records. In addition, the blockchain assists in access control by using smart contracts, thereby enabling secure and efficient EHR sharing. By performing security analysis, we prove that our proposed scheme solves the aforementioned security problems. In addition, we experimentally demonstrate the efficient operation of the proposed system. Full article

(This article belongs to the Special Issue Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021)

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17 pages, 3878 KiB

Open AccessArticle

Development of Cybersecurity Technology and Algorithm Based on Quantum Computing

by Kyung-Kyu Ko and Eun-Sung Jung

Appl. Sci. 2021, 11(19), 9085; https://0-doi-org.brum.beds.ac.uk/10.3390/app11199085 - 29 Sep 2021

Cited by 6 | Viewed by 3653

Abstract

Many hacking incidents are linked to work files because most companies work with them. However, a variety of file encryption and decryption methods have been proposed. Existing file encryption/decryption technologies are under threat as hacking technologies advance, necessitating the development of stronger encryption algorithms. Therefore, in this study, we propose a modified advanced encryption standard (AES) algorithm and use quantum computing to encrypt/decrypt AES image files. Because the shift is regular during the AES Shift Row procedure, the change technique led the shift to become irregular when using quantum random walk. Computing resources and speeds were simulated using IBM Qiskit quantum simulators for performance evaluation, whereas encryption performance was assessed using number of pixels change rate (NPCR) and unified average changing intensity (UACI). Full article

(This article belongs to the Special Issue Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021)

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18 pages, 1384 KiB

Open AccessArticle

Intelligent Stretch Optimization in Information Centric Networking-Based Tactile Internet Applications

by Hussain Ahmad, Muhammad Zubair Islam, Rashid Ali, Amir Haider and Hyungseok Kim

Appl. Sci. 2021, 11(16), 7351; https://0-doi-org.brum.beds.ac.uk/10.3390/app11167351 - 10 Aug 2021

Cited by 4 | Viewed by 2157

Abstract

The fifth-generation (5G) mobile network services are currently being made available for different use case scenarios like enhanced mobile broadband, ultra-reliable and low latency communication, and massive machine-type communication. The ever-increasing data requests from the users have shifted the communication paradigm to be based on the type of the requested data content or the so-called information-centric networking (ICN). The ICN primarily aims to enhance the performance of the network infrastructure in terms of the stretch to opt for the best routing path. Reduction in stretch merely reduces the end-to-end (E2E) latency to ensure the requirements of the 5G-enabled tactile internet (TI) services. The foremost challenge tackled by the ICN-based system is to minimize the stretch while selecting an optimal routing path. Therefore, in this work, a reinforcement learning-based intelligent stretch optimization (ISO) strategy has been proposed to reduce stretch and obtain an optimal routing path in ICN-based systems for the realization of 5G-enabled TI services. A Q-learning algorithm is utilized to explore and exploit the different routing paths within the ICN infrastructure. The problem is designed as a Markov decision process and solved with the help of the Q-learning algorithm. The simulation results indicate that the proposed strategy finds the optimal routing path for the delay-sensitive haptic-driven services of 5G-enabled TI based upon their stretch profile over ICN, such as the augmented reality /virtual reality applications. Moreover, we compare and evaluate the simulation results of propsoed ISO strategy with random routing strategy and history aware routing protocol (HARP). The proposed ISO strategy reduces 33.33% and 33.69% delay as compared to random routing and HARP, respectively. Thus, the proposed strategy suggests an optimal routing path with lesser stretch to minimize the E2E latency. Full article

(This article belongs to the Special Issue Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021)

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23 pages, 7073 KiB

Open AccessArticle

OPMSS: Optimal Producer Mobility Support Solution for Named Data Networking

by Muktar Hussaini, Muhammad Ali Naeem and Byung-Seo Kim

Appl. Sci. 2021, 11(9), 4064; https://0-doi-org.brum.beds.ac.uk/10.3390/app11094064 - 29 Apr 2021

Cited by 14 | Viewed by 1914

Abstract

Named data networking (NDN) is designed as a clean-slate Internet architecture to replace the current IP Internet architecture. The named data networking was proposed to offer vast advantages, especially with the advent of new content distributions in IoT, 5G and vehicular networking. However, the architecture is still facing challenges for managing content producer mobility. Despite the efforts of many researchers that curtailed the high handoff latency and signaling overhead, there are still some prominent challenges, such as non-optimal routing path, long delay for data delivery and unnecessary interest packet losses. This paper proposed a solution to minimize unnecessary interest packet losses, delay and provide data path optimization when the mobile producer relocates by using mobility update, broadcasting and best route strategies. The proposed solution is implemented, evaluated and benchmarked with an existing Kite solution. The performance analysis result revealed that our proposed Optimal Producer Mobility Support Solution (OPMSS) minimizes the number of unnecessary interest packets lost on average by 30%, and an average delay of 25% to 30%, with almost equal and acceptable signaling overhead costs. Furthermore, it provides a better data packet delivery route than the Kite solution. Full article

(This article belongs to the Special Issue Emerging Technologies for Next Generation Applied Science System including Selected Papers from ICGHIT 2021)

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