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Network Management for Sustainable Internet of Things

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Management".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 19180

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Special Issue Editors

Dr. Ikram Ud Din

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Guest Editor

Department of Information Technology, The University of Haripur, Haripur 22620, Pakistan
Interests: circular economy; digital and sustainable transition; industrial policy; innovation governance

Dr. Hasan Ali Khattak

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Guest Editor

NUST School of Electrical Engineering and Computer Science (SEECS), Islamabad H-12, Pakistan
Interests: distributed systems; Internet of Things; vehicular ad hoc networks; data and social engineering for smart cities
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Ahmad Almogren

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Guest Editor

Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia
Interests: mobile and pervasive computing; computer security; sensor and cognitive networks; data consistency

Special Issue Information

Dear Colleagues,

Advancements in information communication and technologies have facilitated various cutting-edge applications. Various applications have emerged, including those in healthcare, industry, transportation, smart grids, and smart cities. However, efforts need to be made in providing sustainable ecosystems for these Internet of Things-enabled cyber–physical systems (CPS). Such developments can occur with improved coordination between computational and physical elements via efficient network management.

Modern technology can be used as a solution paradigm, supporting open-knowledge-based architectures that use automated reasoning to manage information and make decisions. The purpose of this Special Issue is to bring together the most recent and advanced research on subjects including the sustainable Internet of Things, opportunistic computing, and semantic-enabled systems, where devices, agents, and humans interact—all with a focus on settings utilizing a sustainable Internet of Things. Future Internet architectures, software-defined networks, and edge-computing-based technologies for smart manufacturing, supply chain management, collaboration, and co-design are also welcome, as are innovative applications and case studies. Despite so many applications and solutions, there remain many challenges at various levels which need to be addressed.

Topics of interest may include, but are not restricted to, the following:

Protocols and services for sustainable Internet of Things;
Task offloading in sustainable Internet of Things;
Machine learning in resource-constrained systems;
Internet of Things architectures for sustainable societies;
Decision support systems for sustainable Internet of Things, using knowledge-based approaches;
Integration of machine learning technologies in the sustainable Internet of Things;
Network management in cyber–physical systems;
Context-aware security and privacy of sustainable Internet of Things;
Intelligent and adaptive object interaction for sustainable Internet of Things;
Applications for sustainable Internet of Things;
Efficient sustainable Internet of Things through software-defined networks;
Predictive maintenance techniques for sustainable Internet of Things;
Big data architectures and solutions for sustainable Internet of Things;
Future Internet applications for sustainable Internet of Things;
Integrating personal devices (smartphones, tablets, wearables) into the sustainable Internet of Things;
Network management in resource-constrained and heterogeneous systems;
Interoperability between protocols and systems ensuring high autonomy;
Discovering, storing, processing, and managing information in sustainable Internet of Things;
Context-aware analysis of events and data to be translated to actionable events;
High-level frameworks and applications sustainable Internet of Things.

Dr. Ikram Ud Din
Dr. Hasan Ali Khattak
Prof. Dr. Ahmad Almogren
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. Sustainability 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.

Published Papers (9 papers)

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Research

13 pages, 700 KiB

Open AccessArticle

A Cooperative Transmission Scheme in Radio Frequency Energy-Harvesting WBANs

by Juncheng Hu, Gaochao Xu, Liang Hu and Shujing Li

Sustainability 2023, 15(10), 8367; https://doi.org/10.3390/su15108367 - 22 May 2023

Cited by 2 | Viewed by 2063

Abstract

Wireless Body Area Network (WBAN) plays an important role in e-health, sports training, and entertainment to monitor human bodies wirelessly and remotely. One critical challenge for WBAN is to guarantee the quality of user experience and improve the network performance within such a resource-constrained and dynamic network. In the proposed paper, we investigate a cooperative radio frequency energy harvesting-based WBAN. Herein, we primarily focus on improving the energy efficiency and network performance through intelligent cooperation among nodes, allowing sensors with sufficient energy to assist other sensors in data uploading. We propose a relay selection method that considers both energy demand and energy harvest efficiency. Each sensor calculates the transmission power threshold required for data uploading based on the perceived channel state and determines whether it can act as a potential relay node in conjunction with its own energy harvest efficiency. The coordinator is responsible for optimizing collaborative transmission plans based on real-time network status. Experimental results show that the cooperative scheme performs better than the common single-hop scheme in terms of packet reception rate and packet arrival rate. In a network consisting of 10 sensors, the increase in packet reception rate ranges from 4.9% to 7.8% when the sensors are placed in preset fixed positions. When the sensors are randomly placed, the increase in packet reception rate ranges from 0.9% to 7.9% and from 0.7% to 7.4%, corresponding to

δ

values of 0.7 and 0.9, respectively. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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15 pages, 1274 KiB

Open AccessArticle

Visualization of Remote Patient Monitoring System Based on Internet of Medical Things

by Mudassar Ali Khan, Ikram Ud Din, Byung-Seo Kim and Ahmad Almogren

Sustainability 2023, 15(10), 8120; https://doi.org/10.3390/su15108120 - 16 May 2023

Cited by 8 | Viewed by 2838

Abstract

Remote patient monitoring (RPM) has become a crucial tool for healthcare professionals in the monitoring and management of patients, particularly for patients with chronic illnesses. RPM has undergone improvements in its capability to deliver real-time data and information to healthcare practitioners as the Internet of Medical Things (IoMT) devices have become more widely available. However, managing and analyzing such a large volume of data still remains a difficult task. The visualization method suggested in this article enables healthcare professionals to examine data gathered by IoMT devices in real-time. Healthcare professionals may monitor patient health status and identify any data irregularities thanks to the system’s dashboard. To assess the system’s usability and user satisfaction, we employed both the Post-Study System Usability Questionnaire (PSSUQ) and the System Usability Scale (SUS). The outcomes of the PSSUQ and SUS assessments revealed that the suggested visualization system scored higher than the control group, demonstrating the system’s usability, accuracy, and dependability as well as its user-friendliness and intuitive interface. The visualization system can boost the effectiveness and efficiency of remote patient monitoring, resulting in better patient care and lower healthcare costs. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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15 pages, 60103 KiB

Open AccessArticle

Machine Learning Based Healthcare Service Dissemination Using Social Internet of Things and Cloud Architecture in Smart Cities

by Vishnu Kumar Kaliappan, Sundharamurthy Gnanamurthy, Abid Yahya, Ravi Samikannu, Muhammad Babar, Basit Qureshi and Anis Koubaa

Sustainability 2023, 15(6), 5457; https://doi.org/10.3390/su15065457 - 20 Mar 2023

Cited by 3 | Viewed by 1460

Abstract

Smart healthcare using the cloud and the Internet of Things (IoT) allows for remote patient monitoring, real-time data collection, improved data security, and cost-effective storage and analysis of healthcare data. This paper proposes an information-centric dissemination scheme (ICDS) for smart healthcare services in smart cities. The proposed scheme addresses the time sensitiveness of healthcare data and aims to ensure consistent dissemination. The ICDS uses decision-tree learning to classify requests based on time-sensitive features, allowing prioritization of access. The scheme also involves segregating sensitive information and distributing digital health data within the classified time to retain time sensitiveness and prioritize access. The learning is then modified for the leaves based on data significance and minimum resources to reduce waiting times and improve availability. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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22 pages, 4935 KiB

Open AccessArticle

Multi Perspectives Steganography Algorithm for Color Images on Multiple-Formats

by Shahid Rahman, Jamal Uddin, Hameed Hussain, Salman Jan, Inayat Khan, Muhammad Shabir and Shahrulniza Musa

Sustainability 2023, 15(5), 4252; https://doi.org/10.3390/su15054252 - 27 Feb 2023

Viewed by 1903

Abstract

The Internet and Big Data expansion have motivated the requirement for more generous stockpiling to hold and share information. Against the current era of information, guaranteeing protection and security to individuals sending data to each other is of utmost importance. The only file type that is instantly and widely used is the image. Therefore, to secure transmission, it is necessary to develop a mechanism to safeguard user data transmission. Considering this thought, it is necessary to analyze the best file type of image for essential criteria of image steganography, such as Payload, Robustness, Imperceptibility, etc., to challenge the weakness of the current algorithms. The widely used image formats are PNG, TIFF, JPEG, BMP, and GIF, which is the cause of existing methods. However, in this case, the critical softness is the credibility of the steganography, which plays a vital role in these format images to ensure the end users communicate. In this paper, a single algorithm provides several advantages for various types of images used as cover objects. However, after the critical and comparative analysis of different perspectives and some assessment metrics, the experimental results prove the importance, significance, and promising limits for these image formats by accomplishing a 4.4450% normal higher score for PSNR correlation than the next best existing methodology. Besides, in PSNR with a variable measure of code implanted in similar pictures of similar aspects, the proposed approach accomplished a 6.33% better score. Encrypting similar code sizes in pictures of various dimensions brought about a 4.23% better score. Embedding the same message size into the same dimension of different images resulted in a 3.222% better score. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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24 pages, 2172 KiB

Open AccessArticle

A Blockchain-Assisted Trusted Clustering Mechanism for IoT-Enabled Smart Transportation System

by Kamran Ahmad Awan, Ikram Ud Din and Ahmad Almogren

Sustainability 2022, 14(22), 14889; https://doi.org/10.3390/su142214889 - 11 Nov 2022

Cited by 10 | Viewed by 1493

Abstract

Vehicular Ad-hoc Network (VANET) is a modern concept of transportation that was formulated by extending Mobile Ad-hoc Networks (MANETs). VANET presents diverse opportunities to modernize transportation to enhance safety, security, and privacy. Direct communication raises various limitations, most importantly, the overhead ratio. The most prominent solution proposed is to divide these nodes into clusters. In this paper, we propose a clustering mechanism that provides security and maintains quality after the cluster formulation based on the pre-defined Quality-of-Service (QoS) parameters. To address potential attacks in the VANET environment, the proposed mechanism uses blockchain to encrypt the trust parameters’ computation. A particular trust degree of a vehicle is evaluated by the base station, encrypted with the blockchain approach, and transmitted toward roadside units (RSUs) for further utilization. The system’s performance is evaluated and compared with the existing approaches. The results show a significant improvement in terms of security and clustering quality. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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18 pages, 4688 KiB

Open AccessArticle

IIoT: Traffic Data Flow Analysis and Modeling Experiment for Smart IoT Devices

by Akashdeep Bhardwaj, Keshav Kaushik, Salil Bharany, Ateeq Ur Rehman, Yu-Chen Hu, Elsayed Tag Eldin and Nivin A. Ghamry

Sustainability 2022, 14(21), 14645; https://doi.org/10.3390/su142114645 - 07 Nov 2022

Cited by 6 | Viewed by 2529

Abstract

The Internet of Things (IoT) has redefined several aspects of our daily lives, including automation and control of the living environment, innovative healthcare services, and much more. Digital IoT devices and sensors, when integrated with home appliances, industrial systems, and online services in the physical world, have brought intense, disruptive changes in our lives. The industry and home users have widely embraced these ‘things’ on the Internet or IoT. However, the innate, intrinsic repercussions regarding security and data privacy are not evaluated. Security applies to Industrial IoT (IIoT) is in its infancy stage. Techniques from security and privacy research promise to address broad security goals, but attacks continue to emerge in industrial devices. This research explores the vulnerabilities of IIoT ecosystems not just as individual nodes but as the integrated infrastructure of digital and physical systems interacting with the domains. The authors propose a unique threat model framework to analyze the attacks on IIoT application environments. The authors identified sensitive data flows inside the IIoT devices to determine privacy risks at the application level and explored the device exchanges at the physical level. Both these risks lead to insecure ecosystems. The authors also performed a security analysis of physical domains to digital domains. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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24 pages, 4077 KiB

Open AccessArticle

A Hybrid Multi-Cloud Framework Using the IBBE Key Management System for Securing Data Storage

by Manreet Sohal, Salil Bharany, Sandeep Sharma, Mashael S. Maashi and Mohammed Aljebreen

Sustainability 2022, 14(20), 13561; https://doi.org/10.3390/su142013561 - 20 Oct 2022

Cited by 3 | Viewed by 1488

Abstract

Information storage and access in multi-cloud environments have become quite prevalent. In this paper, a multi-cloud framework is presented that secures users’ data. The primary goal of this framework is to secure users’ data from untrusted Cloud Service Providers (CSPs). They can collude with other malicious users and can hand over users’ data to these malicious users for their beneficial interests. In order to achieve this goal, the data are split into parts, and then each part is encrypted and uploaded to a different cloud. Therefore, client-side cryptography is used in this framework. For encrypting users’ data, the BDNA encryption technique is used. This framework presents a hybrid cryptographic approach that uses Identity-based Broadcast Encryption (IBBE) for managing the keys of the symmetric key algorithm (BDNA) by encrypting them with the particular version of IBBE. The work presented in this research paper is the first practical implementation of IBBE for securing encryption keys. Earlier, IBBE was only used for securely broadcasting data across many users over a network. The security of this hybrid scheme was proved through Indistinguishable Chosen-Ciphertext Attacks. This double encryption process makes the framework secure against all insiders and malicious users’ attacks. The proposed framework was implemented as a web application, and real-time storage clouds were used for storing the data. The workflow of the proposed framework is presented through screenshots of different working modules. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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20 pages, 4579 KiB

Open AccessArticle

Optimization of Load Balancing and Task Scheduling in Cloud Computing Environments Using Artificial Neural Networks-Based Binary Particle Swarm Optimization (BPSO)

by Mohammed I. Alghamdi

Sustainability 2022, 14(19), 11982; https://doi.org/10.3390/su141911982 - 22 Sep 2022

Cited by 17 | Viewed by 2735

Abstract

As more people utilize the cloud, more employment opportunities become available. With constraints such as a limited make-span, a high utilization rate of available resources, minimal execution costs, and a rapid turnaround time for scheduling, this becomes an NP-hard optimization issue. The number of solutions/combinations increases exponentially with the magnitude of the challenge, such as the number of tasks and the number of computing resources, making the task scheduling problem NP-hard. As a result, achieving the optimum scheduling of user tasks is difficult. An intelligent resource allocation system can significantly cut down the costs and waste of resources. For instance, binary particle swarm optimization (BPSO) was created to combat ineffective heuristic approaches. However, the optimal solution will not be produced if these algorithms are not paired with additional heuristic or meta-heuristic algorithms. Due to the high temporal complexity of these algorithms, they are less useful in real-world settings. For the NP problem, the binary variation of PSO is presented for workload scheduling and balancing in cloud computing. Considering the updating and optimization constraints stated in this research, our objective function determines if heterogeneous virtual machines (VMs) Phave the most significant difference in completion time. In conjunction with load balancing, we developed a method for updating the placements of particles. According to the experiment results, the proposed method surpasses existing metaheuristic and heuristic algorithms regarding work scheduling and load balancing. This level of success has been attainable because of the application of Artificial Neural Networks (ANN). ANN has demonstrated promising outcomes in resource distribution. ANN is more accurate and faster than multilayer perceptron networks at predicting targets. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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13 pages, 1795 KiB

Open AccessArticle

Energy-Efficient Mobile Agent Protocol for Secure IoT Sustainable Applications

by Mohamed Elhoseny, Mohammad Siraj, Khalid Haseeb, Muhammad Nawaz, Majid Altamimi and Mohammed I. Alghamdi

Sustainability 2022, 14(14), 8960; https://doi.org/10.3390/su14148960 - 21 Jul 2022

Cited by 3 | Viewed by 1444

Abstract

The Internet of Things (IoT) and sensor technologies are combined with various communication networks in smart appliances and perform a significant role. Connected devices sense, analyze, and send environmental data, as well as support applications’ connections. Mobile agents can be explored to provide sensing intelligence with IoT-based systems. Many strategies have been proposed to address the issue of energy efficiency while maintaining the sensor load at a low cost. However, advancements are still desired. Furthermore, without fully trustworthy relationships, sensitive data are at risk, and the solution must provide privacy protection against unexpected events. With the development of two algorithms, this study proposes a mobile agent-based efficient energy resource management solution and also protects IoT appliances. Firstly, the software agents perform a decision using past and present precepts, and by exploring rule-based conditions, it offers an energy-efficient recommended system. Second, data from IoT appliances are securely evaluated on edge interfaces before being transferred to end-centers for verification. Simulations-based tests are conducted and verified the significance of the proposed protocol against other studies in terms of network metrics. Full article

(This article belongs to the Special Issue Network Management for Sustainable Internet of Things)

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