Journal Description
Journal of Sensor and Actuator Networks
Journal of Sensor and Actuator Networks
is an international, peer-reviewed, open access journal on the science and technology of sensor and actuator networks, published bimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), dblp, Inspec, and other databases.
- Journal Rank: CiteScore - Q1 (Control and Optimization)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.4 days after submission; acceptance to publication is undertaken in 5.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.5 (2022);
5-Year Impact Factor:
3.6 (2022)
Latest Articles
An Optimized Link State Routing Protocol with a Blockchain Framework for Efficient Video-Packet Transmission and Security over Mobile Ad-Hoc Networks
J. Sens. Actuator Netw. 2024, 13(2), 22; https://doi.org/10.3390/jsan13020022 - 11 Mar 2024
Abstract
A mobile ad-hoc network (MANET) necessitates appropriate routing techniques to enable optimal data transfer. The selection of appropriate routing protocols while utilizing the default settings is required to solve the existing problems. To enable effective video streaming in MANETs, this study proposes a
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A mobile ad-hoc network (MANET) necessitates appropriate routing techniques to enable optimal data transfer. The selection of appropriate routing protocols while utilizing the default settings is required to solve the existing problems. To enable effective video streaming in MANETs, this study proposes a novel optimized link state routing (OLSR) protocol that incorporates a deep-learning model. Initially, the input videos are collected from the Kaggle dataset. Then, the black-hole node is detected using a novel twin-attention-based dense convolutional bidirectional gated network (SA_ DCBiGNet) model. Next, the neighboring nodes are analyzed using trust values, and routing is performed using the extended osprey-aided optimized link state routing protocol (EO_OLSRP) technique. Similarly, the extended osprey optimization algorithm (EOOA) selects the optimal feature based on parameters such as node stability and link stability. Finally, blockchain storage is included to improve the security of MANET data using interplanetary file system (IPFS) technology. Additionally, the proposed blockchain system is validated utilizing a consensus technique based on delegated proof-of-stake (DPoS). The proposed method utilizes Python and it is evaluated using data acquired from various mobile simulator models accompanied by the NS3 simulator. The proposed model performs better with a packet-delivery ratio (PDR) of 91.6%, average end delay (AED) of 23.6 s, and throughput of 2110 bytes when compared with the existing methods which have a PDR of 89.1%, AED of 22 s, and throughput of 1780 bytes, respectively.
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(This article belongs to the Section Network Security and Privacy)
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Open AccessArticle
Veritas: Layer-2 Scaling Solution for Decentralized Oracles on Ethereum Blockchain with Reputation and Real-Time Considerations
by
Moustafa Mowaffak Saad, Dalia Sobhy and Amani A. Saad
J. Sens. Actuator Netw. 2024, 13(2), 21; https://doi.org/10.3390/jsan13020021 - 07 Mar 2024
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Blockchainsand smart contracts are pivotal in transforming interactions between systems and individuals, offering secure, immutable, and transparent trust-building mechanisms without central oversight. However, Smart Contracts face limitations due to their reliance on blockchain-contained data, a gap addressed by ’Oracles’. These bridges to external
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Blockchainsand smart contracts are pivotal in transforming interactions between systems and individuals, offering secure, immutable, and transparent trust-building mechanisms without central oversight. However, Smart Contracts face limitations due to their reliance on blockchain-contained data, a gap addressed by ’Oracles’. These bridges to external data sources introduce the ’Oracle problem’, where maintaining blockchain-like security and transparency becomes vital to prevent data integrity issues. This paper presents Veritas, a novel decentralized oracle system leveraging a layer-2 scaling solution, enhancing smart contracts’ efficiency and security on Ethereum blockchains. The proposed architecture, explored through simulation and experimental analyses, significantly reduces operational costs while maintaining robust security protocols. An innovative node selection process is also introduced to minimize the risk of malicious data entry, thereby reinforcing network security. Veritas offers a solution to the Oracle problem by aligning with blockchain principles of security and transparency, and demonstrates advancements in reducing operational costs and bolstering network integrity. While the study provides a promising direction, it also highlights potential areas for further exploration in blockchain technology and oracle system optimization.
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Open AccessReview
Interconnected Smart Transactive Microgrids—A Survey on Trading, Energy Management Systems, and Optimisation Approaches
by
Ipeleng L. Machele, Adeiza J. Onumanyi, Adnan M. Abu-Mahfouz and Anish M. Kurien
J. Sens. Actuator Netw. 2024, 13(2), 20; https://doi.org/10.3390/jsan13020020 - 01 Mar 2024
Abstract
The deployment of isolated microgrids has witnessed exponential growth globally, especially in the light of prevailing challenges faced by many larger power grids. However, these isolated microgrids remain separate entities, thus limiting their potential to significantly impact and improve the stability, efficiency, and
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The deployment of isolated microgrids has witnessed exponential growth globally, especially in the light of prevailing challenges faced by many larger power grids. However, these isolated microgrids remain separate entities, thus limiting their potential to significantly impact and improve the stability, efficiency, and reliability of the broader electrical power system. Thus, to address this gap, the concept of interconnected smart transactive microgrids (ISTMGs) has arisen, facilitating the interconnection of these isolated microgrids, each with its unique attributes aimed at enhancing the performance of the broader power grid system. Furthermore, ISTMGs are expected to create more robust and resilient energy networks that enable innovative and efficient mechanisms for energy trading and sharing between individual microgrids and the centralized power grid. This paradigm shift has sparked a surge in research aimed at developing effective ISTMG networks and mechanisms. Thus, in this paper, we present a review of the current state-of-the-art in ISTMGs with a focus on energy trading, energy management systems (EMS), and optimization techniques for effective energy management in ISTMGs. We discuss various types of trading, architectures, platforms, and stakeholders involved in ISTMGs. We proceed to elucidate the suitable applications of EMS within such ISTMG frameworks, emphasizing its utility in various domains. This includes an examination of optimization tools and methodologies for deploying EMS in ISTMGs. Subsequently, we conduct an analysis of current techniques and their constraints, and delineate prospects for future research to advance the establishment and utilization of ISTMGs.
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(This article belongs to the Section Network Services and Applications)
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Open AccessArticle
Low-Cost Internet of Things Solution for Building Information Modeling Level 3B—Monitoring, Analysis and Management
by
Andrzej Szymon Borkowski
J. Sens. Actuator Netw. 2024, 13(2), 19; https://doi.org/10.3390/jsan13020019 - 29 Feb 2024
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The integration of the Internet of Things (IoT) and Building Information Modeling (BIM) is progressing. The use of microcontrollers and sensors in buildings is described as a level 3B maturity in the use of BIM. Design companies, contractors and building operators can use
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The integration of the Internet of Things (IoT) and Building Information Modeling (BIM) is progressing. The use of microcontrollers and sensors in buildings is described as a level 3B maturity in the use of BIM. Design companies, contractors and building operators can use IoT solutions to monitor, analyze or manage processes. As a rule, solutions based on original Arduino boards are quite an expensive investment. The aim of this research was to find a low-cost IoT solution for monitoring, analysis and management, and integrate it with a BIM model. In the present study, an inexpensive NodeMCU microcontroller and a temperature and pressure sensor were used to study the thermal comfort of users in a single-family home. During the summer season, analysis of the monitored temperature can contribute to installation (HVAC) or retrofit work (for energy efficiency). The article presents a low-cost solution for studying the thermal comfort of users using a digital twin built-in BIM. Data obtained from sensors can support both the design and management processes. The main contribution of the article enables the design, construction and use of low-cost circuits (15.57 USD) even in small developments (single-family houses, semi-detached houses, terraced houses, atrium buildings). Combining IoT sensor telemetry with BIM (maturity level 3C) is a challenge that organizations will face in the near future.
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Open AccessFeature PaperArticle
UAV-Assisted Cooperative NOMA and OFDM Communication Systems: Analysis and Optimization
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Thuc Kieu-Xuan and Anh Le-Thi
J. Sens. Actuator Netw. 2024, 13(1), 18; https://doi.org/10.3390/jsan13010018 - 19 Feb 2024
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Utilizing unmanned aerial vehicles (UAVs) to facilitate wireless communication has emerged as a viable and promising strategy to enhance current and prospective wireless systems. This approach offers many advantages by establishing line-of-sight connections, optimizing operational efficiency, and enabling flexible deployment capabilities in various
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Utilizing unmanned aerial vehicles (UAVs) to facilitate wireless communication has emerged as a viable and promising strategy to enhance current and prospective wireless systems. This approach offers many advantages by establishing line-of-sight connections, optimizing operational efficiency, and enabling flexible deployment capabilities in various terrains. Thus, in this paper, we investigate UAV communication in a relaying network in which a UAV helps communication between a source and two destination users while flying to a location. To have a complete view of our proposed system, we consider both orthogonal multiple access, such as OFDMs and non-orthogonal multiple access (NOMA) scenarios. Moreover, we apply successive convex optimization (SCO) and the block-coordinate gradient descent (BCGD) for the sum-rate optimization problems to improve the system performance under constraints of total bandwidth and total power at the ground base station and UAV. The experimental results validate that the achievable secrecy rates are notably enhanced using our proposed algorithms and show optimal trends for critical parameters, such as transmit powers, the flight trajectory and speed of the UAV, and resource allocation of OFDM and NOMA.
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Open AccessArticle
Build–Launch–Consolidate Framework and Toolkit for Impact Analysis on Wireless Sensor Networks
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Rakan Alghofaili, Hussah Albinali and Farag Azzedin
J. Sens. Actuator Netw. 2024, 13(1), 17; https://doi.org/10.3390/jsan13010017 - 18 Feb 2024
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The Internet of Things (IoT) and wireless sensor networks (WSNs) utilize their connectivity to enable solutions supporting a spectrum of industries in different and volatile environments. To effectively enhance the security and quality of the service of networks, empirical research should consider a
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The Internet of Things (IoT) and wireless sensor networks (WSNs) utilize their connectivity to enable solutions supporting a spectrum of industries in different and volatile environments. To effectively enhance the security and quality of the service of networks, empirical research should consider a variety of factors and be reproducible. This will not only ensure scalability but also enable the verification of conclusions, leading to more reliable solutions. Cooja offers limited performance analysis capabilities of simulations, which are often extracted and calculated manually. In this paper, we introduce the Build–Launch–Consolidate (BLC) framework and a toolkit that enable researchers to conduct structured and conclusive experiments considering different factors and metrics, experiment design, and results analysis. Furthermore, the toolkit analyzes diverse network metrics across various scenarios. As a proof of concept, this paper studies the flooding attacks on the IoT and illustrates their impact on the network, utilizing the BLC framework and toolkit.
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Open AccessReview
Reliability of LoRaWAN Communications in Mining Environments: A Survey on Challenges and Design Requirements
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Sonile K. Musonda, Musa Ndiaye, Hastings M. Libati and Adnan M. Abu-Mahfouz
J. Sens. Actuator Netw. 2024, 13(1), 16; https://doi.org/10.3390/jsan13010016 - 09 Feb 2024
Abstract
While a robust and reliable communication network for monitoring the mining environment in a timely manner to take care of people, the planet Earth and profits is key, the mining environment is very challenging in terms of achieving reliable wireless transmission. This survey
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While a robust and reliable communication network for monitoring the mining environment in a timely manner to take care of people, the planet Earth and profits is key, the mining environment is very challenging in terms of achieving reliable wireless transmission. This survey therefore investigates the reliability of LoRaWAN communication in the mining environment, identifying the challenges and design requirements. Bearing in mind that LoRaWAN is an IoT communication technology that has not yet been fully deployed in mining, the survey incorporates an investigation of LoRaWAN and other mining IoT communication technologies to determine their records of reliability, strengths and weaknesses and applications in mining. This aspect of the survey gives insight into the requirements of future mining IoT communication technologies and where LoRaWAN can be deployed in both underground and surface mining. Specific questions that the survey addresses are: (1) What is the record of reliability of LoRaWAN in mining environments? (2) What contributions have been made with regard to LoRa/LoRaWAN communication in general towards improving reliability? (3) What are the challenges and design requirements of LoRaWAN reliability in mining environments? (4) What research opportunities exist for achieving LoRaWAN communication in mining environments? In addition to recommending open research opportunities, the lessons learnt from the survey are also outlined.
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(This article belongs to the Topic Electronic Communications, IOT and Big Data)
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Open AccessArticle
IFGAN—A Novel Image Fusion Model to Fuse 3D Point Cloud Sensory Data
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Henry Alexander Ignatious, Hesham El-Sayed and Salah Bouktif
J. Sens. Actuator Netw. 2024, 13(1), 15; https://doi.org/10.3390/jsan13010015 - 07 Feb 2024
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To enhance the level of autonomy in driving, it is crucial to ensure optimal execution of critical maneuvers in all situations. However, numerous accidents involving autonomous vehicles (AVs) developed by major automobile manufacturers in recent years have been attributed to poor decision making
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To enhance the level of autonomy in driving, it is crucial to ensure optimal execution of critical maneuvers in all situations. However, numerous accidents involving autonomous vehicles (AVs) developed by major automobile manufacturers in recent years have been attributed to poor decision making caused by insufficient perception of environmental information. AVs employ diverse sensors in today’s technology-driven settings to gather this information. However, due to technical and natural factors, the data collected by these sensors may be incomplete or ambiguous, leading to misinterpretation by AVs and resulting in fatal accidents. Furthermore, environmental information obtained from multiple sources in the vehicular environment often exhibits multimodal characteristics. To address this limitation, effective preprocessing of raw sensory data becomes essential, involving two crucial tasks: data cleaning and data fusion. In this context, we propose a comprehensive data fusion engine that categorizes various sensory data formats and appropriately merges them to enhance accuracy. Specifically, we suggest a general framework to combine audio, visual, and textual data, building upon our previous research on an innovative hybrid image fusion model that fused multispectral image data. However, this previous model faced challenges when fusing 3D point cloud data and handling large volumes of sensory data. To overcome these challenges, our study introduces a novel image fusion model called Image Fusion Generative Adversarial Network (IFGAN), which incorporates a multi-scale attention mechanism into both the generator and discriminator of a Generative Adversarial Network (GAN). The primary objective of image fusion is to merge complementary data from various perspectives of the same scene to enhance the clarity and detail of the final image. The multi-scale attention mechanism serves two purposes: the first, capturing comprehensive spatial information to enable the generator to focus on foreground and background target information in the sensory data, and the second, constraining the discriminator to concentrate on attention regions rather than the entire input image. Furthermore, the proposed model integrates the color information retention concept from the previously proposed image fusion model. Furthermore, we propose simple and efficient models for extracting salient image features. We evaluate the proposed models using various standard metrics and compare them with existing popular models. The results demonstrate that our proposed image fusion model outperforms the other models in terms of performance.
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Open AccessArticle
Network Sliced Distributed Learning-as-a-Service for Internet of Vehicles Applications in 6G Non-Terrestrial Network Scenarios
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David Naseh, Swapnil Sadashiv Shinde and Daniele Tarchi
J. Sens. Actuator Netw. 2024, 13(1), 14; https://doi.org/10.3390/jsan13010014 - 07 Feb 2024
Abstract
In the rapidly evolving landscape of next-generation 6G systems, the integration of AI functions to orchestrate network resources and meet stringent user requirements is a key focus. Distributed Learning (DL), a promising set of techniques that shape the future of 6G communication systems,
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In the rapidly evolving landscape of next-generation 6G systems, the integration of AI functions to orchestrate network resources and meet stringent user requirements is a key focus. Distributed Learning (DL), a promising set of techniques that shape the future of 6G communication systems, plays a pivotal role. Vehicular applications, representing various services, are likely to benefit significantly from the advances of 6G technologies, enabling dynamic management infused with inherent intelligence. However, the deployment of various DL methods in traditional vehicular settings with specific demands and resource constraints poses challenges. The emergence of distributed computing and communication resources, such as the edge-cloud continuum and integrated terrestrial and non-terrestrial networks (T/NTN), provides a solution. Efficiently harnessing these resources and simultaneously implementing diverse DL methods becomes crucial, and Network Slicing (NS) emerges as a valuable tool. This study delves into the analysis of DL methods suitable for vehicular environments alongside NS. Subsequently, we present a framework to facilitate DL-as-a-Service (DLaaS) on a distributed networking platform, empowering the proactive deployment of DL algorithms. This approach allows for the effective management of heterogeneous services with varying requirements. The proposed framework is exemplified through a detailed case study in a vehicular integrated T/NTN with diverse service demands from specific regions. Performance analysis highlights the advantages of the DLaaS approach, focusing on flexibility, performance enhancement, added intelligence, and increased user satisfaction in the considered T/NTN vehicular scenario.
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(This article belongs to the Special Issue Advancing towards 6G Networks)
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Open AccessArticle
A Secure Blockchain-Enabled Remote Healthcare Monitoring System for Home Isolation
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Jongsuk Kongsen, Doungsuda Chantaradsuwan, Peeravit Koad, May Thu and Chanankorn Jandaeng
J. Sens. Actuator Netw. 2024, 13(1), 13; https://doi.org/10.3390/jsan13010013 - 05 Feb 2024
Abstract
This article presents a secure framework for remote healthcare monitoring in the context of home isolation, thereby addressing the concerns related to untrustworthy client connections to a hospital information system (HIS) within a secure network. Our proposed solution leverages a public blockchain network
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This article presents a secure framework for remote healthcare monitoring in the context of home isolation, thereby addressing the concerns related to untrustworthy client connections to a hospital information system (HIS) within a secure network. Our proposed solution leverages a public blockchain network as a secure distributed database to buffer and transmit patient vital signs. The framework integrates an algorithm for the secure gathering and transmission of vital signs to the Ethereum network. Additionally, we introduce a publish/subscribe paradigm, thus enhancing security using the TLS channel to connect to the blockchain network. An analysis of the maintenance cost of the distributed database underscores the cost-effectiveness of our approach. In conclusion, our framework provides a highly secure and economical solution for remote healthcare monitoring in home isolation scenarios.
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(This article belongs to the Section Actuators, Sensors and Devices)
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Open AccessArticle
Fast Multi-User Searchable Encryption with Forward and Backward Private Access Control
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Salim Sabah Bulbul, Zaid Ameen Abduljabbar, Duaa Fadhel Najem, Vincent Omollo Nyangaresi, Junchao Ma and Abdulla J. Y. Aldarwish
J. Sens. Actuator Netw. 2024, 13(1), 12; https://doi.org/10.3390/jsan13010012 - 02 Feb 2024
Abstract
Untrusted servers are servers or storage entities lacking complete trust from the data owner or users. This characterization implies that the server hosting encrypted data may not enjoy full trust from data owners or users, stemming from apprehensions related to potential security breaches,
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Untrusted servers are servers or storage entities lacking complete trust from the data owner or users. This characterization implies that the server hosting encrypted data may not enjoy full trust from data owners or users, stemming from apprehensions related to potential security breaches, unauthorized access, or other security risks. The security of searchable encryption has been put into question by several recent attacks. Currently, users can search for encrypted documents on untrusted cloud servers using searchable symmetric encryption (SSE). This study delves deeply into two pivotal concepts of privacy within dynamic searchable symmetric encryption (DSSE) schemes: forward privacy and backward privacy. The former serves as a safeguard against the linkage of recently added documents to previously conducted search queries, whereas the latter guarantees the irretrievability of deleted documents in subsequent search inquiries. However, the provision of fine-grained access control is complex in existing multi-user SSE schemes. SSE schemes may also incur high computation costs due to the need for fine-grained access control, and it is essential to support document updates and forward privacy. In response to these issues, this paper suggests a searchable encryption scheme that uses simple primitive tools. We present a multi-user SSE scheme that efficiently controls access to dynamically encrypted documents to resolve these issues, using an innovative approach that readily enhances previous findings. Rather than employing asymmetric encryption as in comparable systems, we harness low-complexity primitive encryption tools and inverted index-based DSSE to handle retrieving encrypted files, resulting in a notably faster system. Furthermore, we ensure heightened security by refreshing the encryption key after each search, meaning that users are unable to conduct subsequent searches with the same key and must obtain a fresh key from the data owner. An experimental evaluation shows that our scheme achieves forward and Type II backward privacy and has much faster search performance than other schemes. Our scheme can be considered secure, as proven in a random oracle model.
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(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)
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Open AccessEditorial
Featured Papers on Network Security and Privacy
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Jordi Mongay Batalla
J. Sens. Actuator Netw. 2024, 13(1), 11; https://doi.org/10.3390/jsan13010011 - 01 Feb 2024
Abstract
There is an urgent need to introduce security-by-design in networks [...]
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(This article belongs to the Special Issue Feature Papers in Network Security and Privacy)
Open AccessArticle
Service-Aware Hierarchical Fog–Cloud Resource Mappingfor e-Health with Enhanced-Kernel SVM
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Alaa AlZailaa, Hao Ran Chi, Ayman Radwan and Rui L. Aguiar
J. Sens. Actuator Netw. 2024, 13(1), 10; https://doi.org/10.3390/jsan13010010 - 01 Feb 2024
Abstract
Fog–cloud-based hierarchical task-scheduling methods are embracing significant challenges to support e-Health applications due to the large number of users, high task diversity, and harsher service-level requirements. Addressing the challenges of fog–cloud integration, this paper proposes a new service/network-aware fog–cloud hierarchical resource-mapping scheme, which
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Fog–cloud-based hierarchical task-scheduling methods are embracing significant challenges to support e-Health applications due to the large number of users, high task diversity, and harsher service-level requirements. Addressing the challenges of fog–cloud integration, this paper proposes a new service/network-aware fog–cloud hierarchical resource-mapping scheme, which achieves optimized resource utilization efficiency and minimized latency for service-level critical tasks in e-Health applications. Concretely, we develop a service/network-aware task classification algorithm. We adopt support vector machine as a backbone with fast computational speed to support real-time task scheduling, and we develop a new kernel, fusing convolution, cross-correlation, and auto-correlation, to gain enhanced specificity and sensitivity. Based on task classification, we propose task priority assignment and resource-mapping algorithms, which aim to achieve minimized overall latency for critical tasks and improve resource utilization efficiency. Simulation results showcase that the proposed algorithm is able to achieve average execution times for critical/non-critical tasks of 0.23/0.50 ms in diverse networking setups, which surpass the benchmark scheme by 73.88%/52.01%, respectively.
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(This article belongs to the Topic Machine Learning in Communication Systems and Networks)
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Open AccessArticle
On Maximizing the Probability of Achieving Deadlines in Communication Networks
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Benjamin Becker, Christian Oberli, Tobias Meuser and Ralf Steinmetz
J. Sens. Actuator Netw. 2024, 13(1), 9; https://doi.org/10.3390/jsan13010009 - 18 Jan 2024
Abstract
We consider the problem of meeting deadline constraints in wireless communication networks. Fulfilling deadlines depends heavily on the routing algorithm used. We study this dependence generically for a broad class of routing algorithms. For analyzing the impact of routing decisions on deadline fulfillment,
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We consider the problem of meeting deadline constraints in wireless communication networks. Fulfilling deadlines depends heavily on the routing algorithm used. We study this dependence generically for a broad class of routing algorithms. For analyzing the impact of routing decisions on deadline fulfillment, we adopt a stochastic model from operations research to capture the source-to-destination delay distribution and the corresponding probability of successfully delivering data before a given deadline. Based on this model, we propose a decentralized algorithm that operates locally at each node and exchanges information solely with direct neighbors in order to determine the probabilities of achieving deadlines. A modified version of the algorithm also improves routing tables iteratively to progressively increase the deadline achievement probabilities. This modified algorithm is shown to deliver routing tables that maximize the deadline achievement probabilities for all nodes in a given network. We tested the approach by simulation and compared it with routing strategies based on established metrics, specifically the average delay, minimum hop count, and expected transmission count. Our evaluations encompass different channel quality and small-scale fading conditions, as well as various traffic load scenarios. Notably, our solution consistently outperforms the other approaches in all tested scenarios.
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(This article belongs to the Topic Electronic Communications, IOT and Big Data)
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Open AccessArticle
Varactor-Based Tunable Sensor for Dielectric Measurements of Solid and Liquid Materials
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Waseem Shahzad, Weidong Hu, Qasim Ali, Ali Raza Barket and Gulab Shah
J. Sens. Actuator Netw. 2024, 13(1), 8; https://doi.org/10.3390/jsan13010008 - 18 Jan 2024
Abstract
In this article, a tunable RF sensor is presented for the measurement of dielectric materials (liquids and solids) based on a metamaterial resonator. The proposed novel configuration sensor has a microstrip line-loaded metamaterial resonator with tunable characteristics by utilizing a single varactor diode
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In this article, a tunable RF sensor is presented for the measurement of dielectric materials (liquids and solids) based on a metamaterial resonator. The proposed novel configuration sensor has a microstrip line-loaded metamaterial resonator with tunable characteristics by utilizing a single varactor diode in the series of the resonator. CST Microwave studio is employed for 3D simulations of the tunable sensor, and the desired performance is attained by optimizing various structural parameters to enhance the transmission coefficient ( magnitude) notch depth performance. The proposed RF sensor can be tuned in L and S-bands using the varactor diode biasing voltage range of 0–20 V. To validate the performance of the sensor, the proposed design has been simulated, fabricated, and tested for the dielectric characterization of different solid and liquid materials. Material testing is performed in the bandwidth of 1354 MHz by incorporating a single metamaterial resonator-based sensor. Agilent’s Network Analyzer is used for measuring the S-parameters of the proposed sensor topology under loaded and unloaded conditions. Simulated and measured S-parameter results correspond substantially in the 1.79 to 3.15 GHz frequency band during the testing of the fabricated sensor. This novel tunable resonator design has various applications in modulators, phase shifters, and filters as well as in biosensors for liquid materials.
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(This article belongs to the Section Actuators, Sensors and Devices)
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Open AccessArticle
Game Theory-Based Incentive Design for Mitigating Malicious Behavior in Blockchain Networks
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Souhail Mssassi and Anas Abou El Kalam
J. Sens. Actuator Netw. 2024, 13(1), 7; https://doi.org/10.3390/jsan13010007 - 15 Jan 2024
Abstract
This paper presents an innovative incentive model that utilizes graph and game theories to address the issue of node incentives in decentralized blockchain networks such as EVM blockchains. The lack of incentives for nodes within EVM networks gives rise to potential weaknesses that
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This paper presents an innovative incentive model that utilizes graph and game theories to address the issue of node incentives in decentralized blockchain networks such as EVM blockchains. The lack of incentives for nodes within EVM networks gives rise to potential weaknesses that might be used for various purposes, such as broadcasting fake transactions or withholding blocks. This affects the overall trust and integrity of the network. To address this issue, the current study offers a network model that incorporates the concepts of graph theory and utilizes a matrix representation for reward and trust optimization. Furthermore, this study presents a game-theoretic framework that encourages cooperative conduct and discourages malicious actions, ultimately producing a state of equilibrium according to the Nash equilibrium. The simulations validated the model’s efficacy in addressing fraudulent transactions and emphasized its scalability, security, and fairness benefits. This study makes a valuable contribution to the field of blockchain technology by presenting an incentive model that effectively encourages the development of secure and trusted decentralized systems.
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(This article belongs to the Topic Trends and Prospects in Security, Encryption and Encoding)
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Open AccessArticle
Experiences Using Ethereum and Quorum Blockchain Smart Contracts in Dairy Production
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Filisia Melissari, Andreas Papadakis, Dimitris Chatzitheodorou, Duc Tran, Joachim Schouteten, Georgia Athanasiou and Theodore Zahariadis
J. Sens. Actuator Netw. 2024, 13(1), 6; https://doi.org/10.3390/jsan13010006 - 12 Jan 2024
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feta cheese is a Greek protected designation of origin (PDO) product that is produced in three main phases: milk collection, cheese preparation and maturation, and product packaging. Each phase must be aligned with quantitative rules, stemming from the legislation framework and best practices.
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feta cheese is a Greek protected designation of origin (PDO) product that is produced in three main phases: milk collection, cheese preparation and maturation, and product packaging. Each phase must be aligned with quantitative rules, stemming from the legislation framework and best practices. The production complexity, the increased production cost, centralised and monolithic traceability systems, and the lack of a systematic monitoring framework have made dairy products a commodity with increased frequency of food fraud. Given the context of the dairy section in Greece, this study aims to examine (a) whether it is possible to model the end-to-end process of PDO feta cheese considering production rules to develop a trustworthy blockchain-based traceability system (b) how to associate the (‘easy-to-retrieve’, operational) traceability data with the (difficult-to-assess) product characteristics meaningful to the consumer, (c) how to design a technical solution ensuring that information is accessible by the stakeholders and the consumer, while minimising blockchain-related delay, and (d) how to design a graphical user interface and offer tools to consumers so that traceability information is communicated effectively and they can verify it through access to the blockchain. In terms of methods, we analyse and model the process steps, identify measurable, operational parameters and translate the legislative framework into rules. These rules are designed and codified as blockchain smart contracts that ensure the food authenticity and compliance with legislation. The blockchain infrastructure consists of the private Quorum blockchain that is anchored to the public infrastructure of Ethereum. Mechanisms to address scalability in terms of dynamic data volumes, effective data coding, and data verification at the edge as well as relevant limitations are discussed. Consumers are informed about traceability information by using QR codes on food packaging and can verify the data using the blockchain tools and services.
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Open AccessArticle
Dynamic and Distributed Intelligence over Smart Devices, Internet of Things Edges, and Cloud Computing for Human Activity Recognition Using Wearable Sensors
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Ayman Wazwaz, Khalid Amin, Noura Semary and Tamer Ghanem
J. Sens. Actuator Netw. 2024, 13(1), 5; https://doi.org/10.3390/jsan13010005 - 02 Jan 2024
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A wide range of applications, including sports and healthcare, use human activity recognition (HAR). The Internet of Things (IoT), using cloud systems, offers enormous resources but produces high delays and huge amounts of traffic. This study proposes a distributed intelligence and dynamic HAR
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A wide range of applications, including sports and healthcare, use human activity recognition (HAR). The Internet of Things (IoT), using cloud systems, offers enormous resources but produces high delays and huge amounts of traffic. This study proposes a distributed intelligence and dynamic HAR architecture using smart IoT devices, edge devices, and cloud computing. These systems were used to train models, store results, and process real-time predictions. Wearable sensors and smartphones were deployed on the human body to detect activities from three positions; accelerometer and gyroscope parameters were utilized to recognize activities. A dynamic selection of models was used, depending on the availability of the data and the mobility of the users. The results showed that this system could handle different scenarios dynamically according to the available features; its prediction accuracy was 99.23% using the LightGBM algorithm during the training stage, when 18 features were used. The prediction time was around 6.4 milliseconds per prediction on the smart end device and 1.6 milliseconds on the Raspberry Pi edge, which can serve more than 30 end devices simultaneously and reduce the need for the cloud. The cloud was used for storing users’ profiles and can be used for real-time prediction in 391 milliseconds per request.
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Open AccessArticle
Output Stream from the AQM Queue with BMAP Arrivals
by
Andrzej Chydzinski
J. Sens. Actuator Netw. 2024, 13(1), 4; https://doi.org/10.3390/jsan13010004 - 02 Jan 2024
Abstract
We analyse the output stream from a packet buffer governed by the policy that incoming packets are dropped with a probability related to the buffer occupancy. The results include formulas for the number of packets departing the buffer in a specific time, for
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We analyse the output stream from a packet buffer governed by the policy that incoming packets are dropped with a probability related to the buffer occupancy. The results include formulas for the number of packets departing the buffer in a specific time, for the time-dependent output rate and for the steady-state output rate. The latter is the key performance measure of the buffering mechanism, as it reflects its ability to process a specific number of packets in a time unit. To ensure broad applicability of the results in various networks and traffic types, a powerful and versatile model of the input stream is used, i.e., a BMAP. Numeric examples are provided, with several parameterisations of the BMAP, dropping probabilities and loads of the system.
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(This article belongs to the Section Communications and Networking)
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Open AccessArticle
Multi-Objective Optimization of Gateway Location Selection in Long-Range Wide Area Networks: A Tradeoff Analysis between System Costs and Bitrate Maximization
by
Charuay Savithi and Chutchai Kaewta
J. Sens. Actuator Netw. 2024, 13(1), 3; https://doi.org/10.3390/jsan13010003 - 02 Jan 2024
Abstract
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LoRaWANs play a critical role in various applications such as smart farming, industrial IoT, and smart cities. The strategic placement of gateways significantly influences network performance optimization. This study presents a comprehensive analysis of the tradeoffs between system costs and bitrate maximization for
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LoRaWANs play a critical role in various applications such as smart farming, industrial IoT, and smart cities. The strategic placement of gateways significantly influences network performance optimization. This study presents a comprehensive analysis of the tradeoffs between system costs and bitrate maximization for selecting optimal gateway locations in LoRaWANs. To address this challenge, a rigorous mathematical model is formulated to incorporate essential factors and constraints related to gateway selection. Furthermore, we propose an innovative metaheuristic algorithm known as the M-VaNSAS algorithm, which effectively explores the solution space and identifies favorable gateway locations. The Pareto front and TOPSIS methods are employed to evaluate and rank the generated solutions, providing a robust assessment framework. Our research findings highlight the suitability of a network model comprising 144 gateways tailored for the Ubon Ratchathani province. Among the evaluated algorithms, the M-VaNSAS method demonstrates exceptional efficiency in gateway location selection, outperforming the PSO, DE, and GA methods.
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