Md. Saddam Hossain Mukta, Jubaer Ahmad, Mohaimenul Azam Khan Raiaan, Salekul Islam, Sami Azam, Mohammed Eunus Ali, Mirjam Jonkman
With the development of computer vision and deep learning technologies, rapidly expanding approaches have been introduced that allow anyone to create videos and pictures that are both phony and incredibly lifelike. The term deepfake methodology is used to describe such technologies. Face alteration can be performed both in videos and pictures with extreme realism using deepfake innovation. Deepfake recordings, the majority of them targeting politicians or celebrity personalities, have been widely disseminated online. On the other hand, different strategies have been outlined in the research to combat the issues brought up by deepfake. In this paper, we carry out a review by analyzing and comparing (1) the notable research contributions in the field of deepfake models and (2) widely used deepfake tools. We have also built two separate taxonomies for deepfake models and tools. These models and tools are also compared in terms of underlying algorithms, datasets they have used and their accuracy. A number of challenges and open issues have also been identified.
{"title":"An Investigation of the Effectiveness of Deepfake Models and Tools","authors":"Md. Saddam Hossain Mukta, Jubaer Ahmad, Mohaimenul Azam Khan Raiaan, Salekul Islam, Sami Azam, Mohammed Eunus Ali, Mirjam Jonkman","doi":"10.3390/jsan12040061","DOIUrl":"https://doi.org/10.3390/jsan12040061","url":null,"abstract":"With the development of computer vision and deep learning technologies, rapidly expanding approaches have been introduced that allow anyone to create videos and pictures that are both phony and incredibly lifelike. The term deepfake methodology is used to describe such technologies. Face alteration can be performed both in videos and pictures with extreme realism using deepfake innovation. Deepfake recordings, the majority of them targeting politicians or celebrity personalities, have been widely disseminated online. On the other hand, different strategies have been outlined in the research to combat the issues brought up by deepfake. In this paper, we carry out a review by analyzing and comparing (1) the notable research contributions in the field of deepfake models and (2) widely used deepfake tools. We have also built two separate taxonomies for deepfake models and tools. These models and tools are also compared in terms of underlying algorithms, datasets they have used and their accuracy. A number of challenges and open issues have also been identified.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136119404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research proposes a unique platform for lane change assistance for generating data-driven lane change (LC) decisions in vehicular networks. The goal is to reduce the frequency of emergency braking, the rate of vehicle collisions, and the amount of time spent in risky lanes. In order to analyze and mine the massive amounts of data, our platform uses effective Machine Learning (ML) techniques to forecast collisions and advise the driver to safely change lanes. From the unprocessed large data generated by the car sensors, kinematic information is retrieved, cleaned, and evaluated. Machine learning algorithms analyze this kinematic data and provide an action: either stay in lane or change lanes to the left or right. The model is trained using the ML techniques K-Nearest Neighbor, Artificial Neural Network, and Deep Reinforcement Learning based on a set of training data and focus on predicting driver actions. The proposed solution is validated via extensive simulations using a microscopic car-following mobility model, coupled with an accurate mathematical modelling. Performance analysis show that KNN yields up to best performance parameters. Finally, we draw conclusions for road safety stakeholders to adopt the safer technique to lane change maneuver.
{"title":"Safe Data-Driven Lane Change Decision Using Machine Learning in Vehicular Networks","authors":"R. Naja","doi":"10.3390/jsan12040059","DOIUrl":"https://doi.org/10.3390/jsan12040059","url":null,"abstract":"This research proposes a unique platform for lane change assistance for generating data-driven lane change (LC) decisions in vehicular networks. The goal is to reduce the frequency of emergency braking, the rate of vehicle collisions, and the amount of time spent in risky lanes. In order to analyze and mine the massive amounts of data, our platform uses effective Machine Learning (ML) techniques to forecast collisions and advise the driver to safely change lanes. From the unprocessed large data generated by the car sensors, kinematic information is retrieved, cleaned, and evaluated. Machine learning algorithms analyze this kinematic data and provide an action: either stay in lane or change lanes to the left or right. The model is trained using the ML techniques K-Nearest Neighbor, Artificial Neural Network, and Deep Reinforcement Learning based on a set of training data and focus on predicting driver actions. The proposed solution is validated via extensive simulations using a microscopic car-following mobility model, coupled with an accurate mathematical modelling. Performance analysis show that KNN yields up to best performance parameters. Finally, we draw conclusions for road safety stakeholders to adopt the safer technique to lane change maneuver.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43627196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ricardo Severino, João Rodrigues, João Alves, Luis Lino Ferreira
The fast development and adoption of IoT technologies has been enabling their application into increasingly sensitive domains, such as Medical and Industrial IoT, in which safety and cyber-security are paramount. While the number of deployed IoT devices increases annually, they still present severe cyber-security vulnerabilities, becoming potential targets and entry points for further attacks. As these nodes become compromised, attackers aim to set up stealthy communication behaviours, to exfiltrate data or to orchestrate nodes in a cloaked fashion, and network timing covert channels are increasingly being used with such malicious intents. The IEEE 802.15.4 is one of the most pervasive protocols in IoT and a fundamental part of many communication infrastructures. Despite this fact, the possibility of setting up such covert communication techniques on this medium has received very little attention. We aim to analyse the performance and feasibility of such covert-channel implementations upon the IEEE 802.15.4 protocol, particularly upon the DSME behaviour, one of the most promising for large-scale time critical communications. This enables us to better understand the involved risk of such threats and help support the development of active cyber-security mechanisms to mitigate these threats, which, for now, we provide in the form of practical network setup recommendations.
{"title":"Performance Assessment and Mitigation of Timing Covert Channels over the IEEE 802.15.4","authors":"Ricardo Severino, João Rodrigues, João Alves, Luis Lino Ferreira","doi":"10.3390/jsan12040060","DOIUrl":"https://doi.org/10.3390/jsan12040060","url":null,"abstract":"The fast development and adoption of IoT technologies has been enabling their application into increasingly sensitive domains, such as Medical and Industrial IoT, in which safety and cyber-security are paramount. While the number of deployed IoT devices increases annually, they still present severe cyber-security vulnerabilities, becoming potential targets and entry points for further attacks. As these nodes become compromised, attackers aim to set up stealthy communication behaviours, to exfiltrate data or to orchestrate nodes in a cloaked fashion, and network timing covert channels are increasingly being used with such malicious intents. The IEEE 802.15.4 is one of the most pervasive protocols in IoT and a fundamental part of many communication infrastructures. Despite this fact, the possibility of setting up such covert communication techniques on this medium has received very little attention. We aim to analyse the performance and feasibility of such covert-channel implementations upon the IEEE 802.15.4 protocol, particularly upon the DSME behaviour, one of the most promising for large-scale time critical communications. This enables us to better understand the involved risk of such threats and help support the development of active cyber-security mechanisms to mitigate these threats, which, for now, we provide in the form of practical network setup recommendations.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41271876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benedetta Picano, Leonardo Scommegna, E. Vicario, R. Fantacci
Mobile online gaming is constantly growing in popularity and is expected to be one of the most important applications of upcoming sixth generation networks. Nevertheless, it remains challenging for game providers to support it, mainly due to its intrinsic and ever-stricter need for service continuity in the presence of user mobility. In this regard, this paper proposes a machine learning strategy to forecast user channel conditions, aiming at guaranteeing a seamless service whenever a user is involved in a handover, i.e., moving from the coverage area of one base station towards another. In particular, the proposed channel condition prediction approach involves the exploitation of an echo state network, an efficient class of recurrent neural network, that is empowered with a genetic algorithm to perform parameter optimization. The echo state network is applied to improve user decisions regarding the selection of the serving base station, avoiding game breaks as much as possible to lower game lag time. The validity of the proposed framework is confirmed by simulations in comparison to the long short-term memory approach and another alternative method, aimed at thoroughly testing the accuracy of the learning module in forecasting user trajectories and in reducing game breaks or lag time, with a focus on a sixth generation network application scenario.
{"title":"Echo State Learning for User Trajectory Prediction to Minimize Online Game Breaks in 6G Terahertz Networks","authors":"Benedetta Picano, Leonardo Scommegna, E. Vicario, R. Fantacci","doi":"10.3390/jsan12040058","DOIUrl":"https://doi.org/10.3390/jsan12040058","url":null,"abstract":"Mobile online gaming is constantly growing in popularity and is expected to be one of the most important applications of upcoming sixth generation networks. Nevertheless, it remains challenging for game providers to support it, mainly due to its intrinsic and ever-stricter need for service continuity in the presence of user mobility. In this regard, this paper proposes a machine learning strategy to forecast user channel conditions, aiming at guaranteeing a seamless service whenever a user is involved in a handover, i.e., moving from the coverage area of one base station towards another. In particular, the proposed channel condition prediction approach involves the exploitation of an echo state network, an efficient class of recurrent neural network, that is empowered with a genetic algorithm to perform parameter optimization. The echo state network is applied to improve user decisions regarding the selection of the serving base station, avoiding game breaks as much as possible to lower game lag time. The validity of the proposed framework is confirmed by simulations in comparison to the long short-term memory approach and another alternative method, aimed at thoroughly testing the accuracy of the learning module in forecasting user trajectories and in reducing game breaks or lag time, with a focus on a sixth generation network application scenario.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46890697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a general and interoperable Web of Things (WoT)-oriented architecture to support a distributed storage application. In particular, the focus is on a distributed ledger service dedicated to machine-to-machine (M2M) transactions occurring in an intelligent ecosystem. For this purpose, the basic functional modules have been characterized and integrated into a comprehensive framework relying on an IOTA approach. Furthermore, a general protocol that is built upon an underlying publish-and-subscribe framework is proposed to support all the application phases. The proposed approach has been validated by a simulation campaign targeting the achievable latency and throughput and, further, by a qualitative analysis of high-level metrics, both pointing out several advantages in terms of interoperability, scalability, and mobility support, together with addressing some constraints affecting service availability and security.
{"title":"Distributed Ledger as a Service: A Web 3.0-Oriented Architecture","authors":"F. Chiti, Giorgio Gandini","doi":"10.3390/jsan12040057","DOIUrl":"https://doi.org/10.3390/jsan12040057","url":null,"abstract":"This paper proposes a general and interoperable Web of Things (WoT)-oriented architecture to support a distributed storage application. In particular, the focus is on a distributed ledger service dedicated to machine-to-machine (M2M) transactions occurring in an intelligent ecosystem. For this purpose, the basic functional modules have been characterized and integrated into a comprehensive framework relying on an IOTA approach. Furthermore, a general protocol that is built upon an underlying publish-and-subscribe framework is proposed to support all the application phases. The proposed approach has been validated by a simulation campaign targeting the achievable latency and throughput and, further, by a qualitative analysis of high-level metrics, both pointing out several advantages in terms of interoperability, scalability, and mobility support, together with addressing some constraints affecting service availability and security.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48923243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wireless communication is an essential element within Intelligent Transportation Systems and motivates new approaches to intersection management, allowing safer and more efficient road usage. With lives at stake, wireless protocols should be readily available and guarantee safe coordination for all involved traffic participants, even in the presence of radio failures. This work introduces STARC, a coordination primitive for safe, decentralized resource coordination. Using STARC, traffic participants can safely coordinate at intersections despite unreliable radio environments and without a central entity or infrastructure. Unlike other methods that require costly and energy-consuming platforms, STARC utilizes affordable and efficient Internet of Things devices that connect cars, bicycles, electric scooters, pedestrians, and cyclists. For communication, STARC utilizes low-power IEEE 802.15.4 radios and Synchronous Transmissions for multi-hop communication. In addition, the protocol provides distributed transaction, election, and handover mechanisms for decentralized, thus cost-efficient, deployments. While STARC’s coordination remains resource-agnostic, this work presents and evaluates STARC in a roadside scenario. Our simulations have shown that using STARC at intersections leads to safer and more efficient vehicle coordination. We found that average waiting times can be reduced by up to 50% compared to using a fixed traffic light schedule in situations with fewer than 1000 vehicles per hour. Additionally, we design platooning on top of STARC, improving scalability and outperforming static traffic lights even at traffic loads exceeding 1000 vehicles per hour.
{"title":"STARC: Decentralized Coordination Primitive on Low-Power IoT Devices for Autonomous Intersection Management","authors":"Patrick Rathje, Valentin Poirot, O. Landsiedel","doi":"10.3390/jsan12040056","DOIUrl":"https://doi.org/10.3390/jsan12040056","url":null,"abstract":"Wireless communication is an essential element within Intelligent Transportation Systems and motivates new approaches to intersection management, allowing safer and more efficient road usage. With lives at stake, wireless protocols should be readily available and guarantee safe coordination for all involved traffic participants, even in the presence of radio failures. This work introduces STARC, a coordination primitive for safe, decentralized resource coordination. Using STARC, traffic participants can safely coordinate at intersections despite unreliable radio environments and without a central entity or infrastructure. Unlike other methods that require costly and energy-consuming platforms, STARC utilizes affordable and efficient Internet of Things devices that connect cars, bicycles, electric scooters, pedestrians, and cyclists. For communication, STARC utilizes low-power IEEE 802.15.4 radios and Synchronous Transmissions for multi-hop communication. In addition, the protocol provides distributed transaction, election, and handover mechanisms for decentralized, thus cost-efficient, deployments. While STARC’s coordination remains resource-agnostic, this work presents and evaluates STARC in a roadside scenario. Our simulations have shown that using STARC at intersections leads to safer and more efficient vehicle coordination. We found that average waiting times can be reduced by up to 50% compared to using a fixed traffic light schedule in situations with fewer than 1000 vehicles per hour. Additionally, we design platooning on top of STARC, improving scalability and outperforming static traffic lights even at traffic loads exceeding 1000 vehicles per hour.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48049986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We perform a comprehensive analysis of packet losses occurring at an AQM buffer in which the packet deletion probability is relative to the size of the queue. Several characteristics of the loss process are derived: the number of deletions in an interval of length t, the temporary intensity of deletions at arbitrary time, the steady-state loss ratio, and the number of losses if there is no service. All of them are obtained for a general deletion probability function and an advanced model of the arrival process, which incorporates, among other things, the autocorrelation of traffic. Analytical results are accompanied by examples in which numerical values are obtained for several configurations of the system. Using these examples, the dependence of the loss process on the initial system state, deletion probability function, and traffic autocorrelation are discussed.
{"title":"Loss Process at an AQM Buffer","authors":"A. Chydzinski","doi":"10.3390/jsan12040055","DOIUrl":"https://doi.org/10.3390/jsan12040055","url":null,"abstract":"We perform a comprehensive analysis of packet losses occurring at an AQM buffer in which the packet deletion probability is relative to the size of the queue. Several characteristics of the loss process are derived: the number of deletions in an interval of length t, the temporary intensity of deletions at arbitrary time, the steady-state loss ratio, and the number of losses if there is no service. All of them are obtained for a general deletion probability function and an advanced model of the arrival process, which incorporates, among other things, the autocorrelation of traffic. Analytical results are accompanied by examples in which numerical values are obtained for several configurations of the system. Using these examples, the dependence of the loss process on the initial system state, deletion probability function, and traffic autocorrelation are discussed.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48892216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrea Volpi, R. Montanari, L. Tebaldi, Marco Mambrioni
The present work originates from a previous study in which a low-cost Real-Time Locating System (RTLS) based on Ultra-Wideband signals was developed and tested both in a laboratory and in a real industrial environment for assessing its performance and determining the best configuration, according to some selected KPIs. Starting from the future research directions depicted, the evolution herein presented is twofold. First, tests performed in the laboratory are refined and deepened in terms of (i) different anchors’ arrangements and orientation; (ii) the increased number of tested tags; and (iii) the tags’ battery capacity test. Second, the development and deployment of the industrial solution as well is improved by means of a case for hosting tags to be positioned on the asset to be tracked, realized through 3D printing, in line with the industrial context requirements. Finally, an economic analysis is performed so as to demonstrate the convenience of the investment and the feasibility of the solution. Results are positive and promising in terms of both economic sustainability and implementation of the system in a real industrial environment and may constitute guidelines for practitioners and managers.
{"title":"Low-Cost Real-Time Locating System Solution Development and Implementation in Manufacturing Industry","authors":"Andrea Volpi, R. Montanari, L. Tebaldi, Marco Mambrioni","doi":"10.3390/jsan12040054","DOIUrl":"https://doi.org/10.3390/jsan12040054","url":null,"abstract":"The present work originates from a previous study in which a low-cost Real-Time Locating System (RTLS) based on Ultra-Wideband signals was developed and tested both in a laboratory and in a real industrial environment for assessing its performance and determining the best configuration, according to some selected KPIs. Starting from the future research directions depicted, the evolution herein presented is twofold. First, tests performed in the laboratory are refined and deepened in terms of (i) different anchors’ arrangements and orientation; (ii) the increased number of tested tags; and (iii) the tags’ battery capacity test. Second, the development and deployment of the industrial solution as well is improved by means of a case for hosting tags to be positioned on the asset to be tracked, realized through 3D printing, in line with the industrial context requirements. Finally, an economic analysis is performed so as to demonstrate the convenience of the investment and the feasibility of the solution. Results are positive and promising in terms of both economic sustainability and implementation of the system in a real industrial environment and may constitute guidelines for practitioners and managers.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46716082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patients suffering from motor disorders or weakness resulting from either serious spinal cord injury or stroke often require rehabilitation therapy to regain their mobility. In the lower limbs, exoskeletons have two motors aligned with the patients’ hip and knee to assist in rehabilitation exercises by supporting the patient’s body structure to increase the torques at the hip and knee joints. Assistive rehabilitation is, however, challenging, as the human torque is unknown and varies from patient to patient. This poses difficulties in determining the level of assistance required for a particular patient. In this paper, therefore, a modified extended state observer (ESO)-based integral sliding mode (ISM) controller (MESOISMC) for lower-limb exoskeleton assistive gait rehabilitation is proposed. The ESO is used to estimate the unknown human torque without application of a torque sensor while the ISMC is used to achieve robust tracking of preset hip and knee joint angles by considering the estimated human torque as a disturbance. The performance of the proposed MESOISMC was assessed using the mean absolute error (MAE). The obtained results show an 85.02% and 87.38% reduction in the MAE for the hip and joint angles, respectively, when the proposed MESOISMC is compared with ISMC with both controllers tuned via LMI optimization. The results also indicate that the proposed MESOISMC method is effective and efficient for user comfort and safety during gait rehabilitation training.
{"title":"Sensorless Estimation of Human Joint Torque for Robust Tracking Control of Lower-Limb Exoskeleton Assistive Gait Rehabilitation","authors":"A. Abdullahi, R. Chaichaowarat","doi":"10.3390/jsan12040053","DOIUrl":"https://doi.org/10.3390/jsan12040053","url":null,"abstract":"Patients suffering from motor disorders or weakness resulting from either serious spinal cord injury or stroke often require rehabilitation therapy to regain their mobility. In the lower limbs, exoskeletons have two motors aligned with the patients’ hip and knee to assist in rehabilitation exercises by supporting the patient’s body structure to increase the torques at the hip and knee joints. Assistive rehabilitation is, however, challenging, as the human torque is unknown and varies from patient to patient. This poses difficulties in determining the level of assistance required for a particular patient. In this paper, therefore, a modified extended state observer (ESO)-based integral sliding mode (ISM) controller (MESOISMC) for lower-limb exoskeleton assistive gait rehabilitation is proposed. The ESO is used to estimate the unknown human torque without application of a torque sensor while the ISMC is used to achieve robust tracking of preset hip and knee joint angles by considering the estimated human torque as a disturbance. The performance of the proposed MESOISMC was assessed using the mean absolute error (MAE). The obtained results show an 85.02% and 87.38% reduction in the MAE for the hip and joint angles, respectively, when the proposed MESOISMC is compared with ISMC with both controllers tuned via LMI optimization. The results also indicate that the proposed MESOISMC method is effective and efficient for user comfort and safety during gait rehabilitation training.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45319490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
At present, many network applications are seeking to implement Time-Sensitive Network (TSN) technology, which not only furnishes communication transmission services that are deterministic, low-latency, highly dependable, and have ample bandwidth, but also enables unified configuration management, permitting different network types to function under a single management system. These characteristics enable it to be widely used in many fields such as industrial sensor and actuator networks, in-vehicle networks, data center networks, and edge computing. Nonetheless, TSN’s configuration management faces numerous difficulties and challenges related to network deployment, automated operation, and maintenance, as well as real-time and safety assurance, rendering it exceedingly intricate. In recent years, some studies have been conducted on TSN configuration management, encompassing various aspects such as system design, key technologies for configuration management, protocol enhancement, and application development. Nevertheless, there is a dearth of systematic summaries of these studies. Hence, this article aims to provide a comprehensive overview of TSN configuration management. Drawing upon more than 70 relevant publications and the pertinent standards established by the IEEE 802.1 TSN working group, we first introduce the system architecture of TSN configuration management from a macro perspective and then explore specific technical details. Additionally, we demonstrate its application scenarios through practical cases and finally highlight the challenges and future research directions. We aspire to provide a comprehensive reference for peers and new researchers interested in TSN configuration management.
{"title":"Recent Advances in Time-Sensitive Network Configuration Management: A Literature Review","authors":"Boxin Shi, Xiaodong Tu, Bin Wu, Yifei Peng","doi":"10.3390/jsan12040052","DOIUrl":"https://doi.org/10.3390/jsan12040052","url":null,"abstract":"At present, many network applications are seeking to implement Time-Sensitive Network (TSN) technology, which not only furnishes communication transmission services that are deterministic, low-latency, highly dependable, and have ample bandwidth, but also enables unified configuration management, permitting different network types to function under a single management system. These characteristics enable it to be widely used in many fields such as industrial sensor and actuator networks, in-vehicle networks, data center networks, and edge computing. Nonetheless, TSN’s configuration management faces numerous difficulties and challenges related to network deployment, automated operation, and maintenance, as well as real-time and safety assurance, rendering it exceedingly intricate. In recent years, some studies have been conducted on TSN configuration management, encompassing various aspects such as system design, key technologies for configuration management, protocol enhancement, and application development. Nevertheless, there is a dearth of systematic summaries of these studies. Hence, this article aims to provide a comprehensive overview of TSN configuration management. Drawing upon more than 70 relevant publications and the pertinent standards established by the IEEE 802.1 TSN working group, we first introduce the system architecture of TSN configuration management from a macro perspective and then explore specific technical details. Additionally, we demonstrate its application scenarios through practical cases and finally highlight the challenges and future research directions. We aspire to provide a comprehensive reference for peers and new researchers interested in TSN configuration management.","PeriodicalId":37584,"journal":{"name":"Journal of Sensor and Actuator Networks","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45871310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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