Pub Date : 2025-04-24DOI: 10.1109/JSYST.2025.3554840
Dezhen Yang;Yeyang Liu;Yi Ren;Xiaobin Li;Zili Wang
Effective boundary scenario generation methods are critical for dynamic target tracking when evaluating the performance of unmanned aerial vehicles. However, traditional methods primarily rely on exhaustive testing or random sampling and often assume that different contributing factors are independent. This results in the ineffective generation of boundary scenarios and a lack of realism. In this study, a novel high-dimensional dynamic characteristics-based boundary test scenario generation method is proposed using reinforcement learning (RL). Boundary test scenarios can be explored more purposive, by designing an appropriate reward function. First, an innovative scenario modeling method is developed to model the influence of environment, occlusion, and other interference. A joint distribution model of the key correlation factors, such as light intensity and clouds, is also established. This ensures scenario authenticity and test accuracy. Subsequently, a high-dimensional dynamic spatial Markov decision process (HDDS-MDP) model is constructed to facilitate the generation of boundary scenarios based on the scenario modeling. Ultimately, RL is employed to solve the HDDS-MDP model and generate boundary test scenario, thereby substantially improves the effectiveness of boundary test scenario generation. The simulation results indicate that the boundary test scenario generation effectiveness is improved by 91% over random sampling methods.
{"title":"A High-Dimensional Dynamic Characteristics-Based Boundary Test Scenario Generation Method for UAVs in Dynamic Target Tracking","authors":"Dezhen Yang;Yeyang Liu;Yi Ren;Xiaobin Li;Zili Wang","doi":"10.1109/JSYST.2025.3554840","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3554840","url":null,"abstract":"Effective boundary scenario generation methods are critical for dynamic target tracking when evaluating the performance of unmanned aerial vehicles. However, traditional methods primarily rely on exhaustive testing or random sampling and often assume that different contributing factors are independent. This results in the ineffective generation of boundary scenarios and a lack of realism. In this study, a novel high-dimensional dynamic characteristics-based boundary test scenario generation method is proposed using reinforcement learning (RL). Boundary test scenarios can be explored more purposive, by designing an appropriate reward function. First, an innovative scenario modeling method is developed to model the influence of environment, occlusion, and other interference. A joint distribution model of the key correlation factors, such as light intensity and clouds, is also established. This ensures scenario authenticity and test accuracy. Subsequently, a high-dimensional dynamic spatial Markov decision process (HDDS-MDP) model is constructed to facilitate the generation of boundary scenarios based on the scenario modeling. Ultimately, RL is employed to solve the HDDS-MDP model and generate boundary test scenario, thereby substantially improves the effectiveness of boundary test scenario generation. The simulation results indicate that the boundary test scenario generation effectiveness is improved by 91% over random sampling methods.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"553-564"},"PeriodicalIF":4.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-23DOI: 10.1109/JSYST.2025.3553818
Minh-Sang Van Nguyen;Dinh-Thuan Do;Phu Tran Tin;Alireza Vahid
We investigate the integration of an active reconfigurable intelligent surface (ARIS) with nonorthogonal multiple access (NOMA) to enhance the secrecy performance and the security capabilities in Internet of Things (IoT) systems. The system model incorporates ARIS and NOMA, allowing for improved power allocation and higher security. In particular, the physical-layer security of an ARIS-NOMA system is investigated when the system is subject to eavesdropping by a malicious user in a user pair group. To provide real-world impact, we examine the main system performance metrics, including the connection outage probability, the secrecy outage probability (SOP), and the strictly positive secrecy capacity, which are important guidelines in evaluating the system's reliability, security, and achievable secrecy rates. We evaluate the impact of distances between the ARIS, the eavesdropper, and the base station on the SOP. We derive the optimal power allocation factors in the NOMA scheme, which provides insights into the system design and parameter adjustment to achieve robust and secure operation. In comparison to a benchmark model using the orthogonal multiple access, we show ARIS-NOMA is a promising solution to further enhance security and secrecy in IoT networks.
{"title":"Secure Performance Analysis of User Pairs in Active Reconfigurable Intelligent Surface-Aided IoT Systems","authors":"Minh-Sang Van Nguyen;Dinh-Thuan Do;Phu Tran Tin;Alireza Vahid","doi":"10.1109/JSYST.2025.3553818","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3553818","url":null,"abstract":"We investigate the integration of an active reconfigurable intelligent surface (ARIS) with nonorthogonal multiple access (NOMA) to enhance the secrecy performance and the security capabilities in Internet of Things (IoT) systems. The system model incorporates ARIS and NOMA, allowing for improved power allocation and higher security. In particular, the physical-layer security of an ARIS-NOMA system is investigated when the system is subject to eavesdropping by a malicious user in a user pair group. To provide real-world impact, we examine the main system performance metrics, including the connection outage probability, the secrecy outage probability (SOP), and the strictly positive secrecy capacity, which are important guidelines in evaluating the system's reliability, security, and achievable secrecy rates. We evaluate the impact of distances between the ARIS, the eavesdropper, and the base station on the SOP. We derive the optimal power allocation factors in the NOMA scheme, which provides insights into the system design and parameter adjustment to achieve robust and secure operation. In comparison to a benchmark model using the orthogonal multiple access, we show ARIS-NOMA is a promising solution to further enhance security and secrecy in IoT networks.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"370-381"},"PeriodicalIF":4.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-21DOI: 10.1109/JSYST.2025.3557729
Guoliang Chen;Wenqing Zhao;Jianwei Xia;Zhichuang Wang;Ju H. Park
In this article, the vehicular platoons under aperiodic sampled-data information exchange between connected neighbors are implemented with an average output consensus while achieving differential privacy protection. Initially, the complex vehicle dynamics system is simplified into a heterogeneous linear system interconnected through a communication graph. Subsequently, a distributed hybrid controller is deployed, specifically tailored for handling the intermittent sampled-data information, and is augmented with a dynamic noise generator. This framework restricts information exchange to a predefined neighborhood set of vehicles. To ensure differential privacy, design and incorporate random noise adhering to a Laplace distribution, where the decay index and control gain are adjustable parameters corresponding to the desired privacy level and system accuracy, respectively. This noise injection is guided by a differential privacy noise utilization algorithm. The controller design is then formulated and solved using a combination of the pole placement method and the generalized inverse concept, enabling effective networked control. Lastly, simulation examples are provided to rigorously validate the proposed theoretical framework, demonstrating its efficacy in maintaining platoon coherence while preserving the privacy of individual vehicle data.
{"title":"Differentially Private Aperiodic Sampled-Data Consensus for Intelligent Interconnected Heterogeneous Vehicular Platoons","authors":"Guoliang Chen;Wenqing Zhao;Jianwei Xia;Zhichuang Wang;Ju H. Park","doi":"10.1109/JSYST.2025.3557729","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3557729","url":null,"abstract":"In this article, the vehicular platoons under aperiodic sampled-data information exchange between connected neighbors are implemented with an average output consensus while achieving differential privacy protection. Initially, the complex vehicle dynamics system is simplified into a heterogeneous linear system interconnected through a communication graph. Subsequently, a distributed hybrid controller is deployed, specifically tailored for handling the intermittent sampled-data information, and is augmented with a dynamic noise generator. This framework restricts information exchange to a predefined neighborhood set of vehicles. To ensure differential privacy, design and incorporate random noise adhering to a Laplace distribution, where the decay index and control gain are adjustable parameters corresponding to the desired privacy level and system accuracy, respectively. This noise injection is guided by a differential privacy noise utilization algorithm. The controller design is then formulated and solved using a combination of the pole placement method and the generalized inverse concept, enabling effective networked control. Lastly, simulation examples are provided to rigorously validate the proposed theoretical framework, demonstrating its efficacy in maintaining platoon coherence while preserving the privacy of individual vehicle data.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"612-623"},"PeriodicalIF":4.0,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-11DOI: 10.1109/JSYST.2025.3550132
Yuanshan Liu;Yude Xia
The article investigates the leader–followers consensus problem of nonlinear multiagent systems with nonlinear dynamics and uncertain exogenous disturbances, employing dynamic triggered strategies (DTSs). An active disturbance rejection control is utilized to design a disturbance observer for estimating the disturbances in the input channel. To enhance communication efficiency and reduce energy consumption during information interaction between agents, the disturbances estimator is integrated into the consensus controller to suppress these disturbances. The convergence condition and lower bound of DTSs are derived. Finally, numerical simulations validate the effectiveness of the proposed algorithm.
Note to Practitioners— The complete system composed of multiple controlled objects in industrial production, transportation, aerospace, and other fields is inevitably influenced by external uncertain signals to varying degrees. The disturbance observer-based control technique effectively addresses the robust consensus problem of MASs. This significantly enhances the stability of most controlled systems operating in complex environments. Simultaneously, the distributed DTSs efficiently reduce communication burden between devices, minimize microprocessor computing power requirements, and save substantial economic costs. Undoubtedly, this offers a novel approach for the development of MASs.
{"title":"Robust Leader–Followers Consensus for Nonlinear Multiagent Systems With Exogenous Disturbances via Dynamic Triggered Strategies","authors":"Yuanshan Liu;Yude Xia","doi":"10.1109/JSYST.2025.3550132","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3550132","url":null,"abstract":"The article investigates the leader–followers consensus problem of nonlinear multiagent systems with nonlinear dynamics and uncertain exogenous disturbances, employing dynamic triggered strategies (DTSs). An active disturbance rejection control is utilized to design a disturbance observer for estimating the disturbances in the input channel. To enhance communication efficiency and reduce energy consumption during information interaction between agents, the disturbances estimator is integrated into the consensus controller to suppress these disturbances. The convergence condition and lower bound of DTSs are derived. Finally, numerical simulations validate the effectiveness of the proposed algorithm. <p><i>Note to Practitioners—</i> The complete system composed of multiple controlled objects in industrial production, transportation, aerospace, and other fields is inevitably influenced by external uncertain signals to varying degrees. The disturbance observer-based control technique effectively addresses the robust consensus problem of MASs. This significantly enhances the stability of most controlled systems operating in complex environments. Simultaneously, the distributed DTSs efficiently reduce communication burden between devices, minimize microprocessor computing power requirements, and save substantial economic costs. Undoubtedly, this offers a novel approach for the development of MASs.</p>","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"682-689"},"PeriodicalIF":4.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-11DOI: 10.1109/JSYST.2025.3554957
Matthew Litton;Doron Drusinsky;James Bret Michael
Developing and fielding complex systems requires proof that they are reliably correct with respect to their design and operating requirements. Especially for autonomous systems, which exhibit unanticipated emergent behavior, fully enumerating the range of possible correct and incorrect behaviors is intractable. Therefore, we propose an optimization-based search technique for generating high-quality, high-variance, and nontrivial data, which captures the range of correct and incorrect responses a system could exhibit. This manifold between desired and undesired behavior provides a more detailed understanding of system reliability than traditional testing or Monte Carlo simulations. After discovering data points along the manifold, we apply machine learning techniques to quantify the decision manifold's underlying mathematical function. Such models serve as correctness properties, which can be utilized to enable both verification during development and testing, as well as continuous assurance during operation, even amidst system adaptations and dynamic operating environments. This method can be applied in combination with a simulator in order to provide evidence of dependability to system designers and users, with the ultimate aim of establishing trust in the deployment of complex systems. In this proof-of-concept, we apply our method to a software-in-the-loop evaluation of an autonomous vehicle.
{"title":"Discovering Decision Manifolds to Assure Trusted Autonomous Systems","authors":"Matthew Litton;Doron Drusinsky;James Bret Michael","doi":"10.1109/JSYST.2025.3554957","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3554957","url":null,"abstract":"Developing and fielding complex systems requires proof that they are reliably correct with respect to their design and operating requirements. Especially for autonomous systems, which exhibit unanticipated emergent behavior, fully enumerating the range of possible correct and incorrect behaviors is intractable. Therefore, we propose an optimization-based search technique for generating high-quality, high-variance, and nontrivial data, which captures the range of correct and incorrect responses a system could exhibit. This manifold between desired and undesired behavior provides a more detailed understanding of system reliability than traditional testing or Monte Carlo simulations. After discovering data points along the manifold, we apply machine learning techniques to quantify the decision manifold's underlying mathematical function. Such models serve as correctness properties, which can be utilized to enable both verification during development and testing, as well as continuous assurance during operation, even amidst system adaptations and dynamic operating environments. This method can be applied in combination with a simulator in order to provide evidence of dependability to system designers and users, with the ultimate aim of establishing trust in the deployment of complex systems. In this proof-of-concept, we apply our method to a software-in-the-loop evaluation of an autonomous vehicle.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"413-424"},"PeriodicalIF":4.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This letter proposes a novel cluster-driven bilevel Load Redistribution (LR) attack model in cyber physical power systems. The main goal is on overloading multiple transmission lines while maintaining a high level of stealth. The proposed model employs cluster-based approach to form distinct clusters, each representing different load patterns within the power system. This enables the design of attack vectors that seamlessly blend with these load patterns, thereby challenging advanced anomaly detection systems. The stealth of the attack is quantified by the Stealth Distance Index (SDI), ensuring that injected false data remain within the maximum permissible distance from the centroid of its corresponding cluster. The proposed model is validated on the modified IEEE 14-bus and 30-bus systems, demonstrating enhanced stealth capabilities in LR attacks.
{"title":"Enhancing the Stealth of Load Redistribution Attacks: A Novel Cluster-Driven Approach","authors":"Rohini Haridas;Chenghong Gu;Satish Sharma;Rohit Bhakar","doi":"10.1109/JSYST.2025.3554205","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3554205","url":null,"abstract":"This letter proposes a novel cluster-driven bilevel Load Redistribution (LR) attack model in cyber physical power systems. The main goal is on overloading multiple transmission lines while maintaining a high level of stealth. The proposed model employs cluster-based approach to form distinct clusters, each representing different load patterns within the power system. This enables the design of attack vectors that seamlessly blend with these load patterns, thereby challenging advanced anomaly detection systems. The stealth of the attack is quantified by the Stealth Distance Index (SDI), ensuring that injected false data remain within the maximum permissible distance from the centroid of its corresponding cluster. The proposed model is validated on the modified IEEE 14-bus and 30-bus systems, demonstrating enhanced stealth capabilities in LR attacks.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"712-715"},"PeriodicalIF":4.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-09DOI: 10.1109/JSYST.2025.3553965
Zhemei Fang;Dazhi Chen;Qi Ju;Jianbo Wang
Architecture design for system-of-systems (SoSs) is a complex challenge due to interdependencies, uncertainties, and the large design space. The evolutionary nature of SoSs necessitates a multistage architecting process, adding further complexity. This article, thus, proposes a deep reinforcement learning based evolutionary architecture path selection method that considers uncertainties and interdependency. The approach employs an architecture framework to guide the design and defines SoS architecture decisions as the addition of systems and the allocation of operational architecture to physical architecture across sequential stages. Capability evaluation leverages a capability-activity-system structure, supported by a functional dependency network analysis method. Utilizing a deep neural network as a functional approximator to predict future SoS capability, the article develops a proximal policy optimization (PPO) algorithm that balances immediate and future needs. Applied to a mosaic warfare-oriented naval antisubmarine SoS, the proposed method outperforms heuristic optimization techniques by achieving higher SoS capability, reduced instability, and fewer violations of budget and intermediate requirements constraints in both deterministic and stochastic scenarios. These results highlight the PPO method's effectiveness in addressing SoS architecting path selection challenges under uncertainty.
{"title":"Architecting Path Selection Method for Incremental Evolution in System-of-Systems","authors":"Zhemei Fang;Dazhi Chen;Qi Ju;Jianbo Wang","doi":"10.1109/JSYST.2025.3553965","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3553965","url":null,"abstract":"Architecture design for system-of-systems (SoSs) is a complex challenge due to interdependencies, uncertainties, and the large design space. The evolutionary nature of SoSs necessitates a multistage architecting process, adding further complexity. This article, thus, proposes a deep reinforcement learning based evolutionary architecture path selection method that considers uncertainties and interdependency. The approach employs an architecture framework to guide the design and defines SoS architecture decisions as the addition of systems and the allocation of operational architecture to physical architecture across sequential stages. Capability evaluation leverages a capability-activity-system structure, supported by a functional dependency network analysis method. Utilizing a deep neural network as a functional approximator to predict future SoS capability, the article develops a proximal policy optimization (PPO) algorithm that balances immediate and future needs. Applied to a mosaic warfare-oriented naval antisubmarine SoS, the proposed method outperforms heuristic optimization techniques by achieving higher SoS capability, reduced instability, and fewer violations of budget and intermediate requirements constraints in both deterministic and stochastic scenarios. These results highlight the PPO method's effectiveness in addressing SoS architecting path selection challenges under uncertainty.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"636-647"},"PeriodicalIF":4.0,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-08DOI: 10.1109/JSYST.2025.3550559
Tao Yu;Hao Xu;Shuping He
This article is considered with the co-design problem of jump-like FlexRay protocol (FRP) and dynamic control for a class of discrete-time networked systems. A jump-like FRP is proposed to address the constraints of communication resources as well as nonperiodic denial of service (DoS) attacks in the sensor-to-controller communication network. The proposed novel protocol has the characteristics of traditional FRP time-triggered and event-triggered mechanisms. In addition, such protocol is able to avoid selecting sensors affected by DoS attacks. Subsequently, a set of dynamic output feedback controllers related to the selection of sensor nodes is designed to guarantee the finite-time boundedness of the closed-loop system with the prescribed $H_infty$ performance. However, the co-design problem of protocol and dynamic control includes more nonlinear terms, making the problem more challenging to be solved. In order to address the co-design problem and enhance system performance, a genetic-algorithm-based controller design approach has been proposed. Finally, a numerical example and a two-area power system example are given to illustrate the effectiveness of the proposed method.
{"title":"GA-Optimized Co-Design of Jump-Like FlexRay Protocol and Dynamic Control for NCSs and Its Applications","authors":"Tao Yu;Hao Xu;Shuping He","doi":"10.1109/JSYST.2025.3550559","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3550559","url":null,"abstract":"This article is considered with the co-design problem of jump-like FlexRay protocol (FRP) and dynamic control for a class of discrete-time networked systems. A jump-like FRP is proposed to address the constraints of communication resources as well as nonperiodic denial of service (DoS) attacks in the sensor-to-controller communication network. The proposed novel protocol has the characteristics of traditional FRP time-triggered and event-triggered mechanisms. In addition, such protocol is able to avoid selecting sensors affected by DoS attacks. Subsequently, a set of dynamic output feedback controllers related to the selection of sensor nodes is designed to guarantee the finite-time boundedness of the closed-loop system with the prescribed <inline-formula><tex-math>$H_infty$</tex-math></inline-formula> performance. However, the co-design problem of protocol and dynamic control includes more nonlinear terms, making the problem more challenging to be solved. In order to address the co-design problem and enhance system performance, a genetic-algorithm-based controller design approach has been proposed. Finally, a numerical example and a two-area power system example are given to illustrate the effectiveness of the proposed method.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"670-681"},"PeriodicalIF":4.0,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144339026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-01DOI: 10.1109/JSYST.2025.3547967
Prajnamaya Dass;Sudip Misra
The distributed Internet of Things (IoT) systems facilitate real-time services through the composition of loosely coupled microservices. The composed IoT service is the output of multiple microservices, executed at computationally capable edge or fog nodes, which we consider as the facility nodes (FNs). However, the service composition process in IoT microservice architectures is abstracted from the users that gives freedom to the FNs to act maliciously and provide low-quality IoT services. Further, the service composition needs to be transparent so that the FNs involved in a service cannot repudiate their involvement at a later time. In this article, we propose a novel, lightweight, trustworthy, and verifiable service composition framework for IoT-based systems that adopt microservice architecture. First, we propose a dynamic programming approach to select trustworthy FNs for each user request, while considering the trust scores of the FNs and the delay requirements of the users. Next, we propose a transparent service composition framework that uses lightweight cryptography functions to generate the proof-of-involvement for the FNs in each service. With the help of a trust controller, we verify the proofs generated by the FNs and update the trust scores of the FNs. Considering the user traces from Berlin city in the simulation of urban mobility tool, we show the efficacy of the proposed framework in maximizing user trust and detecting malicious FNs involved in user services. Further, we show that the delay and communication overhead of the proposed framework are very low compared to the state-of-the-art methods.
{"title":"$mu$-Trust: Trustworthy and Transparent Service Composition for Microservice-Based IoT Systems","authors":"Prajnamaya Dass;Sudip Misra","doi":"10.1109/JSYST.2025.3547967","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3547967","url":null,"abstract":"The distributed Internet of Things (IoT) systems facilitate real-time services through the composition of loosely coupled microservices. The composed IoT service is the output of multiple microservices, executed at computationally capable edge or fog nodes, which we consider as the facility nodes (FNs). However, the service composition process in IoT microservice architectures is abstracted from the users that gives freedom to the FNs to act maliciously and provide low-quality IoT services. Further, the service composition needs to be transparent so that the FNs involved in a service cannot repudiate their involvement at a later time. In this article, we propose a novel, lightweight, trustworthy, and verifiable service composition framework for IoT-based systems that adopt microservice architecture. First, we propose a dynamic programming approach to select trustworthy FNs for each user request, while considering the trust scores of the FNs and the delay requirements of the users. Next, we propose a transparent service composition framework that uses lightweight cryptography functions to generate the proof-of-involvement for the FNs in each service. With the help of a trust controller, we verify the proofs generated by the FNs and update the trust scores of the FNs. Considering the user traces from Berlin city in the simulation of urban mobility tool, we show the efficacy of the proposed framework in maximizing user trust and detecting malicious FNs involved in user services. Further, we show that the delay and communication overhead of the proposed framework are very low compared to the state-of-the-art methods.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"404-412"},"PeriodicalIF":4.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Narrowband Internet of Things (NB-IoT) is a technology specifically designated by the 3 rd Generation Partnership Project (3GPP) to meet the explosive demand for massive machine-type communications (mMTC), and it is evolving to RedCap. Industrial companies have increasingly adopted NB-IoT as the solution for mMTC due to its lightweight design and comprehensive technical specifications released by 3GPP. This article presents a system-level simulation framework for NB-IoT networks to evaluate their performance. The system-level simulator is structured into four parts: Initialization, pregeneration, main simulation loop, and postprocessing. In addition, three essential features are investigated to enhance coverage, support massive connections, and ensure low power consumption. Simulation results demonstrate that the cumulative distribution function curves of the signal-to-interference-and-noise ratio fully comply with industrial standards. Furthermore, the throughput performance explains how NB-IoT networks realize massive connections at the cost of data rate. This work highlights its practical utility and paves the way for developing NB-IoT networks.
{"title":"System-Level Simulation Framework for NB-IoT: Key Features and Performance Evaluation","authors":"Shutao Zhang;Wenkun Wen;Peiran Wu;Hongqing Huang;Liya Zhu;Yijia Guo;Tingting Yang;Minghua Xia","doi":"10.1109/JSYST.2025.3569189","DOIUrl":"https://doi.org/10.1109/JSYST.2025.3569189","url":null,"abstract":"Narrowband Internet of Things (NB-IoT) is a technology specifically designated by the 3 rd Generation Partnership Project (3GPP) to meet the explosive demand for massive machine-type communications (mMTC), and it is evolving to RedCap. Industrial companies have increasingly adopted NB-IoT as the solution for mMTC due to its lightweight design and comprehensive technical specifications released by 3GPP. This article presents a system-level simulation framework for NB-IoT networks to evaluate their performance. The system-level simulator is structured into four parts: Initialization, pregeneration, main simulation loop, and postprocessing. In addition, three essential features are investigated to enhance coverage, support massive connections, and ensure low power consumption. Simulation results demonstrate that the cumulative distribution function curves of the signal-to-interference-and-noise ratio fully comply with industrial standards. Furthermore, the throughput performance explains how NB-IoT networks realize massive connections at the cost of data rate. This work highlights its practical utility and paves the way for developing NB-IoT networks.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"19 2","pages":"577-588"},"PeriodicalIF":4.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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