Pub Date : 2024-06-05DOI: 10.1109/JSYST.2024.3403673
Raj Mohan Singh;Geeta Sikka;Lalit Kumar Awasthi
With the rapid advancement of Internet of Things technology, the field of fog computing has garnered significant attention and hence become a workable processing platform for upcoming applications. However, compared with vast computing capability of the cloud, the fog nodes have resource constraints, are heterogeneous in nature, and highly distributed. Due to the growing demand as well as diversity of applications, the nodes in a fog network become overloaded, which makes load balancing a prime concern. In this work, a load balancing aware task selection and migration approach is proposed comprising two algorithms to select and place tasks from multiple overloaded nodes to suitable destination nodes. The Selection algorithm determines the tasks that should be migrated from overloaded nodes. Placement algorithm focuses on finding a near optimal solution by applying modified binary particle swarm optimization. Specifically, the objective is to minimize execution time and transfer time of tasks. Simulation studies conducted on iFogSim prove that the suggested approach outperforms the existing approaches in terms of task execution time, task transfer time, and makespan.
{"title":"LBATSM: Load Balancing Aware Task Selection and Migration Approach in Fog Computing Environment","authors":"Raj Mohan Singh;Geeta Sikka;Lalit Kumar Awasthi","doi":"10.1109/JSYST.2024.3403673","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3403673","url":null,"abstract":"With the rapid advancement of Internet of Things technology, the field of fog computing has garnered significant attention and hence become a workable processing platform for upcoming applications. However, compared with vast computing capability of the cloud, the fog nodes have resource constraints, are heterogeneous in nature, and highly distributed. Due to the growing demand as well as diversity of applications, the nodes in a fog network become overloaded, which makes load balancing a prime concern. In this work, a load balancing aware task selection and migration approach is proposed comprising two algorithms to select and place tasks from multiple overloaded nodes to suitable destination nodes. The Selection algorithm determines the tasks that should be migrated from overloaded nodes. Placement algorithm focuses on finding a near optimal solution by applying modified binary particle swarm optimization. Specifically, the objective is to minimize execution time and transfer time of tasks. Simulation studies conducted on iFogSim prove that the suggested approach outperforms the existing approaches in terms of task execution time, task transfer time, and makespan.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"796-804"},"PeriodicalIF":4.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435213","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 : 2024-06-05DOI: 10.1109/JSYST.2024.3403103
Lili Wang;Shiming Chen
This article gives an investigation to the connectivity preserving consensus (CPC) issue for the second-order heterogeneous multiagent systems (MASs), which are constituted by linear and nonlinear subsystem. First, a consensus algorithm for the system without input constraints is proposed and some sufficient conditions for consensus are obtained. Due to the limited communication distance of each agent, the algorithm maintains network connectivity based on potential function techniques. Then, considering the linear and nonlinear subsystem with input constraints, respectively, the results indicate that as long as certain conditions are met, all agents can be guaranteed to achieve CPC. Furthermore, the proposed algorithm is extended to the entire system with input constraints. Five examples are provided to demonstrate efficiency of theoretical results.
{"title":"Connectivity Preserving Consensus for Second-Order Heterogeneous MASs With Input Constraints","authors":"Lili Wang;Shiming Chen","doi":"10.1109/JSYST.2024.3403103","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3403103","url":null,"abstract":"This article gives an investigation to the connectivity preserving consensus (CPC) issue for the second-order heterogeneous multiagent systems (MASs), which are constituted by linear and nonlinear subsystem. First, a consensus algorithm for the system without input constraints is proposed and some sufficient conditions for consensus are obtained. Due to the limited communication distance of each agent, the algorithm maintains network connectivity based on potential function techniques. Then, considering the linear and nonlinear subsystem with input constraints, respectively, the results indicate that as long as certain conditions are met, all agents can be guaranteed to achieve CPC. Furthermore, the proposed algorithm is extended to the entire system with input constraints. Five examples are provided to demonstrate efficiency of theoretical results.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1471-1480"},"PeriodicalIF":4.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435228","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}
Edge intelligence has recently attracted great interest from industry and academia, and it greatly improves the processing speed at the edge by moving data and artificial intelligence to the edge of the network. However, edge devices have bottlenecks in battery capacity and computing power, making it challenging to perform computing tasks in dynamic and harsh network environments. Especially in disaster scenarios, edge (rescue) devices are more likely to fail due to unreliable wireless communications and scattered rescue requests, which makes it urgent to explore how to provide low-latency, reliable services through edge collaboration. In this article, we investigate the task offloading mechanism in mobile edge computing networks, aiming to ensure fault tolerance and rapid response of computing services in dynamic and harsh scenarios. Specifically, we design a fault-tolerant distributed task offloading scheme, which minimizes task execution time and system energy consumption through the multi-agent proximal policy optimization algorithm. Furthermore, we introduce logarithmic ratio reward functions and action masking to reduce the impact of different task queue lengths while accelerating model convergence. Numerical results show that the proposed algorithm is suitable for service failure scenarios, effectively meeting the reliability requirements of tasks while simultaneously reducing system energy consumption and processing latency.
{"title":"Decentralized and Fault-Tolerant Task Offloading for Enabling Network Edge Intelligence","authors":"Huixiang Zhang;Kaihua Liao;Yu Tai;Wenqiang Ma;Guoyan Cao;Wen Sun;Lexi Xu","doi":"10.1109/JSYST.2024.3403696","DOIUrl":"https://doi.org/10.1109/JSYST.2024.3403696","url":null,"abstract":"Edge intelligence has recently attracted great interest from industry and academia, and it greatly improves the processing speed at the edge by moving data and artificial intelligence to the edge of the network. However, edge devices have bottlenecks in battery capacity and computing power, making it challenging to perform computing tasks in dynamic and harsh network environments. Especially in disaster scenarios, edge (rescue) devices are more likely to fail due to unreliable wireless communications and scattered rescue requests, which makes it urgent to explore how to provide low-latency, reliable services through edge collaboration. In this article, we investigate the task offloading mechanism in mobile edge computing networks, aiming to ensure fault tolerance and rapid response of computing services in dynamic and harsh scenarios. Specifically, we design a fault-tolerant distributed task offloading scheme, which minimizes task execution time and system energy consumption through the multi-agent proximal policy optimization algorithm. Furthermore, we introduce logarithmic ratio reward functions and action masking to reduce the impact of different task queue lengths while accelerating model convergence. Numerical results show that the proposed algorithm is suitable for service failure scenarios, effectively meeting the reliability requirements of tasks while simultaneously reducing system energy consumption and processing latency.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1459-1470"},"PeriodicalIF":4.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435393","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 : 2024-04-30DOI: 10.1109/JSYST.2024.3391766
Haoyue Yang;Hao Zhang;Zhuping Wang;Chao Huang;Huaicheng Yan
In this article, the optimal consensus problem for a class of nonlinear multiagent systems in discrete-time case is investigated under jump faults and false data injection (FDI) attacks. First, a general fault model with coefficients obeying a semi-Markov process is introduced into system dynamics. A joint state and fault observer based on the hidden semi-Markov model is designed to estimate both the agent's state and the fault signals. Sufficient conditions for the existence of observer gains are established by constructing the stochastic Lyapunov function with hidden mode, observed mode, and elapsed time dependencies. Based on the observed states, we reconstruct the local performance metric functions of agents and design a policy-value iteration algorithm to address the multiplayer game problem. Then, an neural network policy-value iteration approximation algorithm is proposed, which obtains an approximate Nash equilibrium solution of the multiplayer games. Further, a secure fault-tolerant optimal consensus controller with fault compensation and attack attenuation terms is designed to achieve optimal tracking control, and the stability of the neighbor tracking error system is rigorously demonstrated. Finally, illustrative example and comparison simulations are provided to verify the validity and applicability of the proposed results.
{"title":"Asynchronous Observer-Based Fault-Tolerant Optimal Control of Multiagent Systems","authors":"Haoyue Yang;Hao Zhang;Zhuping Wang;Chao Huang;Huaicheng Yan","doi":"10.1109/JSYST.2024.3391766","DOIUrl":"10.1109/JSYST.2024.3391766","url":null,"abstract":"In this article, the optimal consensus problem for a class of nonlinear multiagent systems in discrete-time case is investigated under jump faults and false data injection (FDI) attacks. First, a general fault model with coefficients obeying a semi-Markov process is introduced into system dynamics. A joint state and fault observer based on the hidden semi-Markov model is designed to estimate both the agent's state and the fault signals. Sufficient conditions for the existence of observer gains are established by constructing the stochastic Lyapunov function with hidden mode, observed mode, and elapsed time dependencies. Based on the observed states, we reconstruct the local performance metric functions of agents and design a policy-value iteration algorithm to address the multiplayer game problem. Then, an neural network policy-value iteration approximation algorithm is proposed, which obtains an approximate Nash equilibrium solution of the multiplayer games. Further, a secure fault-tolerant optimal consensus controller with fault compensation and attack attenuation terms is designed to achieve optimal tracking control, and the stability of the neighbor tracking error system is rigorously demonstrated. Finally, illustrative example and comparison simulations are provided to verify the validity and applicability of the proposed results.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1402-1413"},"PeriodicalIF":4.0,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140832010","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 : 2024-04-30DOI: 10.1109/JSYST.2024.3390554
Zhiyu Huang;Zhichao Sheng;Ali A. Nasir;Hongwen Yu
A full-duplex unmanned aerial vehicle (UAV)-based communication network is investigated, where the UAV is dispatched to transmit information to multiple downlink users (DLUs) and receive signal from uplink users (ULUs) simultaneously in the existence of malicious jammers. Considering the limited battery power of the UAV and the quality of service required, 3-D trajectory, DLUs scheduling, ULUs scheduling, and uplink/downlink transmit power allocation are jointly optimized to maximize the energy efficiency of the network. However, the formulated optimization problem with high coupling variables and fractional objective function is nonconvex and therefore mathematically intractable. To address the problem, the BCD method is implemented to decompose the optimization problem into four independent subproblems. An iterative algorithm based on Dinkelbach's algorithm and successive convex approximation technique is developed to solve the problem efficiently. Numerical simulation results are presented to evaluate the performance of different schemes and demonstrate the advantages of the proposed algorithm.
{"title":"Energy Efficiency Maximization for UAV-Assisted Full-Duplex Communication in the Presence of Multiple Malicious Jammers","authors":"Zhiyu Huang;Zhichao Sheng;Ali A. Nasir;Hongwen Yu","doi":"10.1109/JSYST.2024.3390554","DOIUrl":"10.1109/JSYST.2024.3390554","url":null,"abstract":"A full-duplex unmanned aerial vehicle (UAV)-based communication network is investigated, where the UAV is dispatched to transmit information to multiple downlink users (DLUs) and receive signal from uplink users (ULUs) simultaneously in the existence of malicious jammers. Considering the limited battery power of the UAV and the quality of service required, 3-D trajectory, DLUs scheduling, ULUs scheduling, and uplink/downlink transmit power allocation are jointly optimized to maximize the energy efficiency of the network. However, the formulated optimization problem with high coupling variables and fractional objective function is nonconvex and therefore mathematically intractable. To address the problem, the BCD method is implemented to decompose the optimization problem into four independent subproblems. An iterative algorithm based on Dinkelbach's algorithm and successive convex approximation technique is developed to solve the problem efficiently. Numerical simulation results are presented to evaluate the performance of different schemes and demonstrate the advantages of the proposed algorithm.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1257-1268"},"PeriodicalIF":4.0,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140831984","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 : 2024-04-29DOI: 10.1109/JSYST.2024.3391811
Tianqing Zhou;Dong Qin;Xuefang Nie;Xuan Li;Nan Jiang;Chunguo Li
In this article, the orthogonal frequency-division multiple access (OFDMA) integrated with frequency spectrum (band) partitioning and equal bandwidth allocation is first introduced to mitigate the complicated, severe, and average network interferences in ultradense mobile edge computing (MEC) networks. Then, under such OFDMA, the system energy consumed by all users [mobile devices (MDs)] and base stations (BSs) is minimized to reduce the huge energy consumed by ultradense small BSs (SBSs) and prolong the standby time of MDs, jointly optimizing the spectrum partitioning factor, local and remote computation capacities, local power, and binary offloading decision. According to the coupling form of optimization parameters in the formulated problem, this problem is first cut into a joint power control and resource (frequency spectrum) partitioning (PCRP) subproblem, a joint user association, and a computation capacity optimization (UACCO) subproblem. Then, we try to design an effective iteration algorithm to attain the solutions to these problems using convex optimization methods. As for this algorithm, we give some detailed convergence, computation complexity, and simulation analyses. The simulation results show that it may achieve a guaranteed offloading performance and lower energy consumption than other existing algorithms.
{"title":"Joint Computation Offloading and Resource Optimization for Minimizing Network-Wide Energy Consumption in Ultradense MEC Networks","authors":"Tianqing Zhou;Dong Qin;Xuefang Nie;Xuan Li;Nan Jiang;Chunguo Li","doi":"10.1109/JSYST.2024.3391811","DOIUrl":"10.1109/JSYST.2024.3391811","url":null,"abstract":"In this article, the orthogonal frequency-division multiple access (OFDMA) integrated with frequency spectrum (band) partitioning and equal bandwidth allocation is first introduced to mitigate the complicated, severe, and average network interferences in ultradense mobile edge computing (MEC) networks. Then, under such OFDMA, the system energy consumed by all users [mobile devices (MDs)] and base stations (BSs) is minimized to reduce the huge energy consumed by ultradense small BSs (SBSs) and prolong the standby time of MDs, jointly optimizing the spectrum partitioning factor, local and remote computation capacities, local power, and binary offloading decision. According to the coupling form of optimization parameters in the formulated problem, this problem is first cut into a joint power control and resource (frequency spectrum) partitioning (PCRP) subproblem, a joint user association, and a computation capacity optimization (UACCO) subproblem. Then, we try to design an effective iteration algorithm to attain the solutions to these problems using convex optimization methods. As for this algorithm, we give some detailed convergence, computation complexity, and simulation analyses. The simulation results show that it may achieve a guaranteed offloading performance and lower energy consumption than other existing algorithms.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1115-1126"},"PeriodicalIF":4.0,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140831847","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}
The introduction of building information management (BIM) to enable the management and delivery of megaprojects has illuminated the importance of system integration (SI) to coordinate and bring together complex interdependent technical and organizational systems. SI can inform and address the emerging interdependencies with BIM processes and technologies in megaprojects. Thus, in this article, we extend the theorizing of SI and BIM for the management of megaprojects in the infrastructure sector. This process involves 1) conceptualizing the complementarity and compatibility of SI and BIM in the management of megaprojects, and 2) offering an integrative framework and model of SI and BIM. Finally, we discuss and highlight this twofold contribution and offer insights into future research.
引入建筑信息管理（BIM）以实现超大型项目的管理和交付，揭示了系统集成（SI）在协调和汇集复杂的相互依存的技术和组织系统方面的重要性。系统集成可以为超大型项目中的 BIM 流程和技术提供信息，并解决新出现的相互依存问题。因此，在本文中，我们将扩展 SI 和 BIM 的理论，用于基础设施领域的超大型项目管理。这一过程包括：1）将 SI 和 BIM 在巨型项目管理中的互补性和兼容性概念化；2）提供 SI 和 BIM 的整合框架和模型。最后，我们讨论并强调了这两方面的贡献，并对未来研究提出了见解。
{"title":"Complementarity and Compatibility of Systems Integration and Building Information Management","authors":"Mikela Chatzimichailidou;Tim Whitcher;Nikola Suzic","doi":"10.1109/JSYST.2024.3387064","DOIUrl":"10.1109/JSYST.2024.3387064","url":null,"abstract":"The introduction of building information management (BIM) to enable the management and delivery of megaprojects has illuminated the importance of system integration (SI) to coordinate and bring together complex interdependent technical and organizational systems. SI can inform and address the emerging interdependencies with BIM processes and technologies in megaprojects. Thus, in this article, we extend the theorizing of SI and BIM for the management of megaprojects in the infrastructure sector. This process involves 1) conceptualizing the complementarity and compatibility of SI and BIM in the management of megaprojects, and 2) offering an integrative framework and model of SI and BIM. Finally, we discuss and highlight this twofold contribution and offer insights into future research.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1198-1207"},"PeriodicalIF":4.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140806732","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 : 2024-04-17DOI: 10.1109/JSYST.2024.3384372
Daotong Zhang;Peng Shi;Ramesh K. Agarwal;Levente Kovács
This article presents a novel model predictive control (MPC) framework with an integrated disturbance observer for cyber-physical systems (CPSs) under denial-of-service (DoS) attacks. Uniquely incorporating a memory module, our MPC approach is tailored to maintain stability and security in CPS during DoS attacks, which typically disrupt communication and degrade performance. Our method stands out by addressing time-varying system uncertainties through the disturbance observer, enhancing robustness under these attack conditions. The effectiveness of our approach is validated through numerical simulations, hardware-in-the-loop experiments, and comparative analyses using an omnidirectional robot, highlighting its practical applicability and advancement over existing methods.
本文介绍了一种新颖的模型预测控制（MPC）框架，该框架集成了干扰观测器，可用于拒绝服务（DoS）攻击下的网络物理系统（CPS）。我们的 MPC 方法独特地集成了内存模块，专门用于在 DoS 攻击期间保持 CPS 的稳定性和安全性，DoS 攻击通常会破坏通信并降低性能。我们的方法通过干扰观测器解决了时变系统不确定性问题，增强了在这些攻击条件下的鲁棒性。我们通过数值模拟、硬件在环实验以及使用全向机器人进行比较分析，验证了我们方法的有效性，突出了其实际适用性以及与现有方法相比的先进性。
{"title":"Reference Tracking MPC for Cyber-Physical Systems Under Denial-of-Service Attacks: An Omnidirectional Robot Application","authors":"Daotong Zhang;Peng Shi;Ramesh K. Agarwal;Levente Kovács","doi":"10.1109/JSYST.2024.3384372","DOIUrl":"10.1109/JSYST.2024.3384372","url":null,"abstract":"This article presents a novel model predictive control (MPC) framework with an integrated disturbance observer for cyber-physical systems (CPSs) under denial-of-service (DoS) attacks. Uniquely incorporating a memory module, our MPC approach is tailored to maintain stability and security in CPS during DoS attacks, which typically disrupt communication and degrade performance. Our method stands out by addressing time-varying system uncertainties through the disturbance observer, enhancing robustness under these attack conditions. The effectiveness of our approach is validated through numerical simulations, hardware-in-the-loop experiments, and comparative analyses using an omnidirectional robot, highlighting its practical applicability and advancement over existing methods.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1248-1256"},"PeriodicalIF":4.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140804840","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 : 2024-04-16DOI: 10.1109/JSYST.2024.3381304
Hao Zhang;Jie Yao;Zhuping Wang;Sheng Gao;Huaicheng Yan
This article studies the optimal distributed denial-of-service attack strategy for cyber–physical systems with multiple attackers and multiple defenders. An advanced attack strategy is proposed to cause the great damage to system in a multiattacker–defender form. First, a novel model of signal-to-interference-to-noise ratio for the multiattacker and multidefender is built. Taking the energy constraints into consideration, the objective of defenders is to minimize the system performance, while the attackers tend to deteriorate it by emitting interference energy. Thus, the optimal channel selection and optimal energy allocation strategies are proposed to answer which channel both of them should choose and how much power both of them should allocate to each channel in a finite time horizon. Second, a two-player zero-sum matrix game is formulated to solve the optimal problem by linear programming and obtain the Nash equilibrium. When the channel parameters are time-varying, a dynamic optimal channel selection problem is considered and a multistage game algorithm is proposed to find the Nash equilibrium. In addition, the designed optimal strategies of both players are demonstrated and analyzed. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed approach.
{"title":"Optimal DDoS Attack Strategy for Cyber–Physical Systems: A Multiattacker–Defender Game","authors":"Hao Zhang;Jie Yao;Zhuping Wang;Sheng Gao;Huaicheng Yan","doi":"10.1109/JSYST.2024.3381304","DOIUrl":"10.1109/JSYST.2024.3381304","url":null,"abstract":"This article studies the optimal distributed denial-of-service attack strategy for cyber–physical systems with multiple attackers and multiple defenders. An advanced attack strategy is proposed to cause the great damage to system in a multiattacker–defender form. First, a novel model of signal-to-interference-to-noise ratio for the multiattacker and multidefender is built. Taking the energy constraints into consideration, the objective of defenders is to minimize the system performance, while the attackers tend to deteriorate it by emitting interference energy. Thus, the optimal channel selection and optimal energy allocation strategies are proposed to answer which channel both of them should choose and how much power both of them should allocate to each channel in a finite time horizon. Second, a two-player zero-sum matrix game is formulated to solve the optimal problem by linear programming and obtain the Nash equilibrium. When the channel parameters are time-varying, a dynamic optimal channel selection problem is considered and a multistage game algorithm is proposed to find the Nash equilibrium. In addition, the designed optimal strategies of both players are demonstrated and analyzed. Finally, a numerical simulation is provided to illustrate the effectiveness of the proposed approach.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"929-940"},"PeriodicalIF":4.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615033","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 : 2024-04-15DOI: 10.1109/JSYST.2024.3378699
Long Ma;Yuan Zhang
Internet of Things (IoT) devices frequently encounter various challenges, including limited power, spectrum, and memory resources, as well as harsh environments conditions. Therefore, the development of an efficient transmission scheme is crucial for ensuring reliable and secure communication in IoT networks. In this article, an adaptive semi-grant-free (SGF) transmission scheme is proposed for reliable uplink nonorthogonal multiple access systems with enhanced security, in which a ratio-based user scheduling criterion and a hybrid successive interference cancellation technique are employed to suppress the activity of untrusted nodes while ensuring reliable transmission. To evaluate the superiority of the adaptive scheme, a conventional static transmission scheme and a worst-case eavesdropping scenario are used as benchmarks. Simulation results show that the adaptive scheme outperforms the conventional schemes in terms of outage and intercept probability. In addition, the closed-form results of grant-based user's and grant-free user's outage probability and untrusted node's intercept probability are derived. Compared to existing literature, this work provides a comprehensive view of security-reliability tradeoff analysis of SGF transmissions.
{"title":"Security-Reliability Analysis for Adaptive Semi-Grant-Free Transmissions","authors":"Long Ma;Yuan Zhang","doi":"10.1109/JSYST.2024.3378699","DOIUrl":"10.1109/JSYST.2024.3378699","url":null,"abstract":"Internet of Things (IoT) devices frequently encounter various challenges, including limited power, spectrum, and memory resources, as well as harsh environments conditions. Therefore, the development of an efficient transmission scheme is crucial for ensuring reliable and secure communication in IoT networks. In this article, an adaptive semi-grant-free (SGF) transmission scheme is proposed for reliable uplink nonorthogonal multiple access systems with enhanced security, in which a ratio-based user scheduling criterion and a hybrid successive interference cancellation technique are employed to suppress the activity of untrusted nodes while ensuring reliable transmission. To evaluate the superiority of the adaptive scheme, a conventional static transmission scheme and a worst-case eavesdropping scenario are used as benchmarks. Simulation results show that the adaptive scheme outperforms the conventional schemes in terms of outage and intercept probability. In addition, the closed-form results of grant-based user's and grant-free user's outage probability and untrusted node's intercept probability are derived. Compared to existing literature, this work provides a comprehensive view of security-reliability tradeoff analysis of SGF transmissions.","PeriodicalId":55017,"journal":{"name":"IEEE Systems Journal","volume":"18 2","pages":"1080-1091"},"PeriodicalIF":4.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582673","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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