Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant ...Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI.展开更多
The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensur...The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensure passengers have a satisfactory experience throughout their journey.Installing base stations along urban environments can improve coverage but can dramatically reduce the experience of users due to interference.In particular,when a user with a mobile phone is a passenger in a high speed train traversing between urban centres,the coverage and the 5G resources in general need to be adequate not to diminish her experience of the service.The utilization of macro,pico,and femto cells may optimize the utilization of 5G resources.In this paper,a Genetic Algorithm(GA)-based approach to address the challenges of 5G network planning for 5G-R services is presented.The network is divided into three cell types,macro,pico,and femto cells—and the optimization process is designed to achieve a balance between key objectives:providing comprehensive coverage,minimizing interference,and maximizing energy efficiency.The study focuses on environments with high user density,such as high-speed trains,where reliable and high-quality connectivity is critical.Through simulations,the effectiveness of the GA-driven framework in optimizing coverage and performance in such scenarios is demonstrated.The algorithm is compared with the Particle Swarm Optimisation(PSO)and the Simulated Annealing(SA)methods and interesting insights emerged.The GA offers a strong balance between coverage and efficiency,achieving significantly higher coverage than PSO while maintaining competitive energy efficiency and interference levels.Its steady fitness improvement and adaptability make it well-suited for scenarios where wide coverage is a priority alongside acceptable performance trade-offs.展开更多
The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G en...The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.展开更多
The work proposes a distributed Kalman filtering(KF)algorithm to track a time-varying unknown signal process for a stochastic regression model over network systems in a cooperative way.We provide the stability analysi...The work proposes a distributed Kalman filtering(KF)algorithm to track a time-varying unknown signal process for a stochastic regression model over network systems in a cooperative way.We provide the stability analysis of the proposed distributed KF algorithm without independent and stationary signal assumptions,which implies that the theoretical results are able to be applied to stochastic feedback systems.Note that the main difficulty of stability analysis lies in analyzing the properties of the product of non-independent and non-stationary random matrices involved in the error equation.We employ analysis techniques such as stochastic Lyapunov function,stability theory of stochastic systems,and algebraic graph theory to deal with the above issue.The stochastic spatio-temporal cooperative information condition shows the cooperative property of multiple sensors that even though any local sensor cannot track the time-varying unknown signal,the distributed KF algorithm can be utilized to finish the filtering task in a cooperative way.At last,we illustrate the property of the proposed distributed KF algorithm by a simulation example.展开更多
电转气(power to gas, P2G)技术可将电能转化为天然气,在实现综合能源系统低碳经济调度方面发挥着重要作用。为解决P2G过程中O_(2)未充分利用的问题并进一步降低碳排放,文中提出一种考虑P2G富氧改进和混合光能利用的低碳综合能源系统。...电转气(power to gas, P2G)技术可将电能转化为天然气,在实现综合能源系统低碳经济调度方面发挥着重要作用。为解决P2G过程中O_(2)未充分利用的问题并进一步降低碳排放,文中提出一种考虑P2G富氧改进和混合光能利用的低碳综合能源系统。首先,利用P2G生产的O_(2)与CO_(2)混合作为助燃气体,P2G利用碳捕集的CO_(2)制造天然气供给燃气机组使用;然后,因锅炉效率受O_(2)浓度影响,通过遗传算法和Gurobi求解器的联合算法得出耗氧设备各时段的最优供氧状态;最后,通过混合光能利用提升光能效率,以减少化石能源使用。将富氧燃烧和混合光能利用引入综合能源系统,构建考虑P2G富氧改进和混合光能利用的综合能源系统低碳经济运行模型,并设置场景进行对比验证。仿真结果显示,对比富氧改进前CO_(2)排放量降低75.83%,对比无混合光能场景光能总出力增加9.79%,表明所提模型可有效降低碳排放和运行成本。展开更多
在“30*60”目标背景下,低碳政策和低碳技术成为能源系统节能与减排新的出发点和落脚点,电转气(power to gas,P2G)作为一种新型能源转换方式为消纳新能源和降低碳排放提供了新的途径。文中首先将电转气精细化为电解制氢和氢气制甲烷两...在“30*60”目标背景下,低碳政策和低碳技术成为能源系统节能与减排新的出发点和落脚点,电转气(power to gas,P2G)作为一种新型能源转换方式为消纳新能源和降低碳排放提供了新的途径。文中首先将电转气精细化为电解制氢和氢气制甲烷两个阶段,构建两阶段P2G、碳捕集、微型燃气轮机掺氢、燃气锅炉掺氢相互协同的运行框架。其次考虑P2G反应热的利用,以及能源运营商和能源用户两主体阶梯碳交易机制对系统碳排放的约束。最后建立考虑两阶段P2G和燃气掺氢的综合能源系统日前双层优化调度模型,上层模型以能源商运营收益最大为目标,下层模型以能源用户的用能效用与购能成本之差最大为目标。通过不同场景下的仿真,验证了所提模型的有效性,并分析了掺氢比和碳交易基价对综合能源系统低碳经济的影响。展开更多
基金supported by the National Key R&D Program of China(Grant No.2022YFA1005000)the National Natural Science Foundation of China(Grant No.62025110 and 62101308).
文摘Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI.
文摘The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensure passengers have a satisfactory experience throughout their journey.Installing base stations along urban environments can improve coverage but can dramatically reduce the experience of users due to interference.In particular,when a user with a mobile phone is a passenger in a high speed train traversing between urban centres,the coverage and the 5G resources in general need to be adequate not to diminish her experience of the service.The utilization of macro,pico,and femto cells may optimize the utilization of 5G resources.In this paper,a Genetic Algorithm(GA)-based approach to address the challenges of 5G network planning for 5G-R services is presented.The network is divided into three cell types,macro,pico,and femto cells—and the optimization process is designed to achieve a balance between key objectives:providing comprehensive coverage,minimizing interference,and maximizing energy efficiency.The study focuses on environments with high user density,such as high-speed trains,where reliable and high-quality connectivity is critical.Through simulations,the effectiveness of the GA-driven framework in optimizing coverage and performance in such scenarios is demonstrated.The algorithm is compared with the Particle Swarm Optimisation(PSO)and the Simulated Annealing(SA)methods and interesting insights emerged.The GA offers a strong balance between coverage and efficiency,achieving significantly higher coverage than PSO while maintaining competitive energy efficiency and interference levels.Its steady fitness improvement and adaptability make it well-suited for scenarios where wide coverage is a priority alongside acceptable performance trade-offs.
文摘The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.
基金supported in part by Sichuan Science and Technology Program under Grant No.2025ZNSFSC151in part by the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No.XDA27030201+1 种基金the Natural Science Foundation of China under Grant No.U21B6001in part by the Natural Science Foundation of Tianjin under Grant No.24JCQNJC01930.
文摘The work proposes a distributed Kalman filtering(KF)algorithm to track a time-varying unknown signal process for a stochastic regression model over network systems in a cooperative way.We provide the stability analysis of the proposed distributed KF algorithm without independent and stationary signal assumptions,which implies that the theoretical results are able to be applied to stochastic feedback systems.Note that the main difficulty of stability analysis lies in analyzing the properties of the product of non-independent and non-stationary random matrices involved in the error equation.We employ analysis techniques such as stochastic Lyapunov function,stability theory of stochastic systems,and algebraic graph theory to deal with the above issue.The stochastic spatio-temporal cooperative information condition shows the cooperative property of multiple sensors that even though any local sensor cannot track the time-varying unknown signal,the distributed KF algorithm can be utilized to finish the filtering task in a cooperative way.At last,we illustrate the property of the proposed distributed KF algorithm by a simulation example.
文摘电转气(power to gas, P2G)技术可将电能转化为天然气,在实现综合能源系统低碳经济调度方面发挥着重要作用。为解决P2G过程中O_(2)未充分利用的问题并进一步降低碳排放,文中提出一种考虑P2G富氧改进和混合光能利用的低碳综合能源系统。首先,利用P2G生产的O_(2)与CO_(2)混合作为助燃气体,P2G利用碳捕集的CO_(2)制造天然气供给燃气机组使用;然后,因锅炉效率受O_(2)浓度影响,通过遗传算法和Gurobi求解器的联合算法得出耗氧设备各时段的最优供氧状态;最后,通过混合光能利用提升光能效率,以减少化石能源使用。将富氧燃烧和混合光能利用引入综合能源系统,构建考虑P2G富氧改进和混合光能利用的综合能源系统低碳经济运行模型,并设置场景进行对比验证。仿真结果显示,对比富氧改进前CO_(2)排放量降低75.83%,对比无混合光能场景光能总出力增加9.79%,表明所提模型可有效降低碳排放和运行成本。
文摘在“30*60”目标背景下,低碳政策和低碳技术成为能源系统节能与减排新的出发点和落脚点,电转气(power to gas,P2G)作为一种新型能源转换方式为消纳新能源和降低碳排放提供了新的途径。文中首先将电转气精细化为电解制氢和氢气制甲烷两个阶段,构建两阶段P2G、碳捕集、微型燃气轮机掺氢、燃气锅炉掺氢相互协同的运行框架。其次考虑P2G反应热的利用,以及能源运营商和能源用户两主体阶梯碳交易机制对系统碳排放的约束。最后建立考虑两阶段P2G和燃气掺氢的综合能源系统日前双层优化调度模型,上层模型以能源商运营收益最大为目标,下层模型以能源用户的用能效用与购能成本之差最大为目标。通过不同场景下的仿真,验证了所提模型的有效性,并分析了掺氢比和碳交易基价对综合能源系统低碳经济的影响。
