In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving...In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm（IAMQER） is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints.展开更多
针对传统轨道角动量(Orbital Angular Momentum,OAM)通信系统难以在视距信道受阻塞的非视距环境中正常工作以及无法有效保障多用户的服务质量(Quality of Service,QoS)需求问题,文中基于智能反射表面辅助技术将多用户的非视距信道转化...针对传统轨道角动量(Orbital Angular Momentum,OAM)通信系统难以在视距信道受阻塞的非视距环境中正常工作以及无法有效保障多用户的服务质量(Quality of Service,QoS)需求问题,文中基于智能反射表面辅助技术将多用户的非视距信道转化为等效的视距信道,并在此场景下提出基于太赫兹多用户OAM正交频分多址系统下行资源优化方法。基于双层迭代资源分配算法将非凸联合优化的求解分解成外部和内部两个优化流程,基于交替优化和凸优化理论逐一求解4个核心子问题,实现各用户QoS差异化保障下的系统容量最大化。仿真结果表明,所提方法在通信资源充足时对各用户的QoS需求保障率为100%。在反射单元数量为768时,所提系统比传统OAM系统的系统容量平均提高了19.1%,并且误码率更低。在用户数量为3、信噪比为20 dB时,相较于基于相位补偿的MU(Multiuser)-OAM系统,所提系统的误码率下降了40.5%。展开更多
随着5G技术的广泛应用,用户通信需求和应用场景的日益复杂,对差异化的服务质量(QoS,Quality of Service)有了愈发严苛的要求。本研究提出了一种基于5G QoS标识(5G QoS Identifier,5QI)与无线频率选择优先级(RAT Frequency Selection Pri...随着5G技术的广泛应用,用户通信需求和应用场景的日益复杂,对差异化的服务质量(QoS,Quality of Service)有了愈发严苛的要求。本研究提出了一种基于5G QoS标识(5G QoS Identifier,5QI)与无线频率选择优先级(RAT Frequency Selection Priority,RFSP)联合的动态调度策略,通过改进的加权比例公平(Weighted Proportional Fair,WPF)调度算法融合接入管理-策略控制功能(Access Management-Policy Control Function,AM-PCF)动态策略机制,实现用户级与业务级的资源灵活分配。设计分层分级网络保障模型,为不同用户分配差异化的5QI和RFSP调度权重。测试结果表明,保障用户平均速率、视频播放质量等关键性能均优于普通用户,验证了差异化调度策略在复杂场景下的有效性。展开更多
An efficient QoS routing algorithm was proposed for multiple constrained path selection. Making use of efficient pruning policy, the algorithm reduces greatly the size of search space and the computing time. Although ...An efficient QoS routing algorithm was proposed for multiple constrained path selection. Making use of efficient pruning policy, the algorithm reduces greatly the size of search space and the computing time. Although the proposed algorithm has exponential time complexity in the worst case, it can get the running results quickly in practical application. When the scale of network increases, the algorithm can efficiently control the size of search space by constraint conditions and prior queue. The results of simulation show that successful request ratio ( r ) of efficient algorithm for multi-constrained optimal path (EAMCOP) is better than that of heuristic algorithm for multi-constrained optimal path (H-MCOP), but average computing time ( t ) of EAMCOP is far less than that of H-MCOP. And it can be seen that the computing time of EAMCOP is only one fourth of that of H-MCOP in Advanced Research Projects Agency Network (ARPANet) topology.展开更多
Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristi...Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem.However,existing solutions,most of which suffered either from excessive computational complexities or from low performance,were proposed only for wired networks and cannot be used directly in wireless mesh networks.In this paper,we propose a novel routing scheme based on mean field annealing(MFA-RS)to solve this problem.MFA-RS first uses a function of two QoS parameters,wireless link’s delay and transmission success rate as the cost function,and then seeks to find a feasible path by MFA.Because MFA-RS uses a set of deterministic equations to replace the stochastic process in simulated annealing(SA)and uses saddle point approximation in the calculation of the stationary probability distribution at equilibrium,the convergence time is much less than the routing scheme based on SA(SA-RS).Simulation results demonstrate that MFA-RS is an effective algorithm and is very fit for WMNs.展开更多
现有研究在多QoS(quality of service)调度问题中,由于仅依赖即时奖励反馈机制,在资源受限的场景下处理时延敏感数据和具有连续传输需求的媒体数据时,存在可扩展性差和资源浪费的问题。为此,提出了一种基于奖励回溯的DQN(reward backtra...现有研究在多QoS(quality of service)调度问题中,由于仅依赖即时奖励反馈机制,在资源受限的场景下处理时延敏感数据和具有连续传输需求的媒体数据时,存在可扩展性差和资源浪费的问题。为此,提出了一种基于奖励回溯的DQN(reward backtracking based deep Q-network,RB-DQN)算法。该算法通过未来时刻的交互来回溯调整当前状态的策略评估,以更加有效地识别并解决因不合理调度策略导致的丢包。同时,设计了一种时延-吞吐均衡度量(latency throughput trade-off,LTT)指标,该指标综合考虑了时延敏感数据和媒体类型数据的业务需求,并可通过权重调整来突出不同的侧重点。大量仿真结果表明,与其他调度策略相比,所提算法能够有效降低时延敏感数据的延迟和抖动,同时确保媒体类型数据的流畅性与稳定性。展开更多
Wireless sensor network(WSN)technologies have advanced significantly in recent years.With in WSNs,machine learning algorithms are crucial in selecting cluster heads(CHs)based on various quality of service(QoS)metrics....Wireless sensor network(WSN)technologies have advanced significantly in recent years.With in WSNs,machine learning algorithms are crucial in selecting cluster heads(CHs)based on various quality of service(QoS)metrics.This paper proposes a new clustering routing protocol employing the Traveling Salesman Problem(TSP)to locate the optimal path traversed by the Mobile Data Collector(MDC),in terms of energy and QoS efficiency.To bemore specific,to minimize energy consumption in the CH election stage,we have developed the M-T protocol using the K-Means and the grid clustering algorithms.In addition,to improve the transmission phase of the Low Energy Adaptive Clustering-Grid-KMeans(LEACH-G-K)protocol,the MDC is employed as an intermediary between the CH and the sink to improve the wireless sensor network(WSN)QoS.The results of the experiment demonstrate that the M-T protocol enhances various Low Energy Adaptive Clustering protocol(LEACH)improvements such as the LEACH-G-K,LEACH-C,Threshold sensitive Energy Efficient Sensor Networks(TEEN),MDC maximum residual energy leach protocol.展开更多
为了解决现有路由算法无法学习历史路由决策经验导致的网络负载不均衡问题,将强化学习技术引入软件定义网络(Software Defined Network,SDN)的服务质量(Quality of Service,QoS)路由问题,提出一种基于强化学习的多业务智能QoS路由方法MD...为了解决现有路由算法无法学习历史路由决策经验导致的网络负载不均衡问题,将强化学习技术引入软件定义网络(Software Defined Network,SDN)的服务质量(Quality of Service,QoS)路由问题,提出一种基于强化学习的多业务智能QoS路由方法MDQN(Multi-service QoS routing method based on DeepQ Network)。该方法部署在SDN控制器中,能学习历史决策经验,并在网络状态发生变化时及时调整路径。通过在SDN中部署该方法,有效平衡了网络负载,增加了网络的吞吐量,为SDN中的QoS路由问题提供了一种有效的解决方案。展开更多
Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To sa...Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.展开更多
基金supported by the National Natural Science Foundation of China(61101107)the Beijing Higher Education Young Elite Teacher Project
文摘In order to establish a route supporting multi-constrained quality of service（QoS）, increase network throughput and reduce network energy consumption, an improved ant colony-based multi-constrained QoS energy-saving routing algorithm（IAMQER） is proposed. The ant colony algorithm, as one of the available heuristic algorithms, is used to find the optimal route from source node to destination node. The proposed IAMQER algorithm, which is based on the analysis of local node information such as node queue length, node forwarding number of data packets and node residual energy, balances the relationship between the network throughput and the energy consumption, thus improving the performance of network in multi-constrained QoS routing. Simulation results show that this IAMQER algorithm can find the QoS route that reduce average energy consumption and improves network packet delivery ratio under the end-to-end delay and packet loss ratio constraints.
文摘随着5G技术的广泛应用,用户通信需求和应用场景的日益复杂,对差异化的服务质量(QoS,Quality of Service)有了愈发严苛的要求。本研究提出了一种基于5G QoS标识(5G QoS Identifier,5QI)与无线频率选择优先级(RAT Frequency Selection Priority,RFSP)联合的动态调度策略,通过改进的加权比例公平(Weighted Proportional Fair,WPF)调度算法融合接入管理-策略控制功能(Access Management-Policy Control Function,AM-PCF)动态策略机制,实现用户级与业务级的资源灵活分配。设计分层分级网络保障模型,为不同用户分配差异化的5QI和RFSP调度权重。测试结果表明,保障用户平均速率、视频播放质量等关键性能均优于普通用户,验证了差异化调度策略在复杂场景下的有效性。
文摘An efficient QoS routing algorithm was proposed for multiple constrained path selection. Making use of efficient pruning policy, the algorithm reduces greatly the size of search space and the computing time. Although the proposed algorithm has exponential time complexity in the worst case, it can get the running results quickly in practical application. When the scale of network increases, the algorithm can efficiently control the size of search space by constraint conditions and prior queue. The results of simulation show that successful request ratio ( r ) of efficient algorithm for multi-constrained optimal path (EAMCOP) is better than that of heuristic algorithm for multi-constrained optimal path (H-MCOP), but average computing time ( t ) of EAMCOP is far less than that of H-MCOP. And it can be seen that the computing time of EAMCOP is only one fourth of that of H-MCOP in Advanced Research Projects Agency Network (ARPANet) topology.
基金supported by the National Natural Science Foundation of China(Grant Nos.61002016 and 60702081)the Natural Science Foundation of Zhejiang Province of China(No.Y107309)+2 种基金the University Scientific Research Program of the Education Department of Zhejiang Province of China(No.20070364)the Scientific Research Foundation of Zhejiang Sci-Tech University(Nos.0704698 and 0704697)the Xinmiao Talent Project of Zhejiang Province(2009).
文摘Multi-constrained quality of service(QoS)routing aims at finding an optimal path that satisfies a set of QoS parameters,as an NP complete problem,which is also a big challenge for wireless mesh networks(WMNs).Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this problem.However,existing solutions,most of which suffered either from excessive computational complexities or from low performance,were proposed only for wired networks and cannot be used directly in wireless mesh networks.In this paper,we propose a novel routing scheme based on mean field annealing(MFA-RS)to solve this problem.MFA-RS first uses a function of two QoS parameters,wireless link’s delay and transmission success rate as the cost function,and then seeks to find a feasible path by MFA.Because MFA-RS uses a set of deterministic equations to replace the stochastic process in simulated annealing(SA)and uses saddle point approximation in the calculation of the stationary probability distribution at equilibrium,the convergence time is much less than the routing scheme based on SA(SA-RS).Simulation results demonstrate that MFA-RS is an effective algorithm and is very fit for WMNs.
文摘现有研究在多QoS(quality of service)调度问题中,由于仅依赖即时奖励反馈机制,在资源受限的场景下处理时延敏感数据和具有连续传输需求的媒体数据时,存在可扩展性差和资源浪费的问题。为此,提出了一种基于奖励回溯的DQN(reward backtracking based deep Q-network,RB-DQN)算法。该算法通过未来时刻的交互来回溯调整当前状态的策略评估,以更加有效地识别并解决因不合理调度策略导致的丢包。同时,设计了一种时延-吞吐均衡度量(latency throughput trade-off,LTT)指标,该指标综合考虑了时延敏感数据和媒体类型数据的业务需求,并可通过权重调整来突出不同的侧重点。大量仿真结果表明,与其他调度策略相比,所提算法能够有效降低时延敏感数据的延迟和抖动,同时确保媒体类型数据的流畅性与稳定性。
基金supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2023S1A5C2A07096111).
文摘Wireless sensor network(WSN)technologies have advanced significantly in recent years.With in WSNs,machine learning algorithms are crucial in selecting cluster heads(CHs)based on various quality of service(QoS)metrics.This paper proposes a new clustering routing protocol employing the Traveling Salesman Problem(TSP)to locate the optimal path traversed by the Mobile Data Collector(MDC),in terms of energy and QoS efficiency.To bemore specific,to minimize energy consumption in the CH election stage,we have developed the M-T protocol using the K-Means and the grid clustering algorithms.In addition,to improve the transmission phase of the Low Energy Adaptive Clustering-Grid-KMeans(LEACH-G-K)protocol,the MDC is employed as an intermediary between the CH and the sink to improve the wireless sensor network(WSN)QoS.The results of the experiment demonstrate that the M-T protocol enhances various Low Energy Adaptive Clustering protocol(LEACH)improvements such as the LEACH-G-K,LEACH-C,Threshold sensitive Energy Efficient Sensor Networks(TEEN),MDC maximum residual energy leach protocol.
文摘为了解决现有路由算法无法学习历史路由决策经验导致的网络负载不均衡问题,将强化学习技术引入软件定义网络(Software Defined Network,SDN)的服务质量(Quality of Service,QoS)路由问题,提出一种基于强化学习的多业务智能QoS路由方法MDQN(Multi-service QoS routing method based on DeepQ Network)。该方法部署在SDN控制器中,能学习历史决策经验,并在网络状态发生变化时及时调整路径。通过在SDN中部署该方法,有效平衡了网络负载,增加了网络的吞吐量,为SDN中的QoS路由问题提供了一种有效的解决方案。
基金National Key Research and Development Program(2021YFB2900604)。
文摘Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.
