The radial basis function （RBF）, a kind of neural networks algorithm, is adopted to select clusterheads. It has many advantages such as simple parallel distributed computation, distributed storage, and fast learning...The radial basis function （RBF）, a kind of neural networks algorithm, is adopted to select clusterheads. It has many advantages such as simple parallel distributed computation, distributed storage, and fast learning. Four factors related to a node becoming a cluster-head are drawn by analysis, which are energy （ energy available in each node）, number （the number of neighboring nodes）, centrality （ a value to classify the nodes based on the proximity how central the node is to the cluster）, and location （the distance between the base station and the node）. The factors are as input variables of neural networks and the output variable is suitability that is the degree of a node becoming a cluster head. A group of cluster-heads are selected according to the size of network. Then the base station broadcasts a message containing the list of cluster-heads＇ IDs to all nodes. After that, each cluster-head announces its new status to all its neighbors and sets up a new cluster. If a node around it receives the message, it registers itself to be a member of the cluster. After identifying all the members, the cluster-head manages them and carries out data aggregation in each cluster. Thus data flowing in the network decreases and energy consumption of nodes decreases accordingly. Experimental results show that, compared with other algorithms, the proposed algorithm can significantly increase the lifetime of the sensor network.展开更多
In the target tracking, the nodes aggregate their observations of the directions of arrival of the target. The network then uses an extended Kalman filter （EKF） to combine the measurements from multiple snapshots to...In the target tracking, the nodes aggregate their observations of the directions of arrival of the target. The network then uses an extended Kalman filter （EKF） to combine the measurements from multiple snapshots to track the target. In order to rapidly select the best subset of nodes to localize the target with the minimum mean square position error and low power consumption, this paper proposes a simple algorithm, which uses the location information of the target and the network. The lower botmd of localization error is utilized according to the distances between the target and the selected active nodes. Furthermore, the direction likelihoods of the active nodes is predicted by way of the node/target bearing distributing relationships.展开更多
Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make ...Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make the network structurally controllable. Different from the works in complex network field where structural controllability is often used to explore the emergence properties of complex networks at a macro level,in this paper, we investigate it for control design purpose at the application level and focus on describing and obtaining the solution space for all selections of driver nodes to guarantee structural controllability. In accord with practical applications,we define the complete selection rule set as the solution space which is composed of a series of selection rules expressed by intuitive algebraic forms. It explicitly indicates which nodes must be controlled and how many nodes need to be controlled in a node set and thus is particularly helpful for freely selecting driver nodes. Based on two algebraic criteria of structural controllability, we separately develop an input-connectivity algorithm and a relevancy algorithm to deduce selection rules for driver nodes. In order to reduce the computational complexity,we propose a pretreatment algorithm to reduce the scale of network's structural matrix efficiently, and a rearrangement algorithm to partition the matrix into several smaller ones. A general procedure is proposed to get the complete selection rule set for driver nodes which guarantee network's structural controllability. Simulation tests with efficiency analysis of the proposed algorithms are given and the result of applying the proposed procedure to some real networks is also shown, and these all indicate the validity of the proposed procedure.展开更多
In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioni...In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioning over the past several years.However,due to weak signals,multipath or non-line-of-sight signal propagation,accurately and efficiently localizing targets in harsh indoor environments re-mains a challenging problem.To improve the perfor-mance in harsh environment with insufficient anchors,cooperative localization has emerged.In this paper,a novel cooperative localization algorithm,named area optimization and node selection based sum-product al-gorithm over a wireless network(AN-SPAWN),is de-scribed and analyzed.To alleviate the high compu-tational complexity and build optimized cooperative cluster,a node selection method is designed for the cooperative localization algorithm.Numerical experi-ment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional cooperative localization algo-rithms in the harsh indoor environments.展开更多
This research presents a reputation-based blockchain consensus mechanism called Proof of Intelligent Reputation(PoIR)as an alternative to traditional Proof of Work(PoW).PoIR addresses the limitations of existing reput...This research presents a reputation-based blockchain consensus mechanism called Proof of Intelligent Reputation(PoIR)as an alternative to traditional Proof of Work(PoW).PoIR addresses the limitations of existing reputationbased consensus mechanisms by proposing a more decentralized and fair node selection process.The proposed PoIR consensus combines Bidirectional Long Short-Term Memory(BiLSTM)with the Network Entity Reputation Database(NERD)to generate reputation scores for network entities and select authoritative nodes.NERD records network entity profiles based on various sources,i.e.,Warden,Blacklists,DShield,AlienVault Open Threat Exchange(OTX),and MISP(Malware Information Sharing Platform).It summarizes these profile records into a reputation score value.The PoIR consensus mechanism utilizes these reputation scores to select authoritative nodes.The evaluation demonstrates that PoIR exhibits higher centralization resistance than PoS and PoW.Authoritative nodes were selected fairly during the 1000-block proposal round,ensuring a more decentralized blockchain ecosystem.In contrast,malicious nodes successfully monopolized 58%and 32%of transaction processes in PoS and PoW,respectively,but failed to do so in PoIR.The findings also indicate that PoIR offers efficient transaction times of 12 s,outperforms reputation-based consensus such as PoW,and is comparable to reputation-based consensus such as PoS.Furthermore,the model evaluation shows that BiLSTM outperforms other Recurrent Neural Network models,i.e.,BiGRU(Bidirectional Gated Recurrent Unit),UniLSTM(Unidirectional Long Short-Term Memory),and UniGRU(Unidirectional Gated Recurrent Unit)with 0.022 Root Mean Squared Error(RMSE).This study concludes that the PoIR consensus mechanism is more resistant to centralization than PoS and PoW.Integrating BiLSTM and NERD enhances the fairness and efficiency of blockchain applications.展开更多
Vehicular Ad hoc Networks (VANETs) which is a special form of Mobile Ad hoc Networks (MANETs) has promising application prospects in the future. Due to the rapid changing of topology structure, how to find a route whi...Vehicular Ad hoc Networks (VANETs) which is a special form of Mobile Ad hoc Networks (MANETs) has promising application prospects in the future. Due to the rapid changing of topology structure, how to find a route which can guarantee Quality of Service (QoS) is an important issue in VANETs. This paper presents an improved Greedy Perimeter Stateless Routing (GPSR) protocol based on our proposed next-hop node selection mechanism. Firstly, we define the link reliability in two cases which take the movement direction angle between two vehicles into consideration. Then we propose a next-hop node selection mechanism based on a weighted function which consists of link reliability between the sender node and next-hop candidate node, distance between next-hop candidate node and the destination, movement direction angle of next-hop candidate node. At last, an improved GPSR protocol is proposed based on the next-hop node selection mechanism. Simulation results are presented to evaluate the performance of the improved GPSR protocol, which shows that the performance including packet delivery ratio and average end-to-end delay of the proposed protocol is better in some situations.展开更多
Objective:To explore core acupoints and acupoint selection principles in acupuncture and moxibustion for obesity,from syndrome differentiation prescriptions of the acupuncture-moxibustion therapy in 808 obesity prescr...Objective:To explore core acupoints and acupoint selection principles in acupuncture and moxibustion for obesity,from syndrome differentiation prescriptions of the acupuncture-moxibustion therapy in 808 obesity prescriptions,by using node centrality and cluster analysis methods in complex network.Methods:Firstly,an acupoint network model is established,and acupoint nodes are assessed and calculated in multiple aspects by introducing the node centrality analysis idea of complex network,to excavate core acupoint nodes.Secondly,a cluster analysis is carried out on acupoint network by the cluster algorithm Q-PSO for complex network,to investigate the acupoint combination principles.Results:Zusanli(足三里ST36),Tianshu(天枢ST25),Fenglong(丰隆ST40),Zhongwan(中脘CV12)and Qihai(气海CV6),etc.,were included into the core acupoint Sanyinjiao(三阴交SP6)community.Zhigou(支沟TE6),Neiting(内庭ST44),Shangjuxu(上巨虚ST37),and Pishu(脾俞BL20)etc.,were included into the core acupoint Yinlingquan(阴陵泉SP9)community.Baihuanshu(白环俞BL30)and Zhiyang(至阳GV9)were included into the core acupoint Dachangshu(大肠俞BL25)community.Biguan(髀关ST31)was a single core community.Among all the acupoint nodes,SP6,ST25,SP9,ST36,CV6,Quchi(曲池L111),and Guanyuan(关元CV4)were of high degree centrality and eigenvector centrality,directly reflecting their importance in acupoint selection prescriptions.Conclusion:The Q-PSO algorithm is characterized with high precision and high efficiency,etc.The core acupoints and their combination principles explored by this algorithm are in accordance with clinical experiences.展开更多
The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider at...The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm.展开更多
The deployment of Relay Nodes (RNs) in 4G LTE-A networks, mainly originating from the wireless backhaul link, provides an excellent network planning tool to enhance system performance. Better coordination between the ...The deployment of Relay Nodes (RNs) in 4G LTE-A networks, mainly originating from the wireless backhaul link, provides an excellent network planning tool to enhance system performance. Better coordination between the base station and relays to mitigate inter-cell interference becomes an important aspect of achieving the required system performance, not only in the single-cell scenario, but also in multi-cell scenarios. In this paper, we model and analyze two basic approaches for designing a 4G LTE-A tri-sectored cellular system. The approaches are based on Antenna Selection Sectored Relaying (ASSR) and Beam Selection Sectored Relaying (BSSR). The main purpose of the proposed schemes is to enhance system performance by improving the quality of the wireless relay backhaul link. In this technique, antenna selection takes into consideration Non-Line-Of-Sight (NLOS) communication, whereas BSSR considers the case of Line-Of-Sight (LOS) communication using heuristic beam forming approach. The resource allocation problem has also been investigated for relay based cooperative LTE-A trisectored cell in the downlink. The best possible location for relay node in the sector, power allocation and MIMO channel modeling is formulated as an optimization problem with the aim of maximizing the end to end link rate and the Signal to Interference plus Noise Ratio (SINR) of 4G LTE-A systems. Power allocation/optimization has been solved by means of the duality equation of the stationary Karush-Kuhn-Tucker (KKT) cond让ion and is used to derive optimal values for the beam forming vector on both the relay as well as the access link. The performance of the proposed scheme is verified through simulations carried out using MATLAB software. The simulation results show a significant improvement in the SINR, throughput capacity, and coverage area of the 4G LTE-A cell, while guaranteeing better quality of service.展开更多
将联邦学习应用于无线身体区域网络(wireless body area network,WBAN)可解决隐私数据保护问题,但仍然面临着全局模型准确率下降和能耗高的挑战。提出了面向智慧医疗的联邦学习系统模型,构建了各个WBAN节点参与联邦学习的能耗模型,分析...将联邦学习应用于无线身体区域网络(wireless body area network,WBAN)可解决隐私数据保护问题,但仍然面临着全局模型准确率下降和能耗高的挑战。提出了面向智慧医疗的联邦学习系统模型,构建了各个WBAN节点参与联邦学习的能耗模型,分析了其数据特性和资源特性。为保护本地数据隐私,避免直接获取原始数据信息,引入KL散度(Kullback-Leibler divergence)代表各节点的统计异构程度,通过信道增益、带宽等指标代表各节点的系统异构程度,提出了一种结合SAC(soft actor-critic)的联邦学习动态节点选择和资源分配方法。在每轮联邦学习训练开始前,SAC算法根据WBAN节点上传的数据特性和资源特性,动态选择参与训练的节点、分配本地计算资源和通信资源,解决WBAN节点的统计异构性和系统异构性导致的全局模型准确率下降和能耗高的问题。在CIFAR10、FashionMNIST、PathMNIST数据集上的实验表明,所提方法相比FedAvg、FAVOR、FLASH-RL,全局模型准确率至多提高20%、能耗降低了50%,并加快了全局模型收敛速度、减小了准确率波动,证明了所提方法的有效性。展开更多
基金The National Natural Science Foundation of China(No.60472053),the Natural Science Foundation of Jiangsu Province(No.BK2003055),the Specialized Research Fund for the Doctoral Pro-gram of Higher Education (No.20030286017).
文摘The radial basis function （RBF）, a kind of neural networks algorithm, is adopted to select clusterheads. It has many advantages such as simple parallel distributed computation, distributed storage, and fast learning. Four factors related to a node becoming a cluster-head are drawn by analysis, which are energy （ energy available in each node）, number （the number of neighboring nodes）, centrality （ a value to classify the nodes based on the proximity how central the node is to the cluster）, and location （the distance between the base station and the node）. The factors are as input variables of neural networks and the output variable is suitability that is the degree of a node becoming a cluster head. A group of cluster-heads are selected according to the size of network. Then the base station broadcasts a message containing the list of cluster-heads＇ IDs to all nodes. After that, each cluster-head announces its new status to all its neighbors and sets up a new cluster. If a node around it receives the message, it registers itself to be a member of the cluster. After identifying all the members, the cluster-head manages them and carries out data aggregation in each cluster. Thus data flowing in the network decreases and energy consumption of nodes decreases accordingly. Experimental results show that, compared with other algorithms, the proposed algorithm can significantly increase the lifetime of the sensor network.
基金National Natural Science Foundation of China(60532030)National Basic Research Program of China(973-61361)National Science Fund for Distinguished Young Scholars(60625102)
文摘In the target tracking, the nodes aggregate their observations of the directions of arrival of the target. The network then uses an extended Kalman filter （EKF） to combine the measurements from multiple snapshots to track the target. In order to rapidly select the best subset of nodes to localize the target with the minimum mean square position error and low power consumption, this paper proposes a simple algorithm, which uses the location information of the target and the network. The lower botmd of localization error is utilized according to the distances between the target and the selected active nodes. Furthermore, the direction likelihoods of the active nodes is predicted by way of the node/target bearing distributing relationships.
基金supported by the National Science Foundation of China(61333009,61473317,61433002,61521063,61590924,61673366)the National High Technology Research and Development Program of China(2015AA043102)
文摘Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make the network structurally controllable. Different from the works in complex network field where structural controllability is often used to explore the emergence properties of complex networks at a macro level,in this paper, we investigate it for control design purpose at the application level and focus on describing and obtaining the solution space for all selections of driver nodes to guarantee structural controllability. In accord with practical applications,we define the complete selection rule set as the solution space which is composed of a series of selection rules expressed by intuitive algebraic forms. It explicitly indicates which nodes must be controlled and how many nodes need to be controlled in a node set and thus is particularly helpful for freely selecting driver nodes. Based on two algebraic criteria of structural controllability, we separately develop an input-connectivity algorithm and a relevancy algorithm to deduce selection rules for driver nodes. In order to reduce the computational complexity,we propose a pretreatment algorithm to reduce the scale of network's structural matrix efficiently, and a rearrangement algorithm to partition the matrix into several smaller ones. A general procedure is proposed to get the complete selection rule set for driver nodes which guarantee network's structural controllability. Simulation tests with efficiency analysis of the proposed algorithms are given and the result of applying the proposed procedure to some real networks is also shown, and these all indicate the validity of the proposed procedure.
基金the Nation-alKey Research&Development Program of China un-der Grant No.2020YFC1511702 and Open Fund of IPOC(BUPT)No.IPOC2021ZT20.
文摘In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioning over the past several years.However,due to weak signals,multipath or non-line-of-sight signal propagation,accurately and efficiently localizing targets in harsh indoor environments re-mains a challenging problem.To improve the perfor-mance in harsh environment with insufficient anchors,cooperative localization has emerged.In this paper,a novel cooperative localization algorithm,named area optimization and node selection based sum-product al-gorithm over a wireless network(AN-SPAWN),is de-scribed and analyzed.To alleviate the high compu-tational complexity and build optimized cooperative cluster,a node selection method is designed for the cooperative localization algorithm.Numerical experi-ment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional cooperative localization algo-rithms in the harsh indoor environments.
基金funded by the Ministry of Education,Culture,Research,and Technology(Kemendikbudristek)of Indonesia under PDD Grant with Grant Number NKB1016/UN2.RST/HKP.05.00/2022.
文摘This research presents a reputation-based blockchain consensus mechanism called Proof of Intelligent Reputation(PoIR)as an alternative to traditional Proof of Work(PoW).PoIR addresses the limitations of existing reputationbased consensus mechanisms by proposing a more decentralized and fair node selection process.The proposed PoIR consensus combines Bidirectional Long Short-Term Memory(BiLSTM)with the Network Entity Reputation Database(NERD)to generate reputation scores for network entities and select authoritative nodes.NERD records network entity profiles based on various sources,i.e.,Warden,Blacklists,DShield,AlienVault Open Threat Exchange(OTX),and MISP(Malware Information Sharing Platform).It summarizes these profile records into a reputation score value.The PoIR consensus mechanism utilizes these reputation scores to select authoritative nodes.The evaluation demonstrates that PoIR exhibits higher centralization resistance than PoS and PoW.Authoritative nodes were selected fairly during the 1000-block proposal round,ensuring a more decentralized blockchain ecosystem.In contrast,malicious nodes successfully monopolized 58%and 32%of transaction processes in PoS and PoW,respectively,but failed to do so in PoIR.The findings also indicate that PoIR offers efficient transaction times of 12 s,outperforms reputation-based consensus such as PoW,and is comparable to reputation-based consensus such as PoS.Furthermore,the model evaluation shows that BiLSTM outperforms other Recurrent Neural Network models,i.e.,BiGRU(Bidirectional Gated Recurrent Unit),UniLSTM(Unidirectional Long Short-Term Memory),and UniGRU(Unidirectional Gated Recurrent Unit)with 0.022 Root Mean Squared Error(RMSE).This study concludes that the PoIR consensus mechanism is more resistant to centralization than PoS and PoW.Integrating BiLSTM and NERD enhances the fairness and efficiency of blockchain applications.
文摘Vehicular Ad hoc Networks (VANETs) which is a special form of Mobile Ad hoc Networks (MANETs) has promising application prospects in the future. Due to the rapid changing of topology structure, how to find a route which can guarantee Quality of Service (QoS) is an important issue in VANETs. This paper presents an improved Greedy Perimeter Stateless Routing (GPSR) protocol based on our proposed next-hop node selection mechanism. Firstly, we define the link reliability in two cases which take the movement direction angle between two vehicles into consideration. Then we propose a next-hop node selection mechanism based on a weighted function which consists of link reliability between the sender node and next-hop candidate node, distance between next-hop candidate node and the destination, movement direction angle of next-hop candidate node. At last, an improved GPSR protocol is proposed based on the next-hop node selection mechanism. Simulation results are presented to evaluate the performance of the improved GPSR protocol, which shows that the performance including packet delivery ratio and average end-to-end delay of the proposed protocol is better in some situations.
基金Supported by Hubei Health & Family Planning Commission Notice (No. [2017]20)Wuhan training project of the sixth batch of young and middle-aged medical talents, wuhan health & family planning commission (Wuhan Health & Family Planning Commission Notice No. [2018]116)Training project of the first batch of tanhualin famous doctors and students (Hubei TCM Hospital No. [2018]72)
文摘Objective:To explore core acupoints and acupoint selection principles in acupuncture and moxibustion for obesity,from syndrome differentiation prescriptions of the acupuncture-moxibustion therapy in 808 obesity prescriptions,by using node centrality and cluster analysis methods in complex network.Methods:Firstly,an acupoint network model is established,and acupoint nodes are assessed and calculated in multiple aspects by introducing the node centrality analysis idea of complex network,to excavate core acupoint nodes.Secondly,a cluster analysis is carried out on acupoint network by the cluster algorithm Q-PSO for complex network,to investigate the acupoint combination principles.Results:Zusanli(足三里ST36),Tianshu(天枢ST25),Fenglong(丰隆ST40),Zhongwan(中脘CV12)and Qihai(气海CV6),etc.,were included into the core acupoint Sanyinjiao(三阴交SP6)community.Zhigou(支沟TE6),Neiting(内庭ST44),Shangjuxu(上巨虚ST37),and Pishu(脾俞BL20)etc.,were included into the core acupoint Yinlingquan(阴陵泉SP9)community.Baihuanshu(白环俞BL30)and Zhiyang(至阳GV9)were included into the core acupoint Dachangshu(大肠俞BL25)community.Biguan(髀关ST31)was a single core community.Among all the acupoint nodes,SP6,ST25,SP9,ST36,CV6,Quchi(曲池L111),and Guanyuan(关元CV4)were of high degree centrality and eigenvector centrality,directly reflecting their importance in acupoint selection prescriptions.Conclusion:The Q-PSO algorithm is characterized with high precision and high efficiency,etc.The core acupoints and their combination principles explored by this algorithm are in accordance with clinical experiences.
文摘The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm.
文摘The deployment of Relay Nodes (RNs) in 4G LTE-A networks, mainly originating from the wireless backhaul link, provides an excellent network planning tool to enhance system performance. Better coordination between the base station and relays to mitigate inter-cell interference becomes an important aspect of achieving the required system performance, not only in the single-cell scenario, but also in multi-cell scenarios. In this paper, we model and analyze two basic approaches for designing a 4G LTE-A tri-sectored cellular system. The approaches are based on Antenna Selection Sectored Relaying (ASSR) and Beam Selection Sectored Relaying (BSSR). The main purpose of the proposed schemes is to enhance system performance by improving the quality of the wireless relay backhaul link. In this technique, antenna selection takes into consideration Non-Line-Of-Sight (NLOS) communication, whereas BSSR considers the case of Line-Of-Sight (LOS) communication using heuristic beam forming approach. The resource allocation problem has also been investigated for relay based cooperative LTE-A trisectored cell in the downlink. The best possible location for relay node in the sector, power allocation and MIMO channel modeling is formulated as an optimization problem with the aim of maximizing the end to end link rate and the Signal to Interference plus Noise Ratio (SINR) of 4G LTE-A systems. Power allocation/optimization has been solved by means of the duality equation of the stationary Karush-Kuhn-Tucker (KKT) cond让ion and is used to derive optimal values for the beam forming vector on both the relay as well as the access link. The performance of the proposed scheme is verified through simulations carried out using MATLAB software. The simulation results show a significant improvement in the SINR, throughput capacity, and coverage area of the 4G LTE-A cell, while guaranteeing better quality of service.
文摘将联邦学习应用于无线身体区域网络(wireless body area network,WBAN)可解决隐私数据保护问题,但仍然面临着全局模型准确率下降和能耗高的挑战。提出了面向智慧医疗的联邦学习系统模型,构建了各个WBAN节点参与联邦学习的能耗模型,分析了其数据特性和资源特性。为保护本地数据隐私,避免直接获取原始数据信息,引入KL散度(Kullback-Leibler divergence)代表各节点的统计异构程度,通过信道增益、带宽等指标代表各节点的系统异构程度,提出了一种结合SAC(soft actor-critic)的联邦学习动态节点选择和资源分配方法。在每轮联邦学习训练开始前,SAC算法根据WBAN节点上传的数据特性和资源特性,动态选择参与训练的节点、分配本地计算资源和通信资源,解决WBAN节点的统计异构性和系统异构性导致的全局模型准确率下降和能耗高的问题。在CIFAR10、FashionMNIST、PathMNIST数据集上的实验表明,所提方法相比FedAvg、FAVOR、FLASH-RL,全局模型准确率至多提高20%、能耗降低了50%,并加快了全局模型收敛速度、减小了准确率波动,证明了所提方法的有效性。
