Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combinin...Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.展开更多
中国自动化学会(Chinese Association of Automation,CAA)是我国自动化领域最重要的学术团体之一。面对日益复杂的科研环境和繁重的科研任务,CAA需要不断调整传统的组织和运营模式以应对新的挑战。为此,基于智能合约、分布式自主组织与...中国自动化学会(Chinese Association of Automation,CAA)是我国自动化领域最重要的学术团体之一。面对日益复杂的科研环境和繁重的科研任务,CAA需要不断调整传统的组织和运营模式以应对新的挑战。为此,基于智能合约、分布式自主组织与运营(decentralized autonomous organization and operation,DAO)以及以大模型为代表的人工智能技术,提出了“数字CAA”的概念,构建了总体架构并详细探讨了关键支撑技术,描述了数字CAA的运行逻辑与应用场景,并以分支机构管理为典型案例,阐明其在优化管理和运行效率方面的辅助作用。同时,分析了数字CAA在实际应用中可能面临的主要挑战,在提升CAA可持续发展能力的同时,为其他科技组织的转型与变革提供参考和借鉴。展开更多
Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study...Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.展开更多
The 2023 China-ASEAN Expo was a big deal for Lao’s DAO Coffee.The Lao Prime Minister personally visited the DAO Coffee booth,an act that not only testified to the brand’s exceptional quality but also signaled strong...The 2023 China-ASEAN Expo was a big deal for Lao’s DAO Coffee.The Lao Prime Minister personally visited the DAO Coffee booth,an act that not only testified to the brand’s exceptional quality but also signaled strong support for the country’s burgeoning coffee industry.展开更多
Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has bee...Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has been advocated for decentralized data management in a tamper-resistance,traceable,and transparent manner.However,a major issue that hinders the integration of blockchain and IoT lies in that,it is rather challenging for resource-constrained IoT devices to perform computation-intensive blockchain consensuses such as Proof-of-Work(PoW).Furthermore,the incentive mechanism of PoW pushes lightweight IoT nodes to aggregate their computing power to increase the possibility of successful block generation.Nevertheless,this eventually leads to the formation of computing power alliances,and significantly compromises the decentralization and security of BlockChain-aided IoT(BC-IoT)networks.To cope with these issues,we propose a lightweight consensus protocol for BC-IoT,called Proof-of-Trusted-Work(PoTW).The goal of the proposed consensus is to disincentivize the centralization of computing power and encourage the independent participation of lightweight IoT nodes in blockchain consensus.First,we put forth an on-chain reputation evaluation rule and a reputation chain for PoTW to enable the verifiability and traceability of nodes’reputations based on their contributions of computing power to the blockchain consensus,and we incorporate the multi-level block generation difficulty as a rewards for nodes to accumulate reputations.Second,we model the block generation process of PoTW and analyze the block throughput using the continuous time Markov chain.Additionally,we define and optimize the relative throughput gain to quantify and maximize the capability of PoTW that suppresses the computing power centralization(i.e.,centralization suppression).Furthermore,we investigate the impact of the computing power of the computing power alliance and the levels of block generation difficulty on the centralization suppression capability of PoTW.Finally,simulation results demonstrate the consistency of the analytical results in terms of block throughput.In particular,the results show that PoTW effectively reduces the block generation proportion of the computing power alliance compared with PoW,while simultaneously improving that of individual lightweight nodes.This indicates that PoTW is capable of suppressing the centralization of computing power to a certain degree.Moreover,as the levels of block generation difficulty in PoTW increase,its centralization suppression capability strengthens.展开更多
1 Introduction Dao Zang(《道藏》The Daoist Classic Collection)is an important portrayal of Daoist thought,teachings,and doctrines.The version that has been passed down to the present day is Dao Zang written in the Min...1 Introduction Dao Zang(《道藏》The Daoist Classic Collection)is an important portrayal of Daoist thought,teachings,and doctrines.The version that has been passed down to the present day is Dao Zang written in the Ming dynasty[Zheng Tong Dao Zang(《正统道藏》Dao Zang in the Zhengtong Era)and Wan Li Xu Dao Zang(《万历续道藏》The Supplement of Dao Zang in the Wanli Era)],which contains more than 1,400 types of literature with an all-encompassing content.Therefore,in the study of ancient Chinese culture,Dao Zang is a topic that cannot be neglected,and it has attracted the attention of scholars at home and abroad.At the beginning of the 19th century,with the increasing cultural exchanges between China and the West,European scholars began to develop a strong interest in traditional Chinese culture.As an important component of Chinese culture,Daoism and its classic literature,Dao Zang,became the focus of attention for European scholars.Against this backdrop,a research craze for Daoism gradually emerged in Europe,giving rise to a number of influential scholars and research achievements.The works included the French sinologist Maxime Kaltenmark’s(康德谟)Legend of the Immortal:Biography of the Ancient Daoist Immortal(《列仙传:古代道教仙人的传说传记》,1953),John Lagerwey’s(劳格文)Supreme Secret:Overview of Daoism in the Sixth Century(《无上秘要:六世纪的道教总汇》,1981)from the Far Eastern Academy of France,and Chronicle of Daoist Studies in the West(《西方道教研究编年史》,1989)edited by French scholar Anna Sei-del,to name a few.展开更多
Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and acc...Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.展开更多
In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy.In classical federated learning, the...In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy.In classical federated learning, the communication channel between the devices poses a potential risk of compromising private information. To reduce the risk of adversary eavesdropping in the communication channel, we propose TRADE(transmit difference weight) concept. This concept replaces the decentralized federated learning algorithm's transmitted weight parameters with differential weight parameters, enhancing the privacy data against eavesdropping. Subsequently, by integrating the TRADE concept with the primal-dual stochastic gradient descent(SGD)algorithm, we propose a decentralized TRADE primal-dual SGD algorithm. We demonstrate that our proposed algorithm's convergence properties are the same as those of the primal-dual SGD algorithm while providing enhanced privacy protection. We validate the algorithm's performance on fault diagnosis task using the Case Western Reserve University dataset, and image classification tasks using the CIFAR-10 and CIFAR-100 datasets,revealing model accuracy comparable to centralized federated learning. Additionally, the experiments confirm the algorithm's privacy protection capability.展开更多
Federated Graph Learning (FGL) enables model training without requiring each client to share local graph data, effectively breaking data silos by aggregating the training parameters from each terminal while safeguardi...Federated Graph Learning (FGL) enables model training without requiring each client to share local graph data, effectively breaking data silos by aggregating the training parameters from each terminal while safeguarding data privacy. Traditional FGL relies on a centralized server for model aggregation;however, this central server presents challenges such as a single point of failure and high communication overhead. Additionally, efficiently training a robust personalized local model for each client remains a significant objective in federated graph learning. To address these issues, we propose a decentralized Federated Graph Learning framework with efficient communication, termed Decentralized Federated Graph Learning via Surrogate Model (SD_FGL). In SD_FGL, each client is required to maintain two models: a private model and a surrogate model. The surrogate model is publicly shared and can exchange and update information directly with any client, eliminating the need for a central server and reducing communication overhead. The private model is independently trained by each client, allowing it to calculate similarity with other clients based on local data as well as information shared through the surrogate model. This enables the private model to better adjust its training strategy and selectively update its parameters. Additionally, local differential privacy is incorporated into the surrogate model training process to enhance privacy protection. Testing on three real-world graph datasets demonstrates that the proposed framework improves accuracy while achieving decentralized Federated Graph Learning with lower communication overhead and stronger privacy safeguards.展开更多
Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the ...Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the predicament by evaluating the feasibility of renewable energy-based decentralized electrification in the selected village ofDoleibHill,UpperNile,South Sudan.Using a demand assessment and theMulti-Tier Framework(MTF)approach,it categorizes households,public facilities,private sector,Non-GovernmentalOrganizations(NGOs)and business energy needs and designs an optimized hybrid energy system incorporating solar Photovoltaic(PV),wind turbines,batteries,and a generator.The proposed system,simulated in Hybrid Optimization Model Electric Renewable(HOMER)Pro,demonstrates strong economic viability,with a present worth of$292,145,an annual worth of$22,854,a return on investment(ROI)of 36.5%,and an internal rate of return(IRR)of 42.1%.The simple payback period is 2.31 years,and the discounted payback period is 2.62 years.The system achieves a levelized cost of energy(LCOE)of$0.276/kWh and significantly reduces dependence on diesel,producing 798,800 kWh annually fromwind energy.This research provides a replicable model for cost-effective,sustainable rural electrification,offering valuable insights for policymakers and energy planners seeking to expand electricity access in off-grid communities.展开更多
Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],th...Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],the algorithm combines a consensus protocol on with a local Riemannian gradient term,but the state of each agent evolves on the nonlinear manifold.In absence of global information for each node,a coordinator is introduced in the communication network to ensure that all agents achieve convergence with consensus.Resorting to Lyapunov approaches,it is shown that the proposed algorithm reaches an optimal solution.展开更多
This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,t...This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.展开更多
文摘Optimizing routing and resource allocation in decentralized unmanned aerial vehicle(UAV)networks remains challenging due to interference and rapidly changing topologies.The authors introduce a novel framework combining double deep Q-networks(DDQNs)and graph neural networks(GNNs)for joint routing and resource allocation.The framework uses GNNs to model the network topology and DDQNs to adaptively control routing and resource allocation,addressing interference and improving network performance.Simulation results show that the proposed approach outperforms traditional methods such as Closest-to-Destination(c2Dst),Max-SINR(mSINR),and Multi-Layer Perceptron(MLP)-based models,achieving approximately 23.5% improvement in throughput,50% increase in connection probability,and 17.6% reduction in number of hops,demonstrating its effectiveness in dynamic UAV networks.
文摘中国自动化学会(Chinese Association of Automation,CAA)是我国自动化领域最重要的学术团体之一。面对日益复杂的科研环境和繁重的科研任务,CAA需要不断调整传统的组织和运营模式以应对新的挑战。为此,基于智能合约、分布式自主组织与运营(decentralized autonomous organization and operation,DAO)以及以大模型为代表的人工智能技术,提出了“数字CAA”的概念,构建了总体架构并详细探讨了关键支撑技术,描述了数字CAA的运行逻辑与应用场景,并以分支机构管理为典型案例,阐明其在优化管理和运行效率方面的辅助作用。同时,分析了数字CAA在实际应用中可能面临的主要挑战,在提升CAA可持续发展能力的同时,为其他科技组织的转型与变革提供参考和借鉴。
基金supported by the National Research Foundation of Korea(NRF)grants(2022R1A2C4001228,2022M3H4A4097524,2022M3I3A1082499,and 2021M3I3A1084818)the Technology Innovation Program(20026415)of the Ministry of Trade,Industry&Energy(MOTIE,Korea)the supports from Nanopac for fabrication of scaled-up reactor.
文摘Wastewater electrolysis cells(WECs)for decentralized wastewater treatment/reuse coupled with H_(2) production can reduce the carbon footprint associated with transportation of water,waste,and energy carrier.This study reports Ir-doped NiFe_(2)O_(4)(NFI,~5 at%Ir)spinel layer with TiO_(2) overlayer(NFI/TiO_(2)),as a scalable heterojunction anode for direct electrolysis of wastewater with circumneutral pH in a single-compartment cell.In dilute(0.1 M)NaCl solutions,the NFI/TiO_(2) marks superior activity and selectivity for chlorine evolution reaction,outperforming the benchmark IrO_(2).Robust operation in near-neutral pH was confirmed.Electroanalyses including operando X-ray absorption spectroscopy unveiled crucial roles of TiO_(2) which serves both as the primary site for Cl−chemisorption and a protective layer for NFI as an ohmic contact.Galvanostatic electrolysis of NH4+-laden synthetic wastewater demonstrated that NFI/TiO_(2)not only achieves quasi-stoichiometric NH_(4)^(+)-to-N_(2)conversion,but also enhances H_(2)generation efficiency with minimal competing reactions such as reduction of dissolved oxygen and reactive chlorine.The scaled-up WEC with NFI/TiO_(2)was demonstrated for electrolysis of toilet wastewater.
文摘The 2023 China-ASEAN Expo was a big deal for Lao’s DAO Coffee.The Lao Prime Minister personally visited the DAO Coffee booth,an act that not only testified to the brand’s exceptional quality but also signaled strong support for the country’s burgeoning coffee industry.
基金supported in part by National Key R&D Program of China(Grant No.2021YFB1714100)in part by the National Natural Science Foundation of China(NSFC)under Grant 62371239+5 种基金in part by the the Program of Science and Technology Cooperation of Nanjing with International/Hong Kong,Macao and Taiwan(Grant No.202401019)in part by the Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515012407)in part by the the Research Center for FinTech and Digital-Intelligent Management at Shenzhen University,in part by the National Natural Science Foundation of China under Grant 62271192in part by the Equipment Pre-Research Joint Research Program of Ministry of Education under Grant 8091B032129in part by the Major Science and Technology Projects of Longmen Laboratory under Grant 231100220300 and 231100220200in part by the Central Plains Leading Talent in Scientific and Technological Innovation Program under Grant 244200510048.
文摘Traditional Internet of Things(IoT)architectures that rely on centralized servers for data management and decision-making are vulnerable to security threats and privacy leakage.To address this issue,blockchain has been advocated for decentralized data management in a tamper-resistance,traceable,and transparent manner.However,a major issue that hinders the integration of blockchain and IoT lies in that,it is rather challenging for resource-constrained IoT devices to perform computation-intensive blockchain consensuses such as Proof-of-Work(PoW).Furthermore,the incentive mechanism of PoW pushes lightweight IoT nodes to aggregate their computing power to increase the possibility of successful block generation.Nevertheless,this eventually leads to the formation of computing power alliances,and significantly compromises the decentralization and security of BlockChain-aided IoT(BC-IoT)networks.To cope with these issues,we propose a lightweight consensus protocol for BC-IoT,called Proof-of-Trusted-Work(PoTW).The goal of the proposed consensus is to disincentivize the centralization of computing power and encourage the independent participation of lightweight IoT nodes in blockchain consensus.First,we put forth an on-chain reputation evaluation rule and a reputation chain for PoTW to enable the verifiability and traceability of nodes’reputations based on their contributions of computing power to the blockchain consensus,and we incorporate the multi-level block generation difficulty as a rewards for nodes to accumulate reputations.Second,we model the block generation process of PoTW and analyze the block throughput using the continuous time Markov chain.Additionally,we define and optimize the relative throughput gain to quantify and maximize the capability of PoTW that suppresses the computing power centralization(i.e.,centralization suppression).Furthermore,we investigate the impact of the computing power of the computing power alliance and the levels of block generation difficulty on the centralization suppression capability of PoTW.Finally,simulation results demonstrate the consistency of the analytical results in terms of block throughput.In particular,the results show that PoTW effectively reduces the block generation proportion of the computing power alliance compared with PoW,while simultaneously improving that of individual lightweight nodes.This indicates that PoTW is capable of suppressing the centralization of computing power to a certain degree.Moreover,as the levels of block generation difficulty in PoTW increase,its centralization suppression capability strengthens.
基金financed by the grants from the Youth Program of the National Social Science Foundation(No.19CZJ023)the second batch of approved projects of the Zhejiang Cultural Research Project(No.23WH27ZD).
文摘1 Introduction Dao Zang(《道藏》The Daoist Classic Collection)is an important portrayal of Daoist thought,teachings,and doctrines.The version that has been passed down to the present day is Dao Zang written in the Ming dynasty[Zheng Tong Dao Zang(《正统道藏》Dao Zang in the Zhengtong Era)and Wan Li Xu Dao Zang(《万历续道藏》The Supplement of Dao Zang in the Wanli Era)],which contains more than 1,400 types of literature with an all-encompassing content.Therefore,in the study of ancient Chinese culture,Dao Zang is a topic that cannot be neglected,and it has attracted the attention of scholars at home and abroad.At the beginning of the 19th century,with the increasing cultural exchanges between China and the West,European scholars began to develop a strong interest in traditional Chinese culture.As an important component of Chinese culture,Daoism and its classic literature,Dao Zang,became the focus of attention for European scholars.Against this backdrop,a research craze for Daoism gradually emerged in Europe,giving rise to a number of influential scholars and research achievements.The works included the French sinologist Maxime Kaltenmark’s(康德谟)Legend of the Immortal:Biography of the Ancient Daoist Immortal(《列仙传:古代道教仙人的传说传记》,1953),John Lagerwey’s(劳格文)Supreme Secret:Overview of Daoism in the Sixth Century(《无上秘要:六世纪的道教总汇》,1981)from the Far Eastern Academy of France,and Chronicle of Daoist Studies in the West(《西方道教研究编年史》,1989)edited by French scholar Anna Sei-del,to name a few.
基金Fundação de AmparoàPesquisa do Estado da Bahia(FAPESB),Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico(CNPq)organizations for supporting the Graduate Program in Computer Science at the Federal University of Bahia.
文摘Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.
基金supported by the National Key Research and Development Program of China(2022YFB3305904)the National Natural Science Foundation of China(62133003,61991403,61991400)+4 种基金the Open Project of State Key Laboratory of Synthetical Automation for Process Industries(SAPI-2024-KFKT-05,SAPI-2024-KFKT-08)China Academy of Engineering Institute of Land Cooperation Consulting Project(2023-DFZD-60-02,N2424004)the Fundamental Research Funds for the Central UniversitiesShanghai Municipal Science and Technology Major Project(2021SHZDZX0100)the Key Research and Development Program of Liaoning Province(2023JH26/10200011)
文摘In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy.In classical federated learning, the communication channel between the devices poses a potential risk of compromising private information. To reduce the risk of adversary eavesdropping in the communication channel, we propose TRADE(transmit difference weight) concept. This concept replaces the decentralized federated learning algorithm's transmitted weight parameters with differential weight parameters, enhancing the privacy data against eavesdropping. Subsequently, by integrating the TRADE concept with the primal-dual stochastic gradient descent(SGD)algorithm, we propose a decentralized TRADE primal-dual SGD algorithm. We demonstrate that our proposed algorithm's convergence properties are the same as those of the primal-dual SGD algorithm while providing enhanced privacy protection. We validate the algorithm's performance on fault diagnosis task using the Case Western Reserve University dataset, and image classification tasks using the CIFAR-10 and CIFAR-100 datasets,revealing model accuracy comparable to centralized federated learning. Additionally, the experiments confirm the algorithm's privacy protection capability.
基金supported by InnerMongolia Natural Science Foundation Project(2021LHMS06003)Inner Mongolia University Basic Research Business Fee Project(114).
文摘Federated Graph Learning (FGL) enables model training without requiring each client to share local graph data, effectively breaking data silos by aggregating the training parameters from each terminal while safeguarding data privacy. Traditional FGL relies on a centralized server for model aggregation;however, this central server presents challenges such as a single point of failure and high communication overhead. Additionally, efficiently training a robust personalized local model for each client remains a significant objective in federated graph learning. To address these issues, we propose a decentralized Federated Graph Learning framework with efficient communication, termed Decentralized Federated Graph Learning via Surrogate Model (SD_FGL). In SD_FGL, each client is required to maintain two models: a private model and a surrogate model. The surrogate model is publicly shared and can exchange and update information directly with any client, eliminating the need for a central server and reducing communication overhead. The private model is independently trained by each client, allowing it to calculate similarity with other clients based on local data as well as information shared through the surrogate model. This enables the private model to better adjust its training strategy and selectively update its parameters. Additionally, local differential privacy is incorporated into the surrogate model training process to enhance privacy protection. Testing on three real-world graph datasets demonstrates that the proposed framework improves accuracy while achieving decentralized Federated Graph Learning with lower communication overhead and stronger privacy safeguards.
文摘Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the predicament by evaluating the feasibility of renewable energy-based decentralized electrification in the selected village ofDoleibHill,UpperNile,South Sudan.Using a demand assessment and theMulti-Tier Framework(MTF)approach,it categorizes households,public facilities,private sector,Non-GovernmentalOrganizations(NGOs)and business energy needs and designs an optimized hybrid energy system incorporating solar Photovoltaic(PV),wind turbines,batteries,and a generator.The proposed system,simulated in Hybrid Optimization Model Electric Renewable(HOMER)Pro,demonstrates strong economic viability,with a present worth of$292,145,an annual worth of$22,854,a return on investment(ROI)of 36.5%,and an internal rate of return(IRR)of 42.1%.The simple payback period is 2.31 years,and the discounted payback period is 2.62 years.The system achieves a levelized cost of energy(LCOE)of$0.276/kWh and significantly reduces dependence on diesel,producing 798,800 kWh annually fromwind energy.This research provides a replicable model for cost-effective,sustainable rural electrification,offering valuable insights for policymakers and energy planners seeking to expand electricity access in off-grid communities.
基金supported by the National Key Research and Development Program of China(2022YFA1004701)the National Natural Science Foundation of China(72271187,62373283)Shanghai Municipal Science and Technology Major(2021SHZDZX0100).
文摘Dear Editor,SO(3)SO(3)This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on over a multi-agent network.Inspired by the distributed subgradient method in[1],the algorithm combines a consensus protocol on with a local Riemannian gradient term,but the state of each agent evolves on the nonlinear manifold.In absence of global information for each node,a coordinator is introduced in the communication network to ensure that all agents achieve convergence with consensus.Resorting to Lyapunov approaches,it is shown that the proposed algorithm reaches an optimal solution.
基金supported by the National Natural Science Foundation of China(U21A20477,61722302,61573069,61903290)the Fundamental Research Funds for the Central Universities(DUT19ZD218).
文摘This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.
