To deal with a polluted by-product of coal production,central China’s Shanxi Province has explored a governance path that addresses both the symptoms and root causes.
The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This rev...The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.展开更多
As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-govern...As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.展开更多
Owing to the emergence of drug resistance and high morbidity,the need for novel antiviral drugs with novel targets is highly sought after.Marine-derived compounds mostly possess potent antiviral activity and serve as ...Owing to the emergence of drug resistance and high morbidity,the need for novel antiviral drugs with novel targets is highly sought after.Marine-derived compounds mostly possess potent antiviral activity and serve as a primary source for developing novel antiviral drugs,making the rapid discovery and evaluation of marine antiviral agents particularly crucial.Thus,future research should place greater emphasis on the identification of novel antiviral targets through the combination of artificial intelligence(AI)and structural pharmacology,as well as expanding the marine resource and target databases.展开更多
In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their explora...In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their exploration,extraction,and processing.His successor,Claudia Sheinbaum,reaffirmed this assertive resource governance policy in October 2024.As a direct consequence,the operations of the Chinese firm,Ganfeng Lithium in Mexico,experienced significant disruption.展开更多
Dear Editor,This letter deals with distributed resource allocation(DRA)over multiple interacting coalitions,where conflicts of interest may arise due to the relevance of one coalition’s decision to other coalitions’...Dear Editor,This letter deals with distributed resource allocation(DRA)over multiple interacting coalitions,where conflicts of interest may arise due to the relevance of one coalition’s decision to other coalitions’benefits.To address this challenge,a new model called intra-independent resource allocation game(IIRAG)is formulated under the framework of multi-coalition games.A new DRA algorithm is developed,which draws on techniques of variable replacement and leaderfollowing consensus.The proposed algorithm ensures linear convergence of the collective decision to the Nash equilibrium(NE)of the IIRAG,as well as satisfaction of the resource constraint throughout the iteration process.Numerical simulations validate the effectiveness of the proposed approach.展开更多
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The la...State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.展开更多
Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the id...Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented, l^esource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies： resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.展开更多
In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this neces...In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.展开更多
To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing...To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing resource management models lack openness,sharing ability and scalability,which make it difficult for many heterogeneous resources to co-exist in the same system. It is also difficult to resolve the conflicts between distributed self-management and centralized scheduling in the system. This paper analyzes the characteristics of resources in the distributed environment and proposes a new resource management architecture by considering the resource aggregation capacity of cloud computing. The architecture includes a universal resource scheduling optimization model which has been applied successfully in double-district multi-ship-scheduling multi-container-yard empty containers transporting of international shipping logistics. Applications in all these domains prove that this new resource management architecture is feasible and can achieve the expected effect.展开更多
The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tas...The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.展开更多
Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating ...Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.展开更多
Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-ba...Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-based model that uses Long-Short-Term Memory(LSTM)to optimize resource allocation under dynam-ically changing conditions.Designed to monitor the workload on individual IoT nodes,the model incorporates long-term data dependencies,enabling adaptive resource distribution in real time.The training process utilizes Min-Max normalization and grid search for hyperparameter tuning,ensuring high resource utilization and consistent performance.The simulation results demonstrate the effectiveness of the proposed method,outperforming the state-of-the-art approaches,including Dynamic and Efficient Enhanced Load-Balancing(DEELB),Optimized Scheduling and Collaborative Active Resource-management(OSCAR),Convolutional Neural Network with Monarch Butterfly Optimization(CNN-MBO),and Autonomic Workload Prediction and Resource Allocation for Fog(AWPR-FOG).For example,in scenarios with low system utilization,the model achieved a resource utilization efficiency of 95%while maintaining a latency of just 15 ms,significantly exceeding the performance of comparative methods.展开更多
In the vast hinterland of the Qinghai-Xizang Plateau in western China,a profound green transformation is advancing quietly.On the vast Gobi Desert,arrays of solar panels resemble a shimmering silver sea.White wind tur...In the vast hinterland of the Qinghai-Xizang Plateau in western China,a profound green transformation is advancing quietly.On the vast Gobi Desert,arrays of solar panels resemble a shimmering silver sea.White wind turbines stand tall against the sky,with their blades swirling slowly in the wind.Golmud,a city in west China’s Qinghai Province formerly known for its abundant natural resources.展开更多
The pivotal role of complex numbers in quantum mechanics underpins the resource theory of imaginarity.We investigate imaginarity dynamics in a single-qubit open system coupled to a non-Markovian environment.Crucially,...The pivotal role of complex numbers in quantum mechanics underpins the resource theory of imaginarity.We investigate imaginarity dynamics in a single-qubit open system coupled to a non-Markovian environment.Crucially,cavity field detuning emerges as the dominant regulator,driving continuous conversion between the real and imaginary components of coherence.Nonzero detuning induces characteristic non-periodic oscillations of imaginarity between zero and maximal values,preventing complete decoherence at specific times.We establish that imaginarity resources stem from both intrinsic system evolution and environmental feedback.Significantly,detuning-driven imaginarity generation persists even in Markovian regimes,demonstrating its origin beyond environmental memory effects.These insights offer new perspectives for understanding and harnessing quantum coherence.展开更多
The integration of Geostationary Earth Orbit(GEO)satellite constellations into Sixth Generation(6G)framework for cellular networks is essential to achieve global connectivity.Despite the major importance of this integ...The integration of Geostationary Earth Orbit(GEO)satellite constellations into Sixth Generation(6G)framework for cellular networks is essential to achieve global connectivity.Despite the major importance of this integration,current research often underestimates the limitations imposed by available satellite payload power,erroneously assuming a uniform maximum power density distribution across all communication beams.In this paper,we propose an Efficient Downlink Resource Allocation scheme(EDRA)that accounts for transmitting power resource limitations,variable service quality demands,and a heterogeneous number of users.Our approach relies on the thorough analysis of real-world demographic data,allowing us to optimize the allocation of downlink power and time-frequency resources in a practical and effective manner.Furthermore,we introduce an optimization model to maximize the total system revenue,using an iterative algorithm specifically designed to solve complex optimization problems.Numerical simulations demonstrated that the EDRA scheme improved the average network revenue by more than 66%relatively to standard methods,with performance gains increasingly large for an increasing diversity of service types,establishing the robustness and adaptability of the proposed EDRA scheme in the rapidly-evolving context of satellite-based communication systems.展开更多
Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the networks.With the evolution of new wireless technologies such as Fi...Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the networks.With the evolution of new wireless technologies such as Fifth Generation(5G)and Sixth Generation(6G)mobile networks,the service level requirements have become stricter and more heterogeneous depending on the use case.In this paper,we review a large body of literature on various resource allocation schemes that are used in particular in mobile wireless communication networks and compare the proposed schemes in terms of performance indicators as well as techniques used.Our review shows that among the strategies proposed in the literature,there is a wide variety of optimization targets and combinations thereof,focusing mainly on performance indicators such as energy efficiency,spectral efficiency,and network capacity.In addition,in this paper,selected algorithms for resource allocation are numerically analyzed through simulations to compare and highlight the importance of how the resource algorithms are implemented to achieve efficient usage of the available spectrum.The performance of selected algorithms is evaluated in a multi-cell heterogeneous network and compared to proportional fair and eICIC,a widely-used combination of resource allocation and interferencemitigation techniques used by communication networks.The results show that one approach may performbetter when looking at the individual average user data rate but worse when looking at the overall spectral or energy efficiency,depending on the category of traffic.The results,therefore,confirm that theremay not be a single algorithmthat visibly outperforms other candidates in terms of all performance criteria.Instead,their efficiency is always a consequence of a strategic choice of goals,and the targeted parameters are optimized at a price.Thus,the development and implementation of resource allocation algorithms must follow concrete usage scenarios and network needs and be highly dependent on the requirements and criteria of network performance.展开更多
Achieving the dual carbon goal through energy transition has become a global consensus.The increasingly recognized of mineral resources is increasingly recognized due to their role in determining the pace of energy tr...Achieving the dual carbon goal through energy transition has become a global consensus.The increasingly recognized of mineral resources is increasingly recognized due to their role in determining the pace of energy transition.China has a leading capacity in the production and processing of certain minerals.However,because the major sources are abroad,China still faces certain disadvantages in acquiring upstream resources.In response to the complex international situation and high consumption demand。展开更多
Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,...Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach.展开更多
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.
文摘To deal with a polluted by-product of coal production,central China’s Shanxi Province has explored a governance path that addresses both the symptoms and root causes.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
基金supported by the National Natural Science Foundation of China(W2412135)the Youth Innovation Promotion Association of the Chinese Academy of Sciences.
文摘As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.
文摘Owing to the emergence of drug resistance and high morbidity,the need for novel antiviral drugs with novel targets is highly sought after.Marine-derived compounds mostly possess potent antiviral activity and serve as a primary source for developing novel antiviral drugs,making the rapid discovery and evaluation of marine antiviral agents particularly crucial.Thus,future research should place greater emphasis on the identification of novel antiviral targets through the combination of artificial intelligence(AI)and structural pharmacology,as well as expanding the marine resource and target databases.
文摘In April 2022,then-President of Mexico Andrés Manuel López Obrador officially implemented the lithium resources nationalization law and established the state-owned enterprise LitioMx to oversee their exploration,extraction,and processing.His successor,Claudia Sheinbaum,reaffirmed this assertive resource governance policy in October 2024.As a direct consequence,the operations of the Chinese firm,Ganfeng Lithium in Mexico,experienced significant disruption.
基金supported by the National Natural Science Foundation of China(62003167,62376029,62325304,U22B2046,62073079,62088101,62133003,61991403)the General Joint Fund of the Equipment Advance Research Program of Ministry of Education(8091B022114)the China Postdoctoral Science Foundation(2023M730255).
文摘Dear Editor,This letter deals with distributed resource allocation(DRA)over multiple interacting coalitions,where conflicts of interest may arise due to the relevance of one coalition’s decision to other coalitions’benefits.To address this challenge,a new model called intra-independent resource allocation game(IIRAG)is formulated under the framework of multi-coalition games.A new DRA algorithm is developed,which draws on techniques of variable replacement and leaderfollowing consensus.The proposed algorithm ensures linear convergence of the collective decision to the Nash equilibrium(NE)of the IIRAG,as well as satisfaction of the resource constraint throughout the iteration process.Numerical simulations validate the effectiveness of the proposed approach.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.
基金supported by National High Technology Research and Development Program of China (863 Program)(No. 2007AA010305)the Excellent Doctor Degree Dissertation Fund of Xi an University of Technology (No. 102-211007)
文摘Resource reconstruction algorithms are studied in this paper to solve the problem of resource on-demand allocation and improve the efficiency of resource utilization in virtual computing resource pool. Based on the idea of resource virtualization and the analysis of the resource status transition, the resource allocation process and the necessity of resource reconstruction are presented, l^esource reconstruction algorithms are designed to determine the resource reconstruction types, and it is shown that they can achieve the goal of resource on-demand allocation through three methodologies： resource combination, resource split, and resource random adjustment. The effects that the resource users have on the resource reconstruction results, the deviation between resources and requirements, and the uniformity of resource distribution are studied by three experiments. The experiments show that resource reconstruction has a close relationship with resource requirements, but it is not the same with current distribution of resources. The algorithms can complete the resource adjustment with a lower cost and form the logic resources to match the demands of resource users easily.
基金supported by the National Key Research and Development Program of China(No.2021YFB2900504).
文摘In 6th Generation Mobile Networks(6G),the Space-Integrated-Ground(SIG)Radio Access Network(RAN)promises seamless coverage and exceptionally high Quality of Service(QoS)for diverse services.However,achieving this necessitates effective management of computation and wireless resources tailored to the requirements of various services.The heterogeneity of computation resources and interference among shared wireless resources pose significant coordination and management challenges.To solve these problems,this work provides an overview of multi-dimensional resource management in 6G SIG RAN,including computation and wireless resource.Firstly it provides with a review of current investigations on computation and wireless resource management and an analysis of existing deficiencies and challenges.Then focusing on the provided challenges,the work proposes an MEC-based computation resource management scheme and a mixed numerology-based wireless resource management scheme.Furthermore,it outlines promising future technologies,including joint model-driven and data-driven resource management technology,and blockchain-based resource management technology within the 6G SIG network.The work also highlights remaining challenges,such as reducing communication costs associated with unstable ground-to-satellite links and overcoming barriers posed by spectrum isolation.Overall,this comprehensive approach aims to pave the way for efficient and effective resource management in future 6G networks.
基金Support by the National Key Technology Research and Development Program of China(No.2012BAA13B01,2014BAF07B02)the National Natural Science Foundation of China(No.61273038)+1 种基金Natural Science Foundation of Shandong Province(No.ZR2015FM006)Science and Technology Major Project of the Ministry of Science and Technology of Shandong Province(No.2015ZDXX0201B02)
文摘To address the challenges posed by resource shortage or surplus to enterprises productivity,Internet platforms have been widely used,which can balance shortage and surplus in broader environments. However,the existing resource management models lack openness,sharing ability and scalability,which make it difficult for many heterogeneous resources to co-exist in the same system. It is also difficult to resolve the conflicts between distributed self-management and centralized scheduling in the system. This paper analyzes the characteristics of resources in the distributed environment and proposes a new resource management architecture by considering the resource aggregation capacity of cloud computing. The architecture includes a universal resource scheduling optimization model which has been applied successfully in double-district multi-ship-scheduling multi-container-yard empty containers transporting of international shipping logistics. Applications in all these domains prove that this new resource management architecture is feasible and can achieve the expected effect.
文摘The ease of accessing a virtually unlimited pool of resources makes Infrastructure as a Service (IaaS) clouds an ideal platform for running data-intensive workflow applications comprising hundreds of computational tasks. However, executing scientific workflows in IaaS cloud environments poses significant challenges due to conflicting objectives, such as minimizing execution time (makespan) and reducing resource utilization costs. This study responds to the increasing need for efficient and adaptable optimization solutions in dynamic and complex environments, which are critical for meeting the evolving demands of modern users and applications. This study presents an innovative multi-objective approach for scheduling scientific workflows in IaaS cloud environments. The proposed algorithm, MOS-MWMC, aims to minimize total execution time (makespan) and resource utilization costs by leveraging key features of virtual machine instances, such as a high number of cores and fast local SSD storage. By integrating realistic simulations based on the WRENCH framework, the method effectively dimensions the cloud infrastructure and optimizes resource usage. Experimental results highlight the superiority of MOS-MWMC compared to benchmark algorithms HEFT and Max-Min. The Pareto fronts obtained for the CyberShake, Epigenomics, and Montage workflows demonstrate closer proximity to the optimal front, confirming the algorithm’s ability to balance conflicting objectives. This study contributes to optimizing scientific workflows in complex environments by providing solutions tailored to specific user needs while minimizing costs and execution times.
文摘Efficient resource provisioning,allocation,and computation offloading are critical to realizing lowlatency,scalable,and energy-efficient applications in cloud,fog,and edge computing.Despite its importance,integrating Software Defined Networks(SDN)for enhancing resource orchestration,task scheduling,and traffic management remains a relatively underexplored area with significant innovation potential.This paper provides a comprehensive review of existing mechanisms,categorizing resource provisioning approaches into static,dynamic,and user-centric models,while examining applications across domains such as IoT,healthcare,and autonomous systems.The survey highlights challenges such as scalability,interoperability,and security in managing dynamic and heterogeneous infrastructures.This exclusive research evaluates how SDN enables adaptive policy-based handling of distributed resources through advanced orchestration processes.Furthermore,proposes future directions,including AI-driven optimization techniques and hybrid orchestrationmodels.By addressing these emerging opportunities,thiswork serves as a foundational reference for advancing resource management strategies in next-generation cloud,fog,and edge computing ecosystems.This survey concludes that SDN-enabled computing environments find essential guidance in addressing upcoming management opportunities.
基金funding of the Deanship of Graduate Studies and Scientific Research,Jazan University,Saudi Arabia,through Project Number:ISP-2024.
文摘Efficient resource management within Internet of Things(IoT)environments remains a pressing challenge due to the increasing number of devices and their diverse functionalities.This study introduces a neural network-based model that uses Long-Short-Term Memory(LSTM)to optimize resource allocation under dynam-ically changing conditions.Designed to monitor the workload on individual IoT nodes,the model incorporates long-term data dependencies,enabling adaptive resource distribution in real time.The training process utilizes Min-Max normalization and grid search for hyperparameter tuning,ensuring high resource utilization and consistent performance.The simulation results demonstrate the effectiveness of the proposed method,outperforming the state-of-the-art approaches,including Dynamic and Efficient Enhanced Load-Balancing(DEELB),Optimized Scheduling and Collaborative Active Resource-management(OSCAR),Convolutional Neural Network with Monarch Butterfly Optimization(CNN-MBO),and Autonomic Workload Prediction and Resource Allocation for Fog(AWPR-FOG).For example,in scenarios with low system utilization,the model achieved a resource utilization efficiency of 95%while maintaining a latency of just 15 ms,significantly exceeding the performance of comparative methods.
文摘In the vast hinterland of the Qinghai-Xizang Plateau in western China,a profound green transformation is advancing quietly.On the vast Gobi Desert,arrays of solar panels resemble a shimmering silver sea.White wind turbines stand tall against the sky,with their blades swirling slowly in the wind.Golmud,a city in west China’s Qinghai Province formerly known for its abundant natural resources.
基金support of the Tianchi Talented Young Doctoral Fund Project and Huyang Talent Research Startup Fund Project of Tarim University(Project Number:TDZKSS202511).
文摘The pivotal role of complex numbers in quantum mechanics underpins the resource theory of imaginarity.We investigate imaginarity dynamics in a single-qubit open system coupled to a non-Markovian environment.Crucially,cavity field detuning emerges as the dominant regulator,driving continuous conversion between the real and imaginary components of coherence.Nonzero detuning induces characteristic non-periodic oscillations of imaginarity between zero and maximal values,preventing complete decoherence at specific times.We establish that imaginarity resources stem from both intrinsic system evolution and environmental feedback.Significantly,detuning-driven imaginarity generation persists even in Markovian regimes,demonstrating its origin beyond environmental memory effects.These insights offer new perspectives for understanding and harnessing quantum coherence.
基金supported by Young Elite Scientists Sponsorship Program by CAST(No.2022QNRC001)。
文摘The integration of Geostationary Earth Orbit(GEO)satellite constellations into Sixth Generation(6G)framework for cellular networks is essential to achieve global connectivity.Despite the major importance of this integration,current research often underestimates the limitations imposed by available satellite payload power,erroneously assuming a uniform maximum power density distribution across all communication beams.In this paper,we propose an Efficient Downlink Resource Allocation scheme(EDRA)that accounts for transmitting power resource limitations,variable service quality demands,and a heterogeneous number of users.Our approach relies on the thorough analysis of real-world demographic data,allowing us to optimize the allocation of downlink power and time-frequency resources in a practical and effective manner.Furthermore,we introduce an optimization model to maximize the total system revenue,using an iterative algorithm specifically designed to solve complex optimization problems.Numerical simulations demonstrated that the EDRA scheme improved the average network revenue by more than 66%relatively to standard methods,with performance gains increasingly large for an increasing diversity of service types,establishing the robustness and adaptability of the proposed EDRA scheme in the rapidly-evolving context of satellite-based communication systems.
基金supported by the Slovenian Research and Innovation Agency(ARIS)within the Research Program P2-0425:“Decentralized Solutions for the Digitalization of Industry and Smart Cities and Communities”supported by the Ministry of Education,Science,Technology and Innovation of Republic of Kosovo through the annual small grant projects.
文摘Resource allocation remains a challenging issue in communication networks,and its complexity is continuously increasing with the densification of the networks.With the evolution of new wireless technologies such as Fifth Generation(5G)and Sixth Generation(6G)mobile networks,the service level requirements have become stricter and more heterogeneous depending on the use case.In this paper,we review a large body of literature on various resource allocation schemes that are used in particular in mobile wireless communication networks and compare the proposed schemes in terms of performance indicators as well as techniques used.Our review shows that among the strategies proposed in the literature,there is a wide variety of optimization targets and combinations thereof,focusing mainly on performance indicators such as energy efficiency,spectral efficiency,and network capacity.In addition,in this paper,selected algorithms for resource allocation are numerically analyzed through simulations to compare and highlight the importance of how the resource algorithms are implemented to achieve efficient usage of the available spectrum.The performance of selected algorithms is evaluated in a multi-cell heterogeneous network and compared to proportional fair and eICIC,a widely-used combination of resource allocation and interferencemitigation techniques used by communication networks.The results show that one approach may performbetter when looking at the individual average user data rate but worse when looking at the overall spectral or energy efficiency,depending on the category of traffic.The results,therefore,confirm that theremay not be a single algorithmthat visibly outperforms other candidates in terms of all performance criteria.Instead,their efficiency is always a consequence of a strategic choice of goals,and the targeted parameters are optimized at a price.Thus,the development and implementation of resource allocation algorithms must follow concrete usage scenarios and network needs and be highly dependent on the requirements and criteria of network performance.
基金the General Project of the National Natural Science Foundation of China,“Research on the Method of CO_(2)Technology Economic Evaluation Based on Net Energy and Carbon Input-Output”(72274212)。
文摘Achieving the dual carbon goal through energy transition has become a global consensus.The increasingly recognized of mineral resources is increasingly recognized due to their role in determining the pace of energy transition.China has a leading capacity in the production and processing of certain minerals.However,because the major sources are abroad,China still faces certain disadvantages in acquiring upstream resources.In response to the complex international situation and high consumption demand。
基金supported by National Key Research and Development Program of China(2024YFE0214000)National Natural Science Foundation of China(62173308)+3 种基金Natural Science Foundation of Zhejiang Province of China(LRG25F030002)Zhejiang Province Leading Geese Plan(2025C01056)Jinhua Science and Technology Project(2022-1-042)Natural Science Foundation of Jiangsu Province(BK20240009).
文摘Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.
