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.
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
When a disaster occurs, the demand for information and communication technology (ICT) services drastically increases. To meet such demands, a national project was undertaken in Japan to develop the Movable and Deploya...When a disaster occurs, the demand for information and communication technology (ICT) services drastically increases. To meet such demands, a national project was undertaken in Japan to develop the Movable and Deployable ICT Resource Unit (MDRU). One challenge regarding the MDRU is securing operators to work the units in emergency situations. As ICT service users have diverse and frequently changing demands, strong technical skills and practical knowledge are required for the administration of MDRUs. In this paper, we propose a knowledge-based network management system to alleviate the burden on administrators. To deal with the structural changes to network systems that frequently occur with changes in ICT service demand, we introduce modularization techniques into our previous research. The proposed system can be easily reconfigured by join/disjoin modules corresponding to changes in the system configuration of the MDRU. The results of our experiments using the implemented experimental system confirm that the proposed system can be applied to MDRU operation and effectively supports administrators.展开更多
Cloud computing is a dynamic and rapidly evolving field,where the demand for resources fluctuates continuously.This paper delves into the imperative need for adaptability in the allocation of resources to applications...Cloud computing is a dynamic and rapidly evolving field,where the demand for resources fluctuates continuously.This paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing environments.The motivation stems from the pressing issue of accommodating fluctuating levels of user demand efficiently.By adhering to the proposed resource allocation method,we aim to achieve a substantial reduction in energy consumption.This reduction hinges on the precise and efficient allocation of resources to the tasks that require those most,aligning with the broader goal of sustainable and eco-friendly cloud computing systems.To enhance the resource allocation process,we introduce a novel knowledge-based optimization algorithm.In this study,we rigorously evaluate its efficacy by comparing it to existing algorithms,including the Flower Pollination Algorithm(FPA),Spark Lion Whale Optimization(SLWO),and Firefly Algo-rithm.Our findings reveal that our proposed algorithm,Knowledge Based Flower Pollination Algorithm(KB-FPA),consistently outperforms these conventional methods in both resource allocation efficiency and energy consumption reduction.This paper underscores the profound significance of resource allocation in the realm of cloud computing.By addressing the critical issue of adaptability and energy efficiency,it lays the groundwork for a more sustainable future in cloud computing systems.Our contribution to the field lies in the introduction of a new resource allocation strategy,offering the potential for significantly improved efficiency and sustainability within cloud computing infrastructures.展开更多
The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial resources.Oxygen,crucial for supporting human life on the Moon,can be extract...The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial resources.Oxygen,crucial for supporting human life on the Moon,can be extracted from lunar regolith,which is highly rich in oxygen and contains polymetallic oxides.This oxygen and metal extraction can be achieved using existing metallurgical techniques.Furthermore,the ample reserves of water ice on the Moon offer another means for oxygen production.This paper offers a detailed overview of the leading technologies for achieving oxygen production on the Moon,drawing from an analysis of lunar resources and environmental conditions.It delves into the principles,processes,advantages,and drawbacks of water-ice electrolysis,two-step oxygen production from lunar regolith,and one-step oxygen production from lunar regolith.The two-step methods involve hydrogen reduction,carbothermal reduction,and hydrometallurgy,while the one-step methods encompass fluorination/chlorination,high-temperature decomposition,molten salt electrolysis,and molten regolith electrolysis(MOE).Following a thorough comparison of raw materials,equipment,technology,and economic viability,MOE is identified as the most promising approach for future in-situ oxygen production on the Moon.Considering the corrosion characteristics of molten lunar regolith at high temperatures,along with the Moon's low-gravity environment,the development of inexpensive and stable inert anodes and electrolysis devices that can easily collect oxygen is critical for promoting MOE technology on the Moon.This review significantly contributes to our understanding of in-situ oxygen production technologies on the Moon and supports upcoming lunar exploration initiatives.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
In the sixth generation mobile communication(6G) system,Non-Terrestrial Networks(NTN),as a supplement to terrestrial network,can meet the requirements of wide area intelligent connection and global ubiquitous seamless...In the sixth generation mobile communication(6G) system,Non-Terrestrial Networks(NTN),as a supplement to terrestrial network,can meet the requirements of wide area intelligent connection and global ubiquitous seamless access,establish intelligent connection for wide area objects,and provide intelligent services.Due to issues such as massive access,doppler shift,and limited spectrum resources in NTN,research on resource management is crucial for optimizing NTN performance.In this paper,a comprehensive survey of multi-pattern heterogeneous NTN resource management is provided.Firstly,the key technologies involved in NTN resource management is summarized.Secondly,NTN resource management is discussed from network pattern and resource pattern.The network pattern focuses on the application of different optimization methods to different network dimension communication resource management,and the resource type pattern focuses on the research and application of multi-domain resource management such as computation,cache,communication and sensing.Finally,future research directions and challenges of 6G NTN resource management are discussed.展开更多
By reviewing the research progress and exploration practices of shale gas geology in China,analyzing and summarizing the geological characteristics,enrichment laws,and resource potential of different types of shale ga...By reviewing the research progress and exploration practices of shale gas geology in China,analyzing and summarizing the geological characteristics,enrichment laws,and resource potential of different types of shale gas,the following understandings have been obtained:(1)Marine,transitional,and lacustrine shales in China are distributed from old to new in geological age,and the complexity of tectonic reworking and hydrocarbon generation evolution processes gradually decreases.(2)The sedimentary environment controls the type of source-reservoir configuration,which is the basis of“hydrocarbon generation and reservoir formation”.The types of source-reservoir configuration in marine and lacustrine shales are mainly source-reservoir integration,with occasional source-reservoir separation.The configuration types of transitional shale are mainly source-reservoir integration and source-reservoir symbiosis.(3)The resistance of rigid minerals to compression for pore preservation and the overpressure facilitate the enrichment of source-reservoir integrated shale gas.Good source reservoir coupling and preservation conditions are crucial for the shale gas enrichment of source-reservoir symbiosis and source-reservoir separation types.(4)Marine shale remains the main battlefield for increasing shale gas reserves and production in China,while transitional and lacustrine shales are expected to become important replacement areas.It is recommended to carry out the shale gas exploration at three levels:Accelerate the exploration of Silurian,Cambrian,and Permian marine shales in the Upper-Middle Yangtze region;make key exploration breakthroughs in ultra-deep marine shales of the Upper-Middle Yangtze region,the new Ordovician marine shale strata in the North China region,the transitional shales of the Carboniferous and Permian,as well as the Mesozoic lacustrine shale gas in basins such as Sichuan,Ordos and Songliao;explore and prepare for new shale gas exploration areas such as South China and Northwest China,providing technology and resource reserves for the sustainable development of shale gas in China.展开更多
In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its as...In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.展开更多
Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the corr...Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the correlations between energy poverty,energy intensity,resource abundance,and income inequality,as these factors have been theorized to play important roles in influencing energy poverty in developing countries.By observing that the dataset is heterogeneous across the countries and over the time frame,we use the Method of Moments Quantile Regression(MMQR)to analyze our developing countries’data from 2000 to 2019.Our findings indicate that energy intensity is a significant factor influencing energy poverty,suggesting that higher energy consumption relative to the sample countries can exacerbate this issue.Additionally,we observe that income inequality within the sample countries is a critical determinant of energy poverty levels,highlighting the dynamics between economic disparity and access to energy resources.Interestingly,our study reveals that resource abundance acts as a blessing rather than a curse in terms of energy poverty,implying that countries rich in natural resources may have better opportunities to combat energy deprivation.Finally,we emphasize the vital role of financial markets in addressing energy poverty on a global scale,suggesting that robust financial systems can facilitate investments and innovations aimed at improving energy access for vulnerable populations.The results from the robustness analysis support the empirical results obtained from the main estimation.The empirical findings of the present study advance important comprehensions for policymakers to adopt energy policies that address the complex challenges of energy poverty and promote inclusive energy access.展开更多
The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR ...The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR enhanced canopy heterogeneity by altering the leaf angle between plants on ridges and furrows.The heterogeneous canopy environment increased intercepted photosynthetic active radiation,alleviated canopy temperature stress,and optimized canopy humidity,leading to improvements in light-nitrogen matching and net photosynthetic rate.Consequently,dry matter and yield increased by 13.0%and 11.0%,respectively,while radiation,thermal,and precipitation utilization efficiency increased by 12.3%-16.2%.The corresponding improvements in yield and resource use efficiency were attributed to a heterogeneous canopy environment that improved microclimatic conditions.展开更多
Lithium iron phosphate(LiFePO_(4),LFP)batteries have shown extensive adoption in power applications in recent years for their reliable safety,high theoretical capability and low cost.Nevertheless,the finite lifespan o...Lithium iron phosphate(LiFePO_(4),LFP)batteries have shown extensive adoption in power applications in recent years for their reliable safety,high theoretical capability and low cost.Nevertheless,the finite lifespan of these batteries necessitates the future processing of a significant number of spent LFP batteries,underscoring the urgent need for the development of both efficient and eco-friendly recycling methods.This study combines the advantages of wet leaching and direct regeneration methods,leveraging citric acid's multifaceted role to streamline the combined leaching and hydrothermal processes.Results indicate that citric acid efficiently leaches all elements from spent LFP batteries.Furthermore,through its unique structure,it enhances hydrothermal regeneration by stabilizing metal ions and controlling crystal growth,and also acts as a carbon source for the surface carbon coating of regenerated LFP(RLFP).The R-LFP shows outstanding electrochemical stability,achieving a discharge capacity of 155.1 mAh.g^(-1)at 0.1C,with a capacity retention rate of 93.2%after 300 cycles at 1C.Furthermore,economic and environmental analyses demonstrate this method's superior cost-effectiveness and sustainability.Therefore,the method proposed in this study is efficient,simple and avoids the complex process of element separation,innovatively using a single reagent to achieve closed-loop recycling of LFP batteries,providing a novel and effective solution for the resource sustainability application.展开更多
The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achievi...The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.展开更多
Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industr...Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.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
[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of...[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.展开更多
The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.H...The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.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
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
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When a disaster occurs, the demand for information and communication technology (ICT) services drastically increases. To meet such demands, a national project was undertaken in Japan to develop the Movable and Deployable ICT Resource Unit (MDRU). One challenge regarding the MDRU is securing operators to work the units in emergency situations. As ICT service users have diverse and frequently changing demands, strong technical skills and practical knowledge are required for the administration of MDRUs. In this paper, we propose a knowledge-based network management system to alleviate the burden on administrators. To deal with the structural changes to network systems that frequently occur with changes in ICT service demand, we introduce modularization techniques into our previous research. The proposed system can be easily reconfigured by join/disjoin modules corresponding to changes in the system configuration of the MDRU. The results of our experiments using the implemented experimental system confirm that the proposed system can be applied to MDRU operation and effectively supports administrators.
基金supported by the Ministerio Espanol de Ciencia e Innovación under Project Number PID2020-115570GB-C22 MCIN/AEI/10.13039/501100011033 and by the Cátedra de Empresa Tecnología para las Personas(UGR-Fujitsu).
文摘Cloud computing is a dynamic and rapidly evolving field,where the demand for resources fluctuates continuously.This paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing environments.The motivation stems from the pressing issue of accommodating fluctuating levels of user demand efficiently.By adhering to the proposed resource allocation method,we aim to achieve a substantial reduction in energy consumption.This reduction hinges on the precise and efficient allocation of resources to the tasks that require those most,aligning with the broader goal of sustainable and eco-friendly cloud computing systems.To enhance the resource allocation process,we introduce a novel knowledge-based optimization algorithm.In this study,we rigorously evaluate its efficacy by comparing it to existing algorithms,including the Flower Pollination Algorithm(FPA),Spark Lion Whale Optimization(SLWO),and Firefly Algo-rithm.Our findings reveal that our proposed algorithm,Knowledge Based Flower Pollination Algorithm(KB-FPA),consistently outperforms these conventional methods in both resource allocation efficiency and energy consumption reduction.This paper underscores the profound significance of resource allocation in the realm of cloud computing.By addressing the critical issue of adaptability and energy efficiency,it lays the groundwork for a more sustainable future in cloud computing systems.Our contribution to the field lies in the introduction of a new resource allocation strategy,offering the potential for significantly improved efficiency and sustainability within cloud computing infrastructures.
基金financially supported by the National Natural Science Foundation of China(Nos.52404328,52274412,and 52374418)the China Postdoctoral Science Foundation(No.2024M753248)。
文摘The rich resources and unique environment of the Moon make it an ideal location for human expansion and the utilization of extraterrestrial resources.Oxygen,crucial for supporting human life on the Moon,can be extracted from lunar regolith,which is highly rich in oxygen and contains polymetallic oxides.This oxygen and metal extraction can be achieved using existing metallurgical techniques.Furthermore,the ample reserves of water ice on the Moon offer another means for oxygen production.This paper offers a detailed overview of the leading technologies for achieving oxygen production on the Moon,drawing from an analysis of lunar resources and environmental conditions.It delves into the principles,processes,advantages,and drawbacks of water-ice electrolysis,two-step oxygen production from lunar regolith,and one-step oxygen production from lunar regolith.The two-step methods involve hydrogen reduction,carbothermal reduction,and hydrometallurgy,while the one-step methods encompass fluorination/chlorination,high-temperature decomposition,molten salt electrolysis,and molten regolith electrolysis(MOE).Following a thorough comparison of raw materials,equipment,technology,and economic viability,MOE is identified as the most promising approach for future in-situ oxygen production on the Moon.Considering the corrosion characteristics of molten lunar regolith at high temperatures,along with the Moon's low-gravity environment,the development of inexpensive and stable inert anodes and electrolysis devices that can easily collect oxygen is critical for promoting MOE technology on the Moon.This review significantly contributes to our understanding of in-situ oxygen production technologies on the Moon and supports upcoming lunar exploration initiatives.
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supported in part by the National Natural Science Foundation of China under Grant 62225103,U22B2003,U2441227,and U24A20211the Beijing Natural Science Foundation under Grant L241008+3 种基金the Defense Industrial Technology Development Program JCKY2022110C010the National Key Laboratory of Wireless Communications Foundation under Grant IFN20230201the Fundamental Research Funds for the Central Universities under Grant FRFTP-22-002C2the Xiaomi Fund of Young Scholar。
文摘In the sixth generation mobile communication(6G) system,Non-Terrestrial Networks(NTN),as a supplement to terrestrial network,can meet the requirements of wide area intelligent connection and global ubiquitous seamless access,establish intelligent connection for wide area objects,and provide intelligent services.Due to issues such as massive access,doppler shift,and limited spectrum resources in NTN,research on resource management is crucial for optimizing NTN performance.In this paper,a comprehensive survey of multi-pattern heterogeneous NTN resource management is provided.Firstly,the key technologies involved in NTN resource management is summarized.Secondly,NTN resource management is discussed from network pattern and resource pattern.The network pattern focuses on the application of different optimization methods to different network dimension communication resource management,and the resource type pattern focuses on the research and application of multi-domain resource management such as computation,cache,communication and sensing.Finally,future research directions and challenges of 6G NTN resource management are discussed.
基金Supported by the National Natural Science Foundation of China(42172165,42272143)Project of SINOPEC Science and Technology Department(P24181,KLP24017).
文摘By reviewing the research progress and exploration practices of shale gas geology in China,analyzing and summarizing the geological characteristics,enrichment laws,and resource potential of different types of shale gas,the following understandings have been obtained:(1)Marine,transitional,and lacustrine shales in China are distributed from old to new in geological age,and the complexity of tectonic reworking and hydrocarbon generation evolution processes gradually decreases.(2)The sedimentary environment controls the type of source-reservoir configuration,which is the basis of“hydrocarbon generation and reservoir formation”.The types of source-reservoir configuration in marine and lacustrine shales are mainly source-reservoir integration,with occasional source-reservoir separation.The configuration types of transitional shale are mainly source-reservoir integration and source-reservoir symbiosis.(3)The resistance of rigid minerals to compression for pore preservation and the overpressure facilitate the enrichment of source-reservoir integrated shale gas.Good source reservoir coupling and preservation conditions are crucial for the shale gas enrichment of source-reservoir symbiosis and source-reservoir separation types.(4)Marine shale remains the main battlefield for increasing shale gas reserves and production in China,while transitional and lacustrine shales are expected to become important replacement areas.It is recommended to carry out the shale gas exploration at three levels:Accelerate the exploration of Silurian,Cambrian,and Permian marine shales in the Upper-Middle Yangtze region;make key exploration breakthroughs in ultra-deep marine shales of the Upper-Middle Yangtze region,the new Ordovician marine shale strata in the North China region,the transitional shales of the Carboniferous and Permian,as well as the Mesozoic lacustrine shale gas in basins such as Sichuan,Ordos and Songliao;explore and prepare for new shale gas exploration areas such as South China and Northwest China,providing technology and resource reserves for the sustainable development of shale gas in China.
基金supported by Beijing Natural Science Fund–Haidian Original Innovation Joint Fund(L232040 and L232045).
文摘In this paper,we investigate a multi-UAV aided NOMA communication system,where multiple UAV-mounted aerial base stations are employed to serve ground users in the downlink NOMA communication,and each UAV serves its associated users on its own bandwidth.We aim at maximizing the overall common throughput in a finite time period.Such a problem is a typical mixed integer nonlinear problem,which involves both continuous-variable and combinatorial optimizations.To efficiently solve this problem,we propose a two-layer algorithm,which separately tackles continuous-variable and combinatorial optimization.Specifically,in the inner layer given one user association scheme,subproblems of bandwidth allocation,power allocation and trajectory design are solved based on alternating optimization.In the outer layer,a small number of candidate user association schemes are generated from an initial scheme and the best solution can be determined by comparing all the candidate schemes.In particular,a clustering algorithm based on K-means is applied to produce all candidate user association schemes,the successive convex optimization technique is adopted in the power allocation subproblem and a logistic function approximation approach is employed in the trajectory design subproblem.Simulation results show that the proposed NOMA scheme outperforms three baseline schemes in downlink common throughput,including one solution proposed in an existing literature.
文摘Energy poverty in developing countries is a critical issue characterized by the lack of access to modern energy services,such as electricity and clean cooking facilities,as marked in SDG 7.This study explores the correlations between energy poverty,energy intensity,resource abundance,and income inequality,as these factors have been theorized to play important roles in influencing energy poverty in developing countries.By observing that the dataset is heterogeneous across the countries and over the time frame,we use the Method of Moments Quantile Regression(MMQR)to analyze our developing countries’data from 2000 to 2019.Our findings indicate that energy intensity is a significant factor influencing energy poverty,suggesting that higher energy consumption relative to the sample countries can exacerbate this issue.Additionally,we observe that income inequality within the sample countries is a critical determinant of energy poverty levels,highlighting the dynamics between economic disparity and access to energy resources.Interestingly,our study reveals that resource abundance acts as a blessing rather than a curse in terms of energy poverty,implying that countries rich in natural resources may have better opportunities to combat energy deprivation.Finally,we emphasize the vital role of financial markets in addressing energy poverty on a global scale,suggesting that robust financial systems can facilitate investments and innovations aimed at improving energy access for vulnerable populations.The results from the robustness analysis support the empirical results obtained from the main estimation.The empirical findings of the present study advance important comprehensions for policymakers to adopt energy policies that address the complex challenges of energy poverty and promote inclusive energy access.
基金supported by the National Key Research and Development Program of China (2021YFD1901200)the Key Research and Development Program of Hubei Province of China (2023BBB028)+1 种基金the Earmarked Fund of Hubei province of Chinathe Fundamental Research Funds for the Central Universities (2662024ZKQD005)
文摘The effects of micro-ridge-furrow planting(MR)on yield and the efficiency of light,water,and thermal resource use in rapeseed were tested in a three-year field experiment comparing MR to conventional flat planting.MR enhanced canopy heterogeneity by altering the leaf angle between plants on ridges and furrows.The heterogeneous canopy environment increased intercepted photosynthetic active radiation,alleviated canopy temperature stress,and optimized canopy humidity,leading to improvements in light-nitrogen matching and net photosynthetic rate.Consequently,dry matter and yield increased by 13.0%and 11.0%,respectively,while radiation,thermal,and precipitation utilization efficiency increased by 12.3%-16.2%.The corresponding improvements in yield and resource use efficiency were attributed to a heterogeneous canopy environment that improved microclimatic conditions.
基金financially supported by the Natural Science Foundation of China(No.22162007)the Science and Technology Supporting Project of Guizhou Province(Nos.[2021]480 and[2023]379)+1 种基金Wengfu(Group)Co.,Ltd.Technology Development Project(No.WH-220787(YF))the project from Guizhou Institute of Innovation and development of dual-carbon and new energy technologies(No.DCRE-2023-05)。
文摘Lithium iron phosphate(LiFePO_(4),LFP)batteries have shown extensive adoption in power applications in recent years for their reliable safety,high theoretical capability and low cost.Nevertheless,the finite lifespan of these batteries necessitates the future processing of a significant number of spent LFP batteries,underscoring the urgent need for the development of both efficient and eco-friendly recycling methods.This study combines the advantages of wet leaching and direct regeneration methods,leveraging citric acid's multifaceted role to streamline the combined leaching and hydrothermal processes.Results indicate that citric acid efficiently leaches all elements from spent LFP batteries.Furthermore,through its unique structure,it enhances hydrothermal regeneration by stabilizing metal ions and controlling crystal growth,and also acts as a carbon source for the surface carbon coating of regenerated LFP(RLFP).The R-LFP shows outstanding electrochemical stability,achieving a discharge capacity of 155.1 mAh.g^(-1)at 0.1C,with a capacity retention rate of 93.2%after 300 cycles at 1C.Furthermore,economic and environmental analyses demonstrate this method's superior cost-effectiveness and sustainability.Therefore,the method proposed in this study is efficient,simple and avoids the complex process of element separation,innovatively using a single reagent to achieve closed-loop recycling of LFP batteries,providing a novel and effective solution for the resource sustainability application.
文摘The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.
基金supported by the China Postdoctoral Science Foundation(No.2023T160088)the Youth Fund of the National Natural Science Foundation of China(No.52304324).
文摘Magnesium and magnesium alloys,serving as crucial lightweight structural materials and hydrogen storage elements,find extensive applications in space technology,aviation,automotive,and magnesium-based hydrogen industries.The global production of primary magnesium has reached approximately 1.2 million tons per year,with anticipated diversification in future applications and significant market demand.Nevertheless,approximately 80%of the world’s primary magnesium is still manufactured through the Pidgeon process,grappling with formidable issues including high energy consumption,massive carbon emission,significant resource depletion,and environmental pollution.The implementation of the relative vacuum method shows potential in breaking through technological challenges in the Pidgeon process,facilitating clean,low-carbon continuous magnesium smelting.This paper begins by introducing the principles of the relative vacuum method.Subsequently,it elucidates various innovative process routes,including relative vacuum ferrosilicon reduction,aluminum thermal reduction co-production of spinel,and aluminum thermal reduction co-production of calcium aluminate.Finally,and thermodynamic foundations of the relative vacuum,a quantitative analysis of the material,energy flows,carbon emission,and production cost for several new processes is conducted,comparing and analyzing them against the Pidgeon process.The study findings reveal that,with identical raw materials,the relative vacuum silicon thermal reduction process significantly decreases raw material consumption,energy consumption,and carbon dioxide emissions by 15.86%,30.89%,and 26.27%,respectively,compared to the Pidgeon process.The relative vacuum process,using magnesite as the raw material and aluminum as the reducing agent,has the lowest magnesium-to-feed ratio,at only 3.385.Additionally,its energy consumption and carbon dioxide emissions are the lowest,at 1.817 tce/t Mg and 7.782 t CO_(2)/t Mg,respectively.The energy consumption and carbon emissions of the relative vacuum magnesium smelting process co-producing calcium aluminate(12CaO·7Al_(2)O_(3),3CaO·Al_(2)O_(3),and CaO·Al_(2)O_(3))are highly correlated with the consumption of dolomite in the raw materials.When the reduction temperature is around 1473.15 K,the critical volume fraction of magnesium vapor for different processes varies within the range of 5%–40%.Production cost analysis shows that the relative vacuum primary magnesium smelting process has significant economic benefits.This paper offers essential data support and theoretical guidance for achieving energy efficiency,carbon reduction in magnesium smelting,and the industrial adoption of innovative processes.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
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[Objective]The channel straightening project of the Pinglu Canal has fragmented the river course,compromising the integrity of original river course and causing ecosystem patchiness.Understanding the current status of fish resources and the characteristics of their diversity is crucial for the ecological management of the Pinglu Canal.[Methods]During the spring and autumn in 2021 and 2022,a survey of fish resources and species diversity in the Pinglu Canal was conducted using multi-mesh gill nets.A total of 125 fish species were collected,belonging to 10 orders,34 families,and 89 genera.[Results]The result showed that the Pinglu Canal contained three nationally protected Class II species,two endemic species of the Qinjiang River,three anadromous/migratory species,and eight invasive species,accounting for 2.4%,1.6%,2.4%,and 6.4%of the total species,respectively.The fish community primarily consisted of mid-and bottom-dwelling,adhesive-egg-laying,and omnivorous species.The Shannon-Wiener,Simpson,Margalef,and Pielou indices of the fish community in the Pinglu Canal ranged from 2.347 to 2.757,0.081 to 0.151,3.493 to 4.382,and 0.812 to 0.892,respectively.These indices showed relatively uniform distribution across different river reaches.[Conclusion]The result indicate that the fish community structure in the Pinglu Canal is relatively uniform.The reach from the Yujiang River to the Shaping River shows higher stability,while other river reaches experience moderate or severe disturbances.This study provides supplementary baseline data on the fish community structure in the Pinglu Canal and explores the potential impact of inter-basin connectivity on fish resources,aiming to provide a scientific basis for habitat restoration assessments after the channel straightening project.
基金supported by the Science and Technology Project of State Grid Corporation of China under Grant Number 52094021N010(5400-202199534A-0-5-ZN).
文摘The intelligent operation management of distribution services is crucial for the stability of power systems.Integrating the large language model(LLM)with 6G edge intelligence provides customized management solutions.However,the adverse effects of false data injection(FDI)attacks on the performance of LLMs cannot be overlooked.Therefore,we propose an FDI attack detection and LLM-assisted resource allocation algorithm for 6G edge intelligenceempowered distribution power grids.First,we formulate a resource allocation optimization problem.The objective is to minimize the weighted sum of the global loss function and total LLM fine-tuning delay under constraints of long-term privacy entropy and energy consumption.Then,we decouple it based on virtual queues.We utilize an LLM-assisted deep Q network(DQN)to learn the resource allocation strategy and design an FDI attack detection mechanism to ensure that fine-tuning remains on the correct path.Simulations demonstrate that the proposed algorithm has excellent performance in convergence,delay,and security.
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 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.
