Applying non-orthogonal multiple access(NOMA)to the mobile edge computing(MEC)network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving ...Applying non-orthogonal multiple access(NOMA)to the mobile edge computing(MEC)network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving computing resource constraints and coverage problems.However,the UAV-enabled network has a serious risk of information leakage on account of the openness of wireless channel.This paper considers a UAV-MEC secure network based on NOMA technology,which aims to minimize the UAV energy consumption.To achieve the purpose while meeting the security and users’latency requirements,we formulate an optimization problem that jointly optimizes the UAV trajectory and the allocation of network resources.Given that the original problem is non-convex and multivariate coupled,we proposed an effective algorithm to decouple the nonconvex problem into independent user relation coefficients and subproblems based on successive convex approximation(SCA)and block coordinate descent(BCD).The simulation results showcase the performance of our optimization scheme across various parameter settings and confirm its superiority over other benchmarks with respect to energy consumption.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
Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,th...Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.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
The emergence of multi-access edge computing(MEC)aims at extending cloud computing capabilities to the edge of the radio access network.As the large-scale internet of things(IoT)services are rapidly growing,a single e...The emergence of multi-access edge computing(MEC)aims at extending cloud computing capabilities to the edge of the radio access network.As the large-scale internet of things(IoT)services are rapidly growing,a single edge infrastructure provider(EIP)may not be sufficient to handle the data traffic generated by these services.Most of the existing work addressed the computing resource shortage problem by optimizing tasks schedule,whereas others overcome such issue by placing computing resources on demand.However,when considering a multiple EIPs scenario,an urgent challenge is how to generate a coalition structure to maximize each EIP’s gain with a suitable price for computing resource block corresponding to a container.To this end,we design a scheme of EIPs collaboration with a market price for containers under a scenario that considers a collection of service providers(SPs)with different budgets and several EIPs distributed in geographical locations.First,we bring in the net profit market price model to generate a more reasonable equilibrium price and select the optimal EIPs for each SP by a convex program.Then we use a mathematical model to maximize EIP’s profits and form stable coalitions between EIPs by a distributed coalition formation algorithm.Numerical results demonstrate that our proposed collaborative scheme among EIPs enhances EIPs’gain and increases users’surplus.展开更多
Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e....Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.展开更多
In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allo...In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allowing user equipment(UE)of terrestrial networks to share frequencies with satellite networks.In order to protect the satellite terminal(ST),the base station(BS)needs to control the transmit power and frequency resources of the UE.The optimization problem involves maximizing the achievable throughput while satisfying the interference protection constraints of the ST and the quality of service(QoS)of the UE.However,this problem is highly nonconvex,and we decompose it into power allocation and frequency resource scheduling subproblems.In the power allocation subproblem,we propose a power allocation algorithm based on interference probability(PAIP)to address channel uncertainty.We obtain the suboptimal power allocation solution through iterative optimization.In the frequency resource scheduling subproblem,we develop a heuristic algorithm to handle the non-convexity of the problem.The simulation results show that the combination of power allocation and frequency resource scheduling algorithms can improve spectrum utilization.展开更多
This paper provides an overview of the global wave resource for energy exploration.The most popular metrics and estimators for wave energy resource characterization have been compiled and classified by levels of energ...This paper provides an overview of the global wave resource for energy exploration.The most popular metrics and estimators for wave energy resource characterization have been compiled and classified by levels of energy exploration.A review of existing prospective wave energy resource assessments worldwide is also given,and those studies have been collated and classified by continent.Finally,information about forty existing open sea wave energy test sites worldwide and their characteristics is depicted and displayed on a newly created global map.It has been found that wave power density is still the most consensual metric used for wave energy resource assessment purposes among researchers.Nonetheless,to accomplish a comprehensive wave resource assessment for exploitation,the computation of other metrics at the practicable,technical,and socio-economic levels has also been performed at both spatial and temporal domains.Overall,regions in latitudes between 40°and 60°of both hemispheres are those where the highest wave power density is concentrated.Some areas where the most significant wave power density occurs are in offshore regions of southern Australia,New Zealand,South Africa,Chile,the British Isles,Iceland,and Greenland.However,Europe has been the continent where most research efforts have been done targeting wave energy characterisation for exploitation.展开更多
Wells CXD1 and CX2 have uncovered high-concentration potassium-and lithium-containing brines and substantial layers of halite-type polyhalite potash deposits within the 4th and 5th members of the Triassic Jialingjiang...Wells CXD1 and CX2 have uncovered high-concentration potassium-and lithium-containing brines and substantial layers of halite-type polyhalite potash deposits within the 4th and 5th members of the Triassic Jialingjiang Formation and the 1st Member of Leikoupo Formation(Jia 4 Member,Jia 5 Member,and Lei 1 Member)in the Puguang area,Sichuan Basin.These discoveries mark significant breakthroughs in the exploration of deep marine potassium and lithium resources within the Sichuan Basin.Utilizing the concept of“gas-potassium-lithium integrated exploration”and incorporating drilling,logging,seismic,and geochemical data,we have investigated the geological and enrichment conditions,as well as the metallogenic model of potassium-rich and lithium-rich brines and halite-type polyhalite.First,the sedimentary systems of gypsum-dolomite flats,salt lakes and evaporated flats were developed in Jia 4 Member,Jia 5 Member,and the 1st member of Leikoupo Formation(Lei 1 Member)in northeastern Sichuan Basin,forming three large-scale salt-gathering and potassium formation centers in Puguang,Tongnanba and Yuanba,and developing reservoirs with potassium-rich and lithium-rich brines,which are favorable for the deposition of potassium and lithium resources in both solid or liquid phases.Second,the soluble halite-type polyhalite has a large thickness and wide distribution,and the reservoir brine has a high content of K+and Li+.A solid-liquid superimposed“three-story structure”(with the lower thin-layer of brine reservoir in lower part of Jia 4 Member and Jia 5 Member,middle layer of halite-type polyhalite potash depositS,upper layer of potassium-rich and lithium-rich brine reservoir in Lei 1 Member)is formed.Third,the ternary enrichment and mineralization patterns for potassium and lithium resources were determined.Vertical superposition of polyhalite and green bean rocks is the mineral material basis of potassium-lithium resources featuring“dual-source replenishment and proximal-source release”,with primary seawater and gypsum dehydration as the main sources of deep brines,while multi-stage tectonic modification is the key to the enrichment of halite-type polyhalite and potassiumlithium brines.Fourth,the ore-forming process has gone through four stages:salt-gathering and potassium-lithium accumulation period,initial water-rock reaction period,transformation and aggregation period,and enrichment and finalization period.During this process,the halite-type polyhalite layer in Jia 4 Member and Jia 5 Member is the main target for potassium solution mining,while the brine layer in Lei 1 Member is the focus of comprehensive potassium-lithium exploration and development.展开更多
Low earth orbit(LEO)satellites with wide coverage can carry the mobile edge computing(MEC)servers with powerful computing capabilities to form the LEO satellite edge computing system,providing computing services for t...Low earth orbit(LEO)satellites with wide coverage can carry the mobile edge computing(MEC)servers with powerful computing capabilities to form the LEO satellite edge computing system,providing computing services for the global ground users.In this paper,the computation offloading problem and resource allocation problem are formulated as a mixed integer nonlinear program(MINLP)problem.This paper proposes a computation offloading algorithm based on deep deterministic policy gradient(DDPG)to obtain the user offloading decisions and user uplink transmission power.This paper uses the convex optimization algorithm based on Lagrange multiplier method to obtain the optimal MEC server resource allocation scheme.In addition,the expression of suboptimal user local CPU cycles is derived by relaxation method.Simulation results show that the proposed algorithm can achieve excellent convergence effect,and the proposed algorithm significantly reduces the system utility values at considerable time cost compared with other algorithms.展开更多
Networked robots can perceive their surroundings, interact with each other or humans,and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle(UAV) net...Networked robots can perceive their surroundings, interact with each other or humans,and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle(UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links,via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener’s Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage,enabling new orchestration between network serving and positive mobility control of robots. Moreover,the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing(MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.展开更多
With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of...With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of the aircraft play an important role in the judgment and command of the Operational Control Center(OCC). However, how to transmit various operational status data from abnormal aircraft back to the OCC in an emergency is still an open problem. In this paper, we propose a novel Telemetry, Tracking,and Command(TT&C) architecture named Collaborative TT&C(CoTT&C) based on mega-constellation to solve such a problem. CoTT&C allows each satellite to help the abnormal aircraft by sharing TT&C resources when needed, realizing real-time and reliable aeronautical communication in an emergency. Specifically, we design a dynamic resource sharing mechanism for CoTT&C and model the mechanism as a single-leader-multi-follower Stackelberg game. Further, we give an unique Nash Equilibrium(NE) of the game as a closed form. Simulation results demonstrate that the proposed resource sharing mechanism is effective, incentive compatible, fair, and reciprocal. We hope that our findings can shed some light for future research on aeronautical communications in an emergency.展开更多
Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus t...Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.展开更多
Low earth orbit(LEO) satellite communications can provide ubiquitous and reliable services,making it an essential part of the Internet of Everything network. Beam hopping(BH) is an emerging technology for effectively ...Low earth orbit(LEO) satellite communications can provide ubiquitous and reliable services,making it an essential part of the Internet of Everything network. Beam hopping(BH) is an emerging technology for effectively addressing the issue of low resource utilization caused by the non-uniform spatio-temporal distribution of traffic demands. However, how to allocate multi-dimensional resources in a timely and efficient way for the highly dynamic LEO satellite systems remains a challenge. This paper proposes a joint beam scheduling and power optimization beam hopping(JBSPO-BH) algorithm considering the differences in the geographic distribution of sink nodes. The JBSPO-BH algorithm decouples the original problem into two sub-problems. The beam scheduling problem is modelled as a potential game,and the Nash equilibrium(NE) point is obtained as the beam scheduling strategy. Moreover, the penalty function interior point method is applied to optimize the power allocation. Simulation results show that the JBSPO-BH algorithm has low time complexity and fast convergence and achieves better performance both in throughput and fairness. Compared with greedybased BH, greedy-based BH with the power optimization, round-robin BH, Max-SINR BH and satellite resource allocation algorithm, the throughput of the proposed algorithm is improved by 44.99%, 20.79%,156.06%, 15.39% and 8.17%, respectively.展开更多
The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this...The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)relay.First,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the relay.The original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution directly.First,we use fractional programming to convert the EE maximization problem as a series of subtraction form subproblems.Then,variable substitution and block coordinate descent(BCD)method are used to handle the sub-problems.Next,a resource allocation algorithm is proposed to maximize the EE of the systems.Finally,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.展开更多
Tree allometry plays a crucial role in tree survival,stability,and timber quantity and quality of mixed-species plantations.However,the responses of tree allometry to resource utilisation within the framework of inter...Tree allometry plays a crucial role in tree survival,stability,and timber quantity and quality of mixed-species plantations.However,the responses of tree allometry to resource utilisation within the framework of interspecific competition and complementarity remain poorly understood.Taking into consideration strong-and weakspace competition(SC and WC),as well as N_(2)-fixing and non-N_(2)-fixing tree species(FN and nFN),a mixedspecies planting trial was conducted for Betula alnoides,a pioneer tree species,which was separately mixed with Acacia melanoxylon(SC+FN),Erythrophleum fordii(WC+FN),Eucalyptus cloeziana(SC+nFN)and Pinus kesiya var.langbianensis(WC+nFN)in southern China.Six years after planting,tree growth,total nitrogen(N)and carbon(C)contents,and the natural abundances of^(15)N and^(13)C in the leaves were measured for each species,and the mycorrhizal colonisation rates of B.alnoides were investigated under each treatment.Allometric variations and their relationships with space competition and nutrient-related factors were analyzed.The results showed a consistent effect of space competition on the height-diameter relationship of B.alnoides in mixtures with FN or nFN.The tree height growth of B.alnoides was significantly promoted under high space competition,and growth in diameter at breast height(DBH),tree height and crown size were all expedited in mixtures with FN.The symbiotic relationship between ectomycorrhizal fungi and B.alnoides was significantly influenced by both space competition and N_(2) fixation by the accompanying tree species,whereas such significant effects were absent for arbuscular mycorrhizal fungi.Furthermore,high space competition significantly decreased the water use efficiency(WUE)of B.alnoides,and its N use efficiency(NUE)was much lower in the FN mixtures.Structural equation modeling further demonstrated that the stem allometry of B.alnoides was affected by its NUE and WUE via changes in its height growth,and crown allometry was influenced by the mycorrhizal symbiotic relationship.Our findings provide new insights into the mechanisms driving tree allometric responses to above-and belowground resource competition and complementarity in mixed-species plantations,which are instructive for the establishment of mixed-species plantations.展开更多
Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.Howev...Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.However,to date,all these technologies have been applied in isola-tion.This paper introduces the latest fire detection and sup-pression technologies from ground to space.An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppres-sion.The framework harnesses the advantages of satellite-based,drone,sensor,and human reporting technologies as well as image processing and artificial intelligence machine learning.The study concludes that,if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements,a fire detection and resource suppression system can achieve the ultimate aim:to reduce the risk of fire hazards and the dam-age they may cause.展开更多
The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power suppor...The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power support,which is an important development direction of future communications.In this paper,we take into account a multi-scenario network model under the coverage of low earth orbit(LEO)satellite,which can provide computing resources to users in faraway areas to improve task processing efficiency.However,LEO satellites experience limitations in computing and communication resources and the channels are time-varying and complex,which makes the extraction of state information a daunting task.Therefore,we explore the dynamic resource management issue pertaining to joint computing,communication resource allocation and power control for multi-access edge computing(MEC).In order to tackle this formidable issue,we undertake the task of transforming the issue into a Markov decision process(MDP)problem and propose the self-attention based dynamic resource management(SABDRM)algorithm,which effectively extracts state information features to enhance the training process.Simulation results show that the proposed algorithm is capable of effectively reducing the long-term average delay and energy consumption of the tasks.展开更多
Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus t...Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.展开更多
Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully...Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 61971474in part by the National Natural Science Foundation of China under Grant 62301594+2 种基金in part by the Special Funds of the National Natural Science Foundation of China under Grant 62341112in part by the Beijing Nova Program under Grant Z201100006820121in part by the Beijing Municipal Science and Technology Project under Grant Z181100003218015.
文摘Applying non-orthogonal multiple access(NOMA)to the mobile edge computing(MEC)network supported by unmanned aerial vehicles(UAVs)can improve spectral efficiency and achieve massive user access on the basis of solving computing resource constraints and coverage problems.However,the UAV-enabled network has a serious risk of information leakage on account of the openness of wireless channel.This paper considers a UAV-MEC secure network based on NOMA technology,which aims to minimize the UAV energy consumption.To achieve the purpose while meeting the security and users’latency requirements,we formulate an optimization problem that jointly optimizes the UAV trajectory and the allocation of network resources.Given that the original problem is non-convex and multivariate coupled,we proposed an effective algorithm to decouple the nonconvex problem into independent user relation coefficients and subproblems based on successive convex approximation(SCA)and block coordinate descent(BCD).The simulation results showcase the performance of our optimization scheme across various parameter settings and confirm its superiority over other benchmarks with respect to energy consumption.
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.
基金supported by the Science and Technology Project of the State Grid Corporation of China(5400-202255158A-1-1-ZN).
文摘Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.
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 National Natural Science Foundation of China(No.6206020135)Key Research and Development Program of Gansu Province(No.20YF8GA123)+1 种基金Gansu Provincial Department of Education University Faculty Innovation Fund Project(No.2024B-059)Youth Science Fund Project of Lanzhou Jiaotong University(No.1200061307).
文摘The emergence of multi-access edge computing(MEC)aims at extending cloud computing capabilities to the edge of the radio access network.As the large-scale internet of things(IoT)services are rapidly growing,a single edge infrastructure provider(EIP)may not be sufficient to handle the data traffic generated by these services.Most of the existing work addressed the computing resource shortage problem by optimizing tasks schedule,whereas others overcome such issue by placing computing resources on demand.However,when considering a multiple EIPs scenario,an urgent challenge is how to generate a coalition structure to maximize each EIP’s gain with a suitable price for computing resource block corresponding to a container.To this end,we design a scheme of EIPs collaboration with a market price for containers under a scenario that considers a collection of service providers(SPs)with different budgets and several EIPs distributed in geographical locations.First,we bring in the net profit market price model to generate a more reasonable equilibrium price and select the optimal EIPs for each SP by a convex program.Then we use a mathematical model to maximize EIP’s profits and form stable coalitions between EIPs by a distributed coalition formation algorithm.Numerical results demonstrate that our proposed collaborative scheme among EIPs enhances EIPs’gain and increases users’surplus.
基金the financial support of the National Key Research and Development Plan(2021YFB3302501)the financial support of the National Natural Science Foundation of China(12102077)。
文摘Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.
基金funded by State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster under Grant MS01240103the National Natural Science Foundation of China under Grant 62071146National 2011 Collaborative Innovation Center of Wireless Communication Technologies under Grant 2242022k60006.
文摘In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allowing user equipment(UE)of terrestrial networks to share frequencies with satellite networks.In order to protect the satellite terminal(ST),the base station(BS)needs to control the transmit power and frequency resources of the UE.The optimization problem involves maximizing the achievable throughput while satisfying the interference protection constraints of the ST and the quality of service(QoS)of the UE.However,this problem is highly nonconvex,and we decompose it into power allocation and frequency resource scheduling subproblems.In the power allocation subproblem,we propose a power allocation algorithm based on interference probability(PAIP)to address channel uncertainty.We obtain the suboptimal power allocation solution through iterative optimization.In the frequency resource scheduling subproblem,we develop a heuristic algorithm to handle the non-convexity of the problem.The simulation results show that the combination of power allocation and frequency resource scheduling algorithms can improve spectrum utilization.
文摘This paper provides an overview of the global wave resource for energy exploration.The most popular metrics and estimators for wave energy resource characterization have been compiled and classified by levels of energy exploration.A review of existing prospective wave energy resource assessments worldwide is also given,and those studies have been collated and classified by continent.Finally,information about forty existing open sea wave energy test sites worldwide and their characteristics is depicted and displayed on a newly created global map.It has been found that wave power density is still the most consensual metric used for wave energy resource assessment purposes among researchers.Nonetheless,to accomplish a comprehensive wave resource assessment for exploitation,the computation of other metrics at the practicable,technical,and socio-economic levels has also been performed at both spatial and temporal domains.Overall,regions in latitudes between 40°and 60°of both hemispheres are those where the highest wave power density is concentrated.Some areas where the most significant wave power density occurs are in offshore regions of southern Australia,New Zealand,South Africa,Chile,the British Isles,Iceland,and Greenland.However,Europe has been the continent where most research efforts have been done targeting wave energy characterisation for exploitation.
基金Supported by the National Research and Development Program(2017YFC0602804)Geological Bureau Program of Sichuan Province(SCDZ-KJXM202403).
文摘Wells CXD1 and CX2 have uncovered high-concentration potassium-and lithium-containing brines and substantial layers of halite-type polyhalite potash deposits within the 4th and 5th members of the Triassic Jialingjiang Formation and the 1st Member of Leikoupo Formation(Jia 4 Member,Jia 5 Member,and Lei 1 Member)in the Puguang area,Sichuan Basin.These discoveries mark significant breakthroughs in the exploration of deep marine potassium and lithium resources within the Sichuan Basin.Utilizing the concept of“gas-potassium-lithium integrated exploration”and incorporating drilling,logging,seismic,and geochemical data,we have investigated the geological and enrichment conditions,as well as the metallogenic model of potassium-rich and lithium-rich brines and halite-type polyhalite.First,the sedimentary systems of gypsum-dolomite flats,salt lakes and evaporated flats were developed in Jia 4 Member,Jia 5 Member,and the 1st member of Leikoupo Formation(Lei 1 Member)in northeastern Sichuan Basin,forming three large-scale salt-gathering and potassium formation centers in Puguang,Tongnanba and Yuanba,and developing reservoirs with potassium-rich and lithium-rich brines,which are favorable for the deposition of potassium and lithium resources in both solid or liquid phases.Second,the soluble halite-type polyhalite has a large thickness and wide distribution,and the reservoir brine has a high content of K+and Li+.A solid-liquid superimposed“three-story structure”(with the lower thin-layer of brine reservoir in lower part of Jia 4 Member and Jia 5 Member,middle layer of halite-type polyhalite potash depositS,upper layer of potassium-rich and lithium-rich brine reservoir in Lei 1 Member)is formed.Third,the ternary enrichment and mineralization patterns for potassium and lithium resources were determined.Vertical superposition of polyhalite and green bean rocks is the mineral material basis of potassium-lithium resources featuring“dual-source replenishment and proximal-source release”,with primary seawater and gypsum dehydration as the main sources of deep brines,while multi-stage tectonic modification is the key to the enrichment of halite-type polyhalite and potassiumlithium brines.Fourth,the ore-forming process has gone through four stages:salt-gathering and potassium-lithium accumulation period,initial water-rock reaction period,transformation and aggregation period,and enrichment and finalization period.During this process,the halite-type polyhalite layer in Jia 4 Member and Jia 5 Member is the main target for potassium solution mining,while the brine layer in Lei 1 Member is the focus of comprehensive potassium-lithium exploration and development.
基金supported by National Natural Science Foundation of China No.62231012Natural Science Foundation for Outstanding Young Scholars of Heilongjiang Province under Grant YQ2020F001Heilongjiang Province Postdoctoral General Foundation under Grant AUGA4110004923.
文摘Low earth orbit(LEO)satellites with wide coverage can carry the mobile edge computing(MEC)servers with powerful computing capabilities to form the LEO satellite edge computing system,providing computing services for the global ground users.In this paper,the computation offloading problem and resource allocation problem are formulated as a mixed integer nonlinear program(MINLP)problem.This paper proposes a computation offloading algorithm based on deep deterministic policy gradient(DDPG)to obtain the user offloading decisions and user uplink transmission power.This paper uses the convex optimization algorithm based on Lagrange multiplier method to obtain the optimal MEC server resource allocation scheme.In addition,the expression of suboptimal user local CPU cycles is derived by relaxation method.Simulation results show that the proposed algorithm can achieve excellent convergence effect,and the proposed algorithm significantly reduces the system utility values at considerable time cost compared with other algorithms.
基金supported in part by the National Key Research and Development Program of China (Grant No.2020YFA0711301)in part by the National Natural Science Foundation of China (Grant No.62341110 and U22A2002)in part by the Suzhou Science and Technology Project。
文摘Networked robots can perceive their surroundings, interact with each other or humans,and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle(UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links,via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener’s Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage,enabling new orchestration between network serving and positive mobility control of robots. Moreover,the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing(MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.
基金supported by the National Natural Science Foundation of China under Grant 62131012/61971261。
文摘With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of the aircraft play an important role in the judgment and command of the Operational Control Center(OCC). However, how to transmit various operational status data from abnormal aircraft back to the OCC in an emergency is still an open problem. In this paper, we propose a novel Telemetry, Tracking,and Command(TT&C) architecture named Collaborative TT&C(CoTT&C) based on mega-constellation to solve such a problem. CoTT&C allows each satellite to help the abnormal aircraft by sharing TT&C resources when needed, realizing real-time and reliable aeronautical communication in an emergency. Specifically, we design a dynamic resource sharing mechanism for CoTT&C and model the mechanism as a single-leader-multi-follower Stackelberg game. Further, we give an unique Nash Equilibrium(NE) of the game as a closed form. Simulation results demonstrate that the proposed resource sharing mechanism is effective, incentive compatible, fair, and reciprocal. We hope that our findings can shed some light for future research on aeronautical communications in an emergency.
基金supported in part by the National Key R&D Program of China under Grant 2020YFB1005900the National Natural Science Foundation of China under Grant 62001220+3 种基金the Jiangsu Provincial Key Research and Development Program under Grants BE2022068the Natural Science Foundation of Jiangsu Province under Grants BK20200440the Future Network Scientific Research Fund Project FNSRFP-2021-YB-03the Young Elite Scientist Sponsorship Program,China Association for Science and Technology.
文摘Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.
基金supported by the National Key Research and Development Program of China 2021YFB2900504, 2020YFB1807900。
文摘Low earth orbit(LEO) satellite communications can provide ubiquitous and reliable services,making it an essential part of the Internet of Everything network. Beam hopping(BH) is an emerging technology for effectively addressing the issue of low resource utilization caused by the non-uniform spatio-temporal distribution of traffic demands. However, how to allocate multi-dimensional resources in a timely and efficient way for the highly dynamic LEO satellite systems remains a challenge. This paper proposes a joint beam scheduling and power optimization beam hopping(JBSPO-BH) algorithm considering the differences in the geographic distribution of sink nodes. The JBSPO-BH algorithm decouples the original problem into two sub-problems. The beam scheduling problem is modelled as a potential game,and the Nash equilibrium(NE) point is obtained as the beam scheduling strategy. Moreover, the penalty function interior point method is applied to optimize the power allocation. Simulation results show that the JBSPO-BH algorithm has low time complexity and fast convergence and achieves better performance both in throughput and fairness. Compared with greedybased BH, greedy-based BH with the power optimization, round-robin BH, Max-SINR BH and satellite resource allocation algorithm, the throughput of the proposed algorithm is improved by 44.99%, 20.79%,156.06%, 15.39% and 8.17%, respectively.
基金partially supported by the National Natural Science Foundation of China under Grant 61701064Chongqing Natural Science Foundation under Grant cstc2019jcyj-msxmX0264Sichuan Science and Technology Program under Grant 2022YFQ0017。
文摘The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)relay.First,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the relay.The original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution directly.First,we use fractional programming to convert the EE maximization problem as a series of subtraction form subproblems.Then,variable substitution and block coordinate descent(BCD)method are used to handle the sub-problems.Next,a resource allocation algorithm is proposed to maximize the EE of the systems.Finally,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.
基金supported by National Natural Science Foundation of China (31972949)National Nonprofit Institute Research Grant of Chinese Academy of Forestry,China (CAFYBB2023MB006)。
文摘Tree allometry plays a crucial role in tree survival,stability,and timber quantity and quality of mixed-species plantations.However,the responses of tree allometry to resource utilisation within the framework of interspecific competition and complementarity remain poorly understood.Taking into consideration strong-and weakspace competition(SC and WC),as well as N_(2)-fixing and non-N_(2)-fixing tree species(FN and nFN),a mixedspecies planting trial was conducted for Betula alnoides,a pioneer tree species,which was separately mixed with Acacia melanoxylon(SC+FN),Erythrophleum fordii(WC+FN),Eucalyptus cloeziana(SC+nFN)and Pinus kesiya var.langbianensis(WC+nFN)in southern China.Six years after planting,tree growth,total nitrogen(N)and carbon(C)contents,and the natural abundances of^(15)N and^(13)C in the leaves were measured for each species,and the mycorrhizal colonisation rates of B.alnoides were investigated under each treatment.Allometric variations and their relationships with space competition and nutrient-related factors were analyzed.The results showed a consistent effect of space competition on the height-diameter relationship of B.alnoides in mixtures with FN or nFN.The tree height growth of B.alnoides was significantly promoted under high space competition,and growth in diameter at breast height(DBH),tree height and crown size were all expedited in mixtures with FN.The symbiotic relationship between ectomycorrhizal fungi and B.alnoides was significantly influenced by both space competition and N_(2) fixation by the accompanying tree species,whereas such significant effects were absent for arbuscular mycorrhizal fungi.Furthermore,high space competition significantly decreased the water use efficiency(WUE)of B.alnoides,and its N use efficiency(NUE)was much lower in the FN mixtures.Structural equation modeling further demonstrated that the stem allometry of B.alnoides was affected by its NUE and WUE via changes in its height growth,and crown allometry was influenced by the mycorrhizal symbiotic relationship.Our findings provide new insights into the mechanisms driving tree allometric responses to above-and belowground resource competition and complementarity in mixed-species plantations,which are instructive for the establishment of mixed-species plantations.
基金supported by the National Institute for Forest Products Innovation (NIFPI) Australia (Project No. NS034),titled Scoping an Automated Forest Fire Detection and Suppression Framework for the Green Triangle.
文摘Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.However,to date,all these technologies have been applied in isola-tion.This paper introduces the latest fire detection and sup-pression technologies from ground to space.An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppres-sion.The framework harnesses the advantages of satellite-based,drone,sensor,and human reporting technologies as well as image processing and artificial intelligence machine learning.The study concludes that,if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements,a fire detection and resource suppression system can achieve the ultimate aim:to reduce the risk of fire hazards and the dam-age they may cause.
基金supported by the National Key Research and Development Plan(No.2022YFB2902701)the key Natural Science Foundation of Shenzhen(No.JCYJ20220818102209020).
文摘The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power support,which is an important development direction of future communications.In this paper,we take into account a multi-scenario network model under the coverage of low earth orbit(LEO)satellite,which can provide computing resources to users in faraway areas to improve task processing efficiency.However,LEO satellites experience limitations in computing and communication resources and the channels are time-varying and complex,which makes the extraction of state information a daunting task.Therefore,we explore the dynamic resource management issue pertaining to joint computing,communication resource allocation and power control for multi-access edge computing(MEC).In order to tackle this formidable issue,we undertake the task of transforming the issue into a Markov decision process(MDP)problem and propose the self-attention based dynamic resource management(SABDRM)algorithm,which effectively extracts state information features to enhance the training process.Simulation results show that the proposed algorithm is capable of effectively reducing the long-term average delay and energy consumption of the tasks.
基金This work was supported in part by the National Key R&D Program of China under Grant 2020YFB1005900the National Natural Science Foundation of China under Grant 62001220+3 种基金the Jiangsu Provincial Key Research and Development Program under Grants BE2022068the Natural Science Foundation of Jiangsu Province under Grants BK20200440the Future Network Scientific Research Fund Project FNSRFP-2021-YB-03the Young Elite Scientist Sponsorship Program,China Association for Science and Technology.
文摘Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.
基金supported by the National Technology Extension Fund of Forestry,Forest Vegetation Carbon Storage Monitoring Technology Based on Watershed Algorithm ([2019]06)Fundamental Research Funds for the Central Universities (No.PTYX202107).
文摘Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.
