Shared manufacturing is recognized as a new point-to-point manufac-turing mode in the digital era.Shared manufacturing is referred to as a new man-ufacturing mode to realize the dynamic allocation of manufacturing tas...Shared manufacturing is recognized as a new point-to-point manufac-turing mode in the digital era.Shared manufacturing is referred to as a new man-ufacturing mode to realize the dynamic allocation of manufacturing tasks and resources.Compared with the traditional mode,shared manufacturing offers more abundant manufacturing resources and flexible configuration options.This paper proposes a model based on the description of the dynamic allocation of tasks and resources in the shared manufacturing environment,and the characteristics of shared manufacturing resource allocation.The execution of manufacturing tasks,in which candidate manufacturing resources enter or exit at various time nodes,enables the dynamic allocation of manufacturing tasks and resources.Then non-dominated sorting genetic algorithm(NSGA-II)and multi-objective particle swarm optimization(MOPSO)algorithms are designed to solve the model.The optimal parameter settings for the NSGA-II and MOPSO algorithms have been obtained according to the experiments with various population sizes and iteration numbers.In addition,the proposed model’s efficiency,which considers the entries and exits of manufacturing resources in the shared manufacturing environment,is further demonstrated by the overlap between the outputs of the NSGA-II and MOPSO algorithms for optimal resource allocation.展开更多
Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinfor...Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA.The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the algorithm.Finally,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air confrontation.The experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision space.The MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.展开更多
To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlin...To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.展开更多
Non-orthogonal multiple access(NOMA)represents the latest addition to the array of multiple access techniques,enabling simultaneous servicing of multiple users within a singular resource block in terms of time,frequen...Non-orthogonal multiple access(NOMA)represents the latest addition to the array of multiple access techniques,enabling simultaneous servicing of multiple users within a singular resource block in terms of time,frequency,and code.A typical NOMA configuration comprises a base station along with proximate and distant users.The proximity users experience more favorable channel conditions in contrast to distant users,resulting in a compromised performance for the latter due to the less favorable channel conditions.When cooperative communication is integrated with NOMA,the overall system performance,including spectral efficiency and capacity,is further elevated.This study introduces a cooperative NOMA setup in the downlink,involving three users,and employs dynamic power allocation(DPA).Within this framework,User 2 acts as a relay,functioning under the decode-and-forward protocol,forwarding signals to both User 1 and User 3.This arrangement aims to bolster the performance of the user positioned farthest from the base station,who is adversely affected by weaker channel conditions.Theoretical and simulation outcomes reveal enhancements within the system’s performance.展开更多
To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm allowing a single link to use far beyond its fair...To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm allowing a single link to use far beyond its fair share bandwidth is presented. Three important parameters as the bound on max and minimum bandwidth, the maximum packet delay and the minimum bandwidth utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system use all the spare bandwidth (up to full-bandwidth) while the performance of fairness and QoS requirement is still guaranteed.展开更多
This paper presents a novel model for dynamic bandwidth allocation and rate coordination based on DiffServ and a bandwidth broker(BB). In this model, assignment of bandwidth was made according to a periodic trace of...This paper presents a novel model for dynamic bandwidth allocation and rate coordination based on DiffServ and a bandwidth broker(BB). In this model, assignment of bandwidth was made according to a periodic trace of network characteristics per application. And adjustment of transfer rate was accomplished through negotiation with applications by a bandwidth agent. This model was evaluated using network simulator 2 (NS-2), and distinct improvements were found in respects of delay and packet loss of overall network and single flow. Finally, the model was suggested to be leveraged to multimedia applications with properties of lower delay and lower packet loss.展开更多
Mobile Edge Computing(MEC)has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices.In this paper,we investigate the optimal dynamic spectrum all...Mobile Edge Computing(MEC)has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices.In this paper,we investigate the optimal dynamic spectrum allocation-assisted multiuser computation offloading in MEC for overall latency minimization.Specifically,we first focus on a static multiuser computation offloading scenario and jointly optimize users'offloading decisions,transmission durations,and Edge Servers'(ESs)resource allocations.Owing to the nonconvexity of our joint optimization problem,we identify its layered structure and decompose it into two problems:a subproblem and a top problem.For the subproblem,we propose a bisection search-based algorithm to efficiently find the optimal users'offloading decisions and ESs’resource allocations under a given transmission duration.Second,we use a linear search-based algorithm for solving the top problem to obtain the optimal transmission duration based on the result of the subproblem.Further,after solving the static scenario,we consider a dynamic scenario of multiuser computation offloading with time-varying channels and workload.To efficiently address this dynamic scenario,we propose a deep reinforcement learning-based online algorithm to determine the near-optimal transmission duration in a real-time manner.Numerical results are provided to validate our proposed algorithms for minimizing the overall latency in both static and dynamic offloading scenarios.We also demonstrate the advantages of our proposed algorithms compared to the conventional multiuser computation offloading schemes.展开更多
The passive optical network(PON)technology has been drastically improved in recent years.In spite of using the optical technology,the utilization of the entire bandwidth is a very challenging task.The main categories ...The passive optical network(PON)technology has been drastically improved in recent years.In spite of using the optical technology,the utilization of the entire bandwidth is a very challenging task.The main categories of PON are the Ethernet passive optical network(EPON)and gigabit passive optical network(GPON).These two networks use the dynamic bandwidth allocation(DBA)algorithm to attain the maximum usage of bandwidth,which is provided in the network dynamically according to the need of the customers with the support of the service level agreement(SLA).This paper will provide a clear review about the DBA algorithm of both technologies as well as the comparison。展开更多
As the traffic distribution in China mainland is far from uniform, a new traffic model in China mainland is presented on the basis of per-capita Gross Domestic Product (GDP) and density of population. Based on this ch...As the traffic distribution in China mainland is far from uniform, a new traffic model in China mainland is presented on the basis of per-capita Gross Domestic Product (GDP) and density of population. Based on this characteristic traffic model, a new Traffic Dependent Dynamic Channel Allocation and Reservation (TDDCAR) technique is proposed, the simulation model is built, and the strategies' performance is evaluated through computer simulation. The simulation results show that, compared to the conventional Fixed Channel Allocation (FCA), TDDCAR estimates the traffic conditions in every spot beam and frequently adjusts the traffic according to current traffic conditions. It has achieved a significant improvement in new call blocking probability, handover blocking probability, and fair index, particularly, in heavy traffic conditions. The building of traffic model in China mainland and the analysis of the simulation results has been a key foundation for the study of resource allocation schemes in the future.展开更多
A realistic population density distribution scenario in conjunction with the spatial dynamic spectrum allocation (DSA) is taken into account to mitigate the spectrum wastage in terms of extra guard bands. For the in...A realistic population density distribution scenario in conjunction with the spatial dynamic spectrum allocation (DSA) is taken into account to mitigate the spectrum wastage in terms of extra guard bands. For the insertion of the extra guard bands, an efficient strategy based on self-assessment is applied to each victim cell individually and independently. Consequently, it is no more required to spread the extra guard band over the whole DSA region. Simulation results StlOW an improvement of 3% -4% in percentage of satisfied users for Universal Mobile Telecommunications System (UMTS) network and 4%-5% for Digital Video Broadcasting Terrestrial (DVB-T) network.展开更多
With the rapid development of wireless network technologies and the growing de⁃mand for a high quality of service(QoS),the effective management of network resources has attracted a lot of attention.For example,in a pr...With the rapid development of wireless network technologies and the growing de⁃mand for a high quality of service(QoS),the effective management of network resources has attracted a lot of attention.For example,in a practical scenario,when a network shock oc⁃curs,a batch of affected flows needs to be rerouted to respond to the network shock to bring the entire network deployment back to the optimal state,and in the process of rerouting a batch of flows,the entire response time needs to be as short as possible.Specifically,we re⁃duce the time consumed for routing by slicing,but the routing success rate after slicing is re⁃duced compared with the unsliced case.In this context,we propose a two-stage dynamic net⁃work resource allocation framework that first makes decisions on the slices to which flows are assigned,and coordinates resources among slices to ensure a comparable routing suc⁃cess rate as in the unsliced case,while taking advantage of the time efficiency gains from slicing.展开更多
It is known that dynamic channel assignment(D CA ) strategy outperforms the fixed channel assignment(FCA) strategy in omni-direc tional antenna cellular systems. One of the most important methods used in DCA w as chan...It is known that dynamic channel assignment(D CA ) strategy outperforms the fixed channel assignment(FCA) strategy in omni-direc tional antenna cellular systems. One of the most important methods used in DCA w as channel borrowing. But with the emergence of cell sectorization and spatial d ivision multiple access(SDMA) which are used to increase the capacity of cel lular systems, the channel assignment faces a series of new problems. In this pa per, a dynamic channel allocation scheme based on sectored cellular systems is p roposed. By introducing intra-cell channel borrowing (borrowing channels from n eighboring sectors) and inter-cell channel borrowing (borrowing channels from n eighboring cells) methods, previous DCA strategies, including compact pattern ba sed channel borrowing(CPCB) and greedy based dynamic channel assignment(GDCA) schemes proposed by the author, are improved significantly. The computer simu lation shows that either intra-cell borrowing scheme or inter-cell borrowing s cheme is efficient enough to uniform and non-uniform traffic service distributi ons.展开更多
The Ethernet passive optical network(EPON) is the next generation of broad-band network technique.A crucial issue in EPONs is the sharing of uplink bandwidth among optical network units(ONUs).This article provides a n...The Ethernet passive optical network(EPON) is the next generation of broad-band network technique.A crucial issue in EPONs is the sharing of uplink bandwidth among optical network units(ONUs).This article provides a novel dynamic bandwidth allocation algorithm,i.e.threshold dynamic bandwidth allocation(TDBA),which is based on adaptive threshold,to increase resource utilization.The algorithm uses ONU data-transmitting rate to adjust optical line terminal(OLT) receiving data threshold from an ONU.Simulation results show that this algorithm can decrease average packet delay and increase network throughput in a 10G EPON system.展开更多
Network virtualization can effectively establish dedicated virtual networks to implement various network functions.However,the existing research works have some shortcomings,for example,although computing resource pro...Network virtualization can effectively establish dedicated virtual networks to implement various network functions.However,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and priority.In addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation redundancy.Based on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology properties.In the node mapping process,three properties of the node are used to measure its mapping ability.Second,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link mapping.Finally,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource allocation.The former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision probability.Simulation results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenue by 15%and 38%,and reduce the network cost and link pressure by 25%and 17%.展开更多
This paper presents an efficient dynamic spectrum allocation (DSA) scheme in a flexible spectrum licensing environment where multiple networks coexist and interfere with each other. In particular, an extension of vi...This paper presents an efficient dynamic spectrum allocation (DSA) scheme in a flexible spectrum licensing environment where multiple networks coexist and interfere with each other. In particular, an extension of virtual boundary concept in DSA is proposed, which is spectrally efficient than the previous virtual boundary concept applied to donor systems only. Here, the same technique is applied to both donor and rental systems so as to further reduce the occurrences where the insertion of guard bands is obligatory and as a result provides better spectral efficiency. The proposed extension improves the spectrum utilization without any compromise on interference and fairness issues.展开更多
WTA (weapon-target allocation) of air defense operation is a very complicated problem and current models focus on static and restricted WTA problem mostly. Based on the dynamic characteristics of air defense operati...WTA (weapon-target allocation) of air defense operation is a very complicated problem and current models focus on static and restricted WTA problem mostly. Based on the dynamic characteristics of air defense operational command and decision of warships' formation, a dynamic WTA model is established. Simulation results show that switch fire and repetition fire of anti-air weapon system affect the result of the air defense operation remarkably and the dynamic model is more satisfying than static ones. Related results are gained based on the analysis of the simulation results and the results are accordant with the intuitionistic tactical judgment. The model is some reference for the research of air defense C^3I system of warships' formation.展开更多
In this paper, the 40-Gbps orthogonal frequency division multiple access(OFDMA) technology enabled by subcarrier allocation in the form of integrated architecture for the intra-cell is proposed in the downlink transmi...In this paper, the 40-Gbps orthogonal frequency division multiple access(OFDMA) technology enabled by subcarrier allocation in the form of integrated architecture for the intra-cell is proposed in the downlink transmission passive broadband optical access system. The data-carrying subcarriers in the inverse fast Fourier transform/fast Fourier transform(IFFT/FFT) size of1 024 points are successfully divided into three sub-channels,in which each sub-channel has 256 useful subcarriers, by using adaptive dynamic bandwidth allocation(DBA). Taking the inherent advantages of M-ary quadrature amplitude modulation(MQAM)modulation mechanism into account, the performance of the absolutely identical MQAM format over the different sub-channels for the downstream OFDMA-passive optical network(PON) is investigated based on the intensity modulation direct detection(IMDD) system by simulations. The results show that three parallel4 QAM or 16 QAM or 64 QAM OFDMA data, which are transmitted over three sub-channels, is more suitable for different sub-channel allocations, respectively. In addition, comparing with single port4/16/64 QAM OFDM over the same access system, the receiver sensitivity economizes – 0.6 d Bm, 0.6 d Bm, 4.6 d Bm at the bit error rate(BER) value of 10-3 respectively.展开更多
Multi-beam antenna and beam hopping technologies are an effective solution for scarce satellite frequency resources.One of the primary challenges accompanying with Multi-Beam Satellites(MBS)is an efficient Dynamic Res...Multi-beam antenna and beam hopping technologies are an effective solution for scarce satellite frequency resources.One of the primary challenges accompanying with Multi-Beam Satellites(MBS)is an efficient Dynamic Resource Allocation(DRA)strategy.This paper presents a learning-based Hybrid-Action Deep Q-Network(HADQN)algorithm to address the sequential decision-making optimization problem in DRA.By using a parameterized hybrid action space,HADQN makes it possible to schedule the beam pattern and allocate transmitter power more flexibly.To pursue multiple long-term QoS requirements,HADQN adopts a multi-objective optimization method to decrease system transmission delay,loss ratio of data packets and power consumption load simultaneously.Experimental results demonstrate that the proposed HADQN algorithm is feasible and greatly reduces in-orbit energy consumption without compromising QoS performance.展开更多
A novel centralized approach for Dynamic Spectrum Allocation (DSA) in the Cognitive Radio (CR) network is presented in this paper. Instead of giving the solution in terms of formulas modeling network environment such ...A novel centralized approach for Dynamic Spectrum Allocation (DSA) in the Cognitive Radio (CR) network is presented in this paper. Instead of giving the solution in terms of formulas modeling network environment such as linear programming or convex optimization, the new approach obtains the capability of iteratively on-line learning environment performance by using Reinforcement Learning (RL) algorithm after observing the variability and uncertainty of the heterogeneous wireless networks. Appropriate decision-making access actions can then be obtained by employing Fuzzy Inference System (FIS) which ensures the strategy being able to explore the possible status and exploit the experiences sufficiently. The new approach considers multi-objective such as spectrum efficiency and fairness between CR Access Points (AP) effectively. By interacting with the environment and accumulating comprehensive advantages, it can achieve the largest long-term reward expected on the desired objectives and implement the best action. Moreover, the present algorithm is relatively simple and does not require complex calculations. Simulation results show that the proposed approach can get better performance with respect to fixed frequency planning scheme or general dynamic spectrum allocation policy.展开更多
The multi-objective optimization problem has been encountered in numerous fields such as high-speed train head shape design,overlapping community detection,power dispatch,and unmanned aerial vehicle formation.To addre...The multi-objective optimization problem has been encountered in numerous fields such as high-speed train head shape design,overlapping community detection,power dispatch,and unmanned aerial vehicle formation.To address such issues,current approaches focus mainly on problems with regular Pareto front rather than solving the irregular Pareto front.Considering this situation,we propose a many-objective evolutionary algorithm based on decomposition with dynamic resource allocation(Ma OEA/D-DRA)for irregular optimization.The proposed algorithm can dynamically allocate computing resources to different search areas according to different shapes of the problem’s Pareto front.An evolutionary population and an external archive are used in the search process,and information extracted from the external archive is used to guide the evolutionary population to different search regions.The evolutionary population evolves with the Tchebycheff approach to decompose a problem into several subproblems,and all the subproblems are optimized in a collaborative manner.The external archive is updated with the method of rithms using a variety of test problems with irregular Pareto front.Experimental results show that the proposed algorithèm out-p£performs these five algorithms with respect to convergence speed and diversity of population members.By comparison with the weighted-sum approach and penalty-based boundary intersection approach,there is an improvement in performance after integration of the Tchebycheff approach into the proposed algorithm.展开更多
基金This work was supported by the Key Program of Social Science Planning Foundation of Liaoning Province under Grant L21AGL017.
文摘Shared manufacturing is recognized as a new point-to-point manufac-turing mode in the digital era.Shared manufacturing is referred to as a new man-ufacturing mode to realize the dynamic allocation of manufacturing tasks and resources.Compared with the traditional mode,shared manufacturing offers more abundant manufacturing resources and flexible configuration options.This paper proposes a model based on the description of the dynamic allocation of tasks and resources in the shared manufacturing environment,and the characteristics of shared manufacturing resource allocation.The execution of manufacturing tasks,in which candidate manufacturing resources enter or exit at various time nodes,enables the dynamic allocation of manufacturing tasks and resources.Then non-dominated sorting genetic algorithm(NSGA-II)and multi-objective particle swarm optimization(MOPSO)algorithms are designed to solve the model.The optimal parameter settings for the NSGA-II and MOPSO algorithms have been obtained according to the experiments with various population sizes and iteration numbers.In addition,the proposed model’s efficiency,which considers the entries and exits of manufacturing resources in the shared manufacturing environment,is further demonstrated by the overlap between the outputs of the NSGA-II and MOPSO algorithms for optimal resource allocation.
基金This research was funded by the Project of the National Natural Science Foundation of China,Grant Number 62106283.
文摘Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA.The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the algorithm.Finally,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air confrontation.The experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision space.The MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.
基金supported by the National Natural Science Foundation of China(No.62071354)the Key Research and Development Program of Shaanxi(No.2022ZDLGY05-08)supported by the ISN State Key Laboratory。
文摘To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.
文摘Non-orthogonal multiple access(NOMA)represents the latest addition to the array of multiple access techniques,enabling simultaneous servicing of multiple users within a singular resource block in terms of time,frequency,and code.A typical NOMA configuration comprises a base station along with proximate and distant users.The proximity users experience more favorable channel conditions in contrast to distant users,resulting in a compromised performance for the latter due to the less favorable channel conditions.When cooperative communication is integrated with NOMA,the overall system performance,including spectral efficiency and capacity,is further elevated.This study introduces a cooperative NOMA setup in the downlink,involving three users,and employs dynamic power allocation(DPA).Within this framework,User 2 acts as a relay,functioning under the decode-and-forward protocol,forwarding signals to both User 1 and User 3.This arrangement aims to bolster the performance of the user positioned farthest from the base station,who is adversely affected by weaker channel conditions.Theoretical and simulation outcomes reveal enhancements within the system’s performance.
文摘To improve and optimize the bandwidth utilization for multi-service packet transporting system, a kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm allowing a single link to use far beyond its fair share bandwidth is presented. Three important parameters as the bound on max and minimum bandwidth, the maximum packet delay and the minimum bandwidth utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system use all the spare bandwidth (up to full-bandwidth) while the performance of fairness and QoS requirement is still guaranteed.
文摘This paper presents a novel model for dynamic bandwidth allocation and rate coordination based on DiffServ and a bandwidth broker(BB). In this model, assignment of bandwidth was made according to a periodic trace of network characteristics per application. And adjustment of transfer rate was accomplished through negotiation with applications by a bandwidth agent. This model was evaluated using network simulator 2 (NS-2), and distinct improvements were found in respects of delay and packet loss of overall network and single flow. Finally, the model was suggested to be leveraged to multimedia applications with properties of lower delay and lower packet loss.
基金supported in part by the Joint Scientific Research Project Funding Scheme between Macao Science and Technology Development Fund and the Ministry of Science and Technology of the People's Republic of China under Grant 0066/2019/AMJin part by the Intergovernmental International Cooperation in Science and Technology Innovation Program under Grants 2019YFE0111600+3 种基金in part by the Macao Science and Technology Development Fund under Grants 0060/2019/A1 and 0162/2019/A3in part by National Natural Science Foundation of China under Grant 62072490in part by Research Grant of University of Macao under Grants MYRG2018-00237-FST and SRG2019-00168-IOTSCin part by FDCT SKL-IOTSC(UM)-2021-2023.
文摘Mobile Edge Computing(MEC)has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices.In this paper,we investigate the optimal dynamic spectrum allocation-assisted multiuser computation offloading in MEC for overall latency minimization.Specifically,we first focus on a static multiuser computation offloading scenario and jointly optimize users'offloading decisions,transmission durations,and Edge Servers'(ESs)resource allocations.Owing to the nonconvexity of our joint optimization problem,we identify its layered structure and decompose it into two problems:a subproblem and a top problem.For the subproblem,we propose a bisection search-based algorithm to efficiently find the optimal users'offloading decisions and ESs’resource allocations under a given transmission duration.Second,we use a linear search-based algorithm for solving the top problem to obtain the optimal transmission duration based on the result of the subproblem.Further,after solving the static scenario,we consider a dynamic scenario of multiuser computation offloading with time-varying channels and workload.To efficiently address this dynamic scenario,we propose a deep reinforcement learning-based online algorithm to determine the near-optimal transmission duration in a real-time manner.Numerical results are provided to validate our proposed algorithms for minimizing the overall latency in both static and dynamic offloading scenarios.We also demonstrate the advantages of our proposed algorithms compared to the conventional multiuser computation offloading schemes.
文摘The passive optical network(PON)technology has been drastically improved in recent years.In spite of using the optical technology,the utilization of the entire bandwidth is a very challenging task.The main categories of PON are the Ethernet passive optical network(EPON)and gigabit passive optical network(GPON).These two networks use the dynamic bandwidth allocation(DBA)algorithm to attain the maximum usage of bandwidth,which is provided in the network dynamically according to the need of the customers with the support of the service level agreement(SLA).This paper will provide a clear review about the DBA algorithm of both technologies as well as the comparison。
文摘As the traffic distribution in China mainland is far from uniform, a new traffic model in China mainland is presented on the basis of per-capita Gross Domestic Product (GDP) and density of population. Based on this characteristic traffic model, a new Traffic Dependent Dynamic Channel Allocation and Reservation (TDDCAR) technique is proposed, the simulation model is built, and the strategies' performance is evaluated through computer simulation. The simulation results show that, compared to the conventional Fixed Channel Allocation (FCA), TDDCAR estimates the traffic conditions in every spot beam and frequently adjusts the traffic according to current traffic conditions. It has achieved a significant improvement in new call blocking probability, handover blocking probability, and fair index, particularly, in heavy traffic conditions. The building of traffic model in China mainland and the analysis of the simulation results has been a key foundation for the study of resource allocation schemes in the future.
基金The National High-Tech Research and Development Program of China ( No.2005AA123950)the National Science Foundation of China (No.90604035)
文摘A realistic population density distribution scenario in conjunction with the spatial dynamic spectrum allocation (DSA) is taken into account to mitigate the spectrum wastage in terms of extra guard bands. For the insertion of the extra guard bands, an efficient strategy based on self-assessment is applied to each victim cell individually and independently. Consequently, it is no more required to spread the extra guard band over the whole DSA region. Simulation results StlOW an improvement of 3% -4% in percentage of satisfied users for Universal Mobile Telecommunications System (UMTS) network and 4%-5% for Digital Video Broadcasting Terrestrial (DVB-T) network.
文摘With the rapid development of wireless network technologies and the growing de⁃mand for a high quality of service(QoS),the effective management of network resources has attracted a lot of attention.For example,in a practical scenario,when a network shock oc⁃curs,a batch of affected flows needs to be rerouted to respond to the network shock to bring the entire network deployment back to the optimal state,and in the process of rerouting a batch of flows,the entire response time needs to be as short as possible.Specifically,we re⁃duce the time consumed for routing by slicing,but the routing success rate after slicing is re⁃duced compared with the unsliced case.In this context,we propose a two-stage dynamic net⁃work resource allocation framework that first makes decisions on the slices to which flows are assigned,and coordinates resources among slices to ensure a comparable routing suc⁃cess rate as in the unsliced case,while taking advantage of the time efficiency gains from slicing.
文摘It is known that dynamic channel assignment(D CA ) strategy outperforms the fixed channel assignment(FCA) strategy in omni-direc tional antenna cellular systems. One of the most important methods used in DCA w as channel borrowing. But with the emergence of cell sectorization and spatial d ivision multiple access(SDMA) which are used to increase the capacity of cel lular systems, the channel assignment faces a series of new problems. In this pa per, a dynamic channel allocation scheme based on sectored cellular systems is p roposed. By introducing intra-cell channel borrowing (borrowing channels from n eighboring sectors) and inter-cell channel borrowing (borrowing channels from n eighboring cells) methods, previous DCA strategies, including compact pattern ba sed channel borrowing(CPCB) and greedy based dynamic channel assignment(GDCA) schemes proposed by the author, are improved significantly. The computer simu lation shows that either intra-cell borrowing scheme or inter-cell borrowing s cheme is efficient enough to uniform and non-uniform traffic service distributi ons.
文摘The Ethernet passive optical network(EPON) is the next generation of broad-band network technique.A crucial issue in EPONs is the sharing of uplink bandwidth among optical network units(ONUs).This article provides a novel dynamic bandwidth allocation algorithm,i.e.threshold dynamic bandwidth allocation(TDBA),which is based on adaptive threshold,to increase resource utilization.The algorithm uses ONU data-transmitting rate to adjust optical line terminal(OLT) receiving data threshold from an ONU.Simulation results show that this algorithm can decrease average packet delay and increase network throughput in a 10G EPON system.
基金We are grateful for the support of the Natural Science Foundation of Shandong Province(No.ZR2020LZH008,ZR2020QF112,ZR2019MF071)the National Natural Science Foundation of China(61373149).
文摘Network virtualization can effectively establish dedicated virtual networks to implement various network functions.However,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and priority.In addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation redundancy.Based on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology properties.In the node mapping process,three properties of the node are used to measure its mapping ability.Second,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link mapping.Finally,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource allocation.The former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision probability.Simulation results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenue by 15%and 38%,and reduce the network cost and link pressure by 25%and 17%.
基金This work was supported in part by the National Nature Science Foundation of China (NSFC) under Grant No. 90604035the 863 high-tech R&D program of China under Grant No. 2005AA123950.
文摘This paper presents an efficient dynamic spectrum allocation (DSA) scheme in a flexible spectrum licensing environment where multiple networks coexist and interfere with each other. In particular, an extension of virtual boundary concept in DSA is proposed, which is spectrally efficient than the previous virtual boundary concept applied to donor systems only. Here, the same technique is applied to both donor and rental systems so as to further reduce the occurrences where the insertion of guard bands is obligatory and as a result provides better spectral efficiency. The proposed extension improves the spectrum utilization without any compromise on interference and fairness issues.
文摘WTA (weapon-target allocation) of air defense operation is a very complicated problem and current models focus on static and restricted WTA problem mostly. Based on the dynamic characteristics of air defense operational command and decision of warships' formation, a dynamic WTA model is established. Simulation results show that switch fire and repetition fire of anti-air weapon system affect the result of the air defense operation remarkably and the dynamic model is more satisfying than static ones. Related results are gained based on the analysis of the simulation results and the results are accordant with the intuitionistic tactical judgment. The model is some reference for the research of air defense C^3I system of warships' formation.
基金supported by the National Natural Science Foundation of China(61771082 61801065+3 种基金 61871062)the China Scholarship Council(201908500139)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN201800615KJQN201800609)
文摘In this paper, the 40-Gbps orthogonal frequency division multiple access(OFDMA) technology enabled by subcarrier allocation in the form of integrated architecture for the intra-cell is proposed in the downlink transmission passive broadband optical access system. The data-carrying subcarriers in the inverse fast Fourier transform/fast Fourier transform(IFFT/FFT) size of1 024 points are successfully divided into three sub-channels,in which each sub-channel has 256 useful subcarriers, by using adaptive dynamic bandwidth allocation(DBA). Taking the inherent advantages of M-ary quadrature amplitude modulation(MQAM)modulation mechanism into account, the performance of the absolutely identical MQAM format over the different sub-channels for the downstream OFDMA-passive optical network(PON) is investigated based on the intensity modulation direct detection(IMDD) system by simulations. The results show that three parallel4 QAM or 16 QAM or 64 QAM OFDMA data, which are transmitted over three sub-channels, is more suitable for different sub-channel allocations, respectively. In addition, comparing with single port4/16/64 QAM OFDM over the same access system, the receiver sensitivity economizes – 0.6 d Bm, 0.6 d Bm, 4.6 d Bm at the bit error rate(BER) value of 10-3 respectively.
基金co-supported by the National Natural Science Foundation of China(No.U20B2056)the Office of Military and Civilian Integration Development Committee of Shanghai,China(No.2020-jmrh1-kj25).
文摘Multi-beam antenna and beam hopping technologies are an effective solution for scarce satellite frequency resources.One of the primary challenges accompanying with Multi-Beam Satellites(MBS)is an efficient Dynamic Resource Allocation(DRA)strategy.This paper presents a learning-based Hybrid-Action Deep Q-Network(HADQN)algorithm to address the sequential decision-making optimization problem in DRA.By using a parameterized hybrid action space,HADQN makes it possible to schedule the beam pattern and allocate transmitter power more flexibly.To pursue multiple long-term QoS requirements,HADQN adopts a multi-objective optimization method to decrease system transmission delay,loss ratio of data packets and power consumption load simultaneously.Experimental results demonstrate that the proposed HADQN algorithm is feasible and greatly reduces in-orbit energy consumption without compromising QoS performance.
基金supported in part by National Science Fund for Distinguished Young Scholars project under Grant No.60725105National Basic Research Program of China (973 Pro-gram) under Grant No.2009CB320404+1 种基金National Natural Science Foundation of China under Grant No.61072068Fundamental Research Funds for the Central Universities under Grant No.JY10000901031
文摘A novel centralized approach for Dynamic Spectrum Allocation (DSA) in the Cognitive Radio (CR) network is presented in this paper. Instead of giving the solution in terms of formulas modeling network environment such as linear programming or convex optimization, the new approach obtains the capability of iteratively on-line learning environment performance by using Reinforcement Learning (RL) algorithm after observing the variability and uncertainty of the heterogeneous wireless networks. Appropriate decision-making access actions can then be obtained by employing Fuzzy Inference System (FIS) which ensures the strategy being able to explore the possible status and exploit the experiences sufficiently. The new approach considers multi-objective such as spectrum efficiency and fairness between CR Access Points (AP) effectively. By interacting with the environment and accumulating comprehensive advantages, it can achieve the largest long-term reward expected on the desired objectives and implement the best action. Moreover, the present algorithm is relatively simple and does not require complex calculations. Simulation results show that the proposed approach can get better performance with respect to fixed frequency planning scheme or general dynamic spectrum allocation policy.
基金the National Natural Science Foundation of China(Nos.6156301261802085+5 种基金and 61203109)the Guangxi Natural Science Foundation of China(Nos.2014GhXN6SF AA1183712015GXNSFBA139260and 2020GXNSFAA159038)the Guangxi Key Laboratory of Embedded Technology and Intelligent System Foundation(No.2018A-04)the Guangxi Key Laboratory of Trusted Software Foundation(Nos.kx202011 and khx2601926)。
文摘The multi-objective optimization problem has been encountered in numerous fields such as high-speed train head shape design,overlapping community detection,power dispatch,and unmanned aerial vehicle formation.To address such issues,current approaches focus mainly on problems with regular Pareto front rather than solving the irregular Pareto front.Considering this situation,we propose a many-objective evolutionary algorithm based on decomposition with dynamic resource allocation(Ma OEA/D-DRA)for irregular optimization.The proposed algorithm can dynamically allocate computing resources to different search areas according to different shapes of the problem’s Pareto front.An evolutionary population and an external archive are used in the search process,and information extracted from the external archive is used to guide the evolutionary population to different search regions.The evolutionary population evolves with the Tchebycheff approach to decompose a problem into several subproblems,and all the subproblems are optimized in a collaborative manner.The external archive is updated with the method of rithms using a variety of test problems with irregular Pareto front.Experimental results show that the proposed algorithèm out-p£performs these five algorithms with respect to convergence speed and diversity of population members.By comparison with the weighted-sum approach and penalty-based boundary intersection approach,there is an improvement in performance after integration of the Tchebycheff approach into the proposed algorithm.