Dynamic Allocation of Manufacturing Tasks and Resources in Shared Manufacturing

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.

Fuzzy Earthwork Dynamic Allocation and Optimization for Construction of High Concrete Face Rockfill Dam

Due to the complexity of earthwork allocation system for the construction of high concrete face rockfill dam,traditional allocation and planning are not able to function properly in the construction process with strong randomness.In this paper,the working mechanism of earthwork dynamic allocation system is analyzed comprehensively and a solution to fuzzy earthwork dynamic allocation is proposed on the basis of uncertain factors in the earthwork allocation of a hydropower project.Under the premise of actual situation and the experience of the construction site,an all-coefficient-fuzzy linear programming mathematical model with fuzzy parameters and constraints for earthwork allocation is established according to the structure unit weighted ranking criteria.In this way,the deficiency of certain allocation model can be overcome.The application results indicate that the proposed method is more rational compared with traditional earthwork allocation.

MADDPG-D2: An Intelligent Dynamic Task Allocation Algorithm Based on Multi-Agent Architecture Driven by Prior Knowledge

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.

Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

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.

Cooperative Relaying in a Three User Downlink NOMA System Using Dynamic Power Allocation

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.

Dynamic bandwidth allocation algorithm for full-band utilization

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.

DYNAMIC BANDWIDTH ALLOCATION ALGORITHM UTILIZING FULL BAND

A kind of Dynamic Full Bandwidth Utilized (DFBU) allocation algorithm is introduced. This algorithm allows a single link to use bandwidth far beyond its fair share bandwidth in a multi-service packet transporting system. Three important parameters as the bound on maximum and minimum bandwidth, the maximum packet delay and the minimum band width utilization are discussed and analyzed. Results of experiments show that the DFBU-algorithm is capable of making a single link in the system to use all the spare bandwidth (up to full-bandwidth) while the performance of fairness and QoS requirement is still guaranteed.

Dynamic resource allocation for high-speed railway downlink MIMO-OFDM system

The dynamic resource allocation problem in high-speed railway downlink orthogonal frequency-division multiplexing（OFDM） systems with multiple-input multiple-output（MIMO） antennas is investigated.Sub-carriers,antennas,time slots,and power are jointly considered.The problem of multi-dimensional resource allocation is formulated as a mixed-integer nonlinear programming problem.The effect of the moving speed on Doppler shift is analyzed to calculate the inter-carrier interference power.The optimization objective is to maximize the system throughput under the constraint of a total transmitted power that is no greater than a certain threshold.In order to reduce the computational complexity,a suboptimal solution to the optimization problem is obtained by a two-step method.First,sub-carriers,antennas,and time slots are assigned to users under the assumption of equal power allocation.Next,the power allocation problem is solved according to the result of the first-step resource allocation.Simulation results show that the proposed multi-dimensional resource allocation strategy has a significant performance improvement in terms of system throughput compared with the existing one.

Centralized Dynamic Spectrum Allocation in Cognitive Radio Networks Based on Fuzzy Logic and Q-Learning

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.

Dynamic Bandwidth Allocation and Rate Coordination for DiffServ Environment

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.

Optimal dynamic spectrum allocation-assisted latency minimization for multiuser mobile edge computing

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.

Review on Dynamic Bandwidth Allocation of GPON and EPON

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。

DYNAMIC RESOURCE ALLOCATION SCHEME UNDER TRAFFIC CONDITION IN SATELLITE SYSTEMS

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.

Spatio-Temporal Population Density and Spatial Dynamic Spectrum Allocation

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.

Efficient Network Slicing with Dynamic Resource Allocation

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.

Dynamic spectrum allocations in multi-cells and intra-cell of cognitive network to enhance system performance

In this study, we propose new dynamic spectrum allocations in multi-cells and intra-cell of cognitive network to enhance system performance in terms of decreasing probability of interruption and spectrum handoff of communication services in a cognitive system. The inter-cells of the spectrum allocation mechanism is designed to share the risk of vacating spectrum caused by licensed incumbents re-occupying the spectrum and minimize probability of service interruption in the cognitive network. This mechanism also can guarantee fairness among multi-cells. The intra-cell of the proposed spectrum allocation is based on a service data hierarchical model and establishes a mapping mechanism between layered data and the spectrum. It can reduce probability of spectrum handoff. Finally, simulation results are given and show that the new mechanism can reduce service interruption ratio and the probability of spectrum handoff caused by licensed incumbents with re-occupying the spectrum.

Dynamic Channel Allocation in Sectored Cellular Systems

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.

Utility-optimization dynamic subcarrier allocation algorithm for SC-FDMA systems

Two utility-optimization dynamic subcarrier allocation(DSA) algorithms are designed for single carrier frequency division multiple access system(SC-FDMA).The two proposed algorithms aim to support diverse transmission capacity requirements in wireless networks,which consider both the channel state information(CSI) and the capacity requirements of each user by setting appropriate utility functions.Simulation results show that with considerable lower computational complexity,the first utility-optimization algorithm can meet the system capacity requirements of each user effectively.However,the rate-sum capacity performance is poor.Furthermore,the second proposed utility-optimization algorithm can contribute a better trade-off between system rate-sum capacity requirement and the capacity requirements of each user by introducing the signal to noise ratio(SNR) information to the utility function based on the first utility-optimization algorithm,which can improve the user requirements processing capability as well as achieve a better sum-rate capacity.

A novel algorithm for Ethernet-passive-optical-network dynamic bandwidth allocation based on threshold

The Ethemet 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 l 0G EPON system.

Genetic approach for Cell-by-Cell dynamic spectrum allocation in the heterogeneous scenario

In this paper,a genetic algorithm (GA) is investigated to deal with cell-by-cell dynamic spectrumallocation (DSA) in the heterogeneous scenario with temporal and spatial traffic demand changes,whichis also known as a difficult combinatorial optimization problem.A new two-dimensional chromosome encodingscheme is defined according to characteristics of the heterogeneous scenario,which prevents forminginvalid solutions during the genetic operation and enables much faster convergence.A novel randomcoloring gene generation function is presented which is the basic operation for initialization and mutationin the genetic algorithm.Simulative comparison demonstrates that the proposed GA-based cell-by-cellDSA outperforms the conventional contiguous DSA scheme both in terms of spectral efficiency gain andquality of service (QoS) satisfaction.