Resource Allocation for Cognitive Network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning

In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.

User Scheduling and Slicing Resource Allocation in Industrial Internet of Things

Heterogeneous base station deployment enables to provide high capacity and wide area coverage.Network slicing makes it possible to allocate wireless resource for heterogeneous services on demand.These two promising technologies contribute to the unprecedented service in 5G.We establish a multiservice heterogeneous network model,which aims to raise the transmission rate under the delay constraints for active control terminals,and optimize the energy efficiency for passive network terminals.A policygradient-based deep reinforcement learning algorithm is proposed to make decisions on user association and power control in the continuous action space.Simulation results indicate the good convergence of the algorithm,and higher reward is obtained compared with other baselines.

An Intelligent Admission Control Scheme for Dynamic Slice Handover Policy in 5G Network Slicing

5G use cases,for example enhanced mobile broadband(eMBB),massive machine-type communications(mMTC),and an ultra-reliable low latency communication(URLLC),need a network architecture capable of sustaining stringent latency and bandwidth requirements;thus,it should be extremely flexible and dynamic.Slicing enables service providers to develop various network slice architectures.As users travel from one coverage region to another area,the callmust be routed to a slice thatmeets the same or different expectations.This research aims to develop and evaluate an algorithm to make handover decisions appearing in 5G sliced networks.Rules of thumb which indicates the accuracy regarding the training data classification schemes within machine learning should be considered for validation and selection of the appropriate machine learning strategies.Therefore,this study discusses the network model’s design and implementation of self-optimization Fuzzy Qlearning of the decision-making algorithm for slice handover.The algorithm’s performance is assessed by means of connection-level metrics considering the Quality of Service(QoS),specifically the probability of the new call to be blocked and the probability of a handoff call being dropped.Hence,within the network model,the call admission control(AC)method is modeled by leveraging supervised learning algorithm as prior knowledge of additional capacity.Moreover,to mitigate high complexity,the integration of fuzzy logic as well as Fuzzy Q-Learning is used to discretize state and the corresponding action spaces.The results generated from our proposal surpass the traditional methods without the use of supervised learning and fuzzy-Q learning.

Opportunistic admission and resource allocation for slicing enhanced IoT networks

Network slicing is envisioned as one of the key techniques to meet the extremely diversified service requirements of the Internet of Things(IoT)as it provides an enhanced user experience and elastic resource configuration.In the context of slicing enhanced IoT networks,both the Service Provider(SP)and Infrastructure Provider(InP)face challenges of ensuring efficient slice construction and high profit in dynamic environments.These challenges arise from randomly generated and departed slice requests from end-users,uncertain resource availability,and multidimensional resource allocation.Admission and resource allocation for distinct demands of slice requests are the key issues in addressing these challenges and should be handled effectively in dynamic environments.To this end,we propose an Opportunistic Admission and Resource allocation(OAR)policy to deal with the issues of random slicing requests,uncertain resource availability,and heterogeneous multi-resources.The key idea of OAR is to allow the SP to decide whether to accept slice requests immediately or defer them according to the load and price of resources.To cope with the random slice requests and uncertain resource availability,we formulated this issue as a Markov Decision Process(MDP)to obtain the optimal admission policy,with the aim of maximizing the system reward.Furthermore,the buyer-seller game theory approach was adopted to realize the optimal resource allocation,while motivating each SP and InP to maximize their rewards.Our numerical results show that the proposed OAR policy can make reasonable decisions effectively and steadily,and outperforms the baseline schemes in terms of the system reward.

Subsidence control method by inversely-inclined slicing and upward mining for ultra-thick steep seams

Ultra-thick steep coal seam mining will inevitably lead to the increase of greater and violent ground subsidence and deformation.A subsidence control method by inversely-inclined slicing and upward mining is proposed in this paper.By this method,the sequence of collapse of overlying strata and the direction of propagation of strata movement are changed,the extent of roof-side deformation thereby is lessened,and boundary angle of roof-side subsidence is reduced by 5°-10°.The mechanism of this mining method for control of strata movement has been evidenced by numerical simulation and experiments with similarity materials.A subsidence prediction model based on the variation of mining influence propagation angle can be used to evaluate the surface movement and deformation of the mining method.The application of the method in No.3 Mine in Yaojie mining area has yielded the expected result.

Direct Slicing Based on Material Performance and Process Parameters for Selective Laser Sintering

Direct slicing from GAD models to generate sectional contours of the part to be sintered for Selective Laser Sintering （SLS） may overcome inherent disadvantages of using a Stereo Lithography （STL） format. In this paper, a direct slicing procedure is proposed for Selective Laser Sintering based on material performance and process parameters. Slicing thickness depends on the 3 D geometric model, material performance and process parameters. The relationship among material performance, process parameters and the largest slicing thickness is established using analysis of a sintering temperature field. A dynamic linked library is developed to realize direct slicing from a CAD model.

Effect of the Cutter Parameters and Machining Parameters on the Interference in Gear Slicing

Current researches have not yet found the effect law of the cutter parameters and machining parameters on the interference in gear slicing, the interference between the cutter and machined gear often happens because the appropriate cutter parameters and machining parameters cannot be set, which reduces the gear machining accuracy. The relative position between the major flank face and edge-sweeping surface, distribution law of the interference area in forming process of edge-sweeping surface, and effect law of relative positions among edge-sweeping surfaces on the interference are studied by graphical analysis. The effect law of the cutter parameters and machining parameters on the interference is found. The effect law shows that the interference in gear slicing can be controlled when the relief angle measured on the top edge and feed of every rotation are chosen respectively larger than 9~ and smaller than 0.15 mrn/r. An internal helical gear is sliced with the spur slice cutter and the cutter parameters and machining parameters are set based on above the effect law. The machined gear is measured in Gear Measuring Center and the detection result shows that the comprehensive accuracy reaches GB/T Class 7, where some reach GB/T Class 6. The result can meet the gear machining accuracy requirement and shows that the effect law found is valid. The problem of the interference in gear slicing is solved and the gear machining accuracy can be improved.

Monitoring strata behavior due to multi-slicing top coal caving longwall mining in steeply dipping extra thick coal seam

For studying the strata behavior due to multi-slicing top coal caving longwall mining along-the-strike direction in steeply dipping extra thick coal seams,the shield support pressures of the upper and lower slices of panel 37220 in Dongxia Coal Mine were monitored using the KJ513 dynamic monitoring system.The set up rooms adopted the "horizontal line-arc segment-inclined line" form and used different types of shield supports.The results show that the strata pressure of upper slice panel 37220-1 changed slightly along the strike direction,while along the dip direction it exhibited strong to weak pressure from bottom to top.The first weighting interval of lower slice panel 37220-2 was about 60.8 m,and the average periodic weighting interval were about 22.6 m.The strata behavior of panel 37220-2 exhibited a spatiotemporal characteristic in that periodic weighting occurred first in the middle-upper part,followed by the middle and upper parts,arc segment,and finally the lower part.During the periodic weighting,the weighting interval and intensity also exhibited strong space characteristics.The average dynamic load coefficient was 1.48 and the maximum lateral load of the side shield was 20-25 MPa.

Research on Intelligent Logic Design and Application of Campus MMTC Scene Based on 5G Slicing Technology

A consensus has been reached that 5G network slicing technology is becoming increasingly important in EMBB,MMTC and URLLC.However,this technology still has a long way to go in education industry.By selecting four types of demands in campus MMTC scenarios as specific application references,this research explores the architectural relationship between network slicing layer,intelligent terminal layer and application capability layer.Besides,emphasis has been put on the influences that virtual logic network design technology,isolation technology and standard technology has on application experiences.Under such goal,a two-dimensional route has been proposed to deploy network slicing technology based on the concept of full life cycle and the synergistic effect that AI algorithms has on slicing technology.This research is expected to nurture slicing technology,not only its technology chain,but more importantly,facilitate its value chain and large-scale vertical industry applications.

Dependence Analysis Based on Dynamic Slicing for Debugging

Dynamic program slicing is an effective technique for narrowing the errors to the relevant parts of a program when debugging. Given a slicing criterion, the dynamic slice contains only those statements that actually affect the variables in the slicing criterion. This paper proposes a dynamic slicing method based on static dependence analysis. It uses the program dependence graph and other static information to reduce the information needed to be traced during program execution. Thus, the efficiency is dramatically improved while the precision is not depressed. The slicing criterion is modified to fit for debugging. It consists of file name and the line number at which the statement is.

Fast Parallel Algorithm for Slicing STL Based on Pipeline

In Additive Manufacturing field, the current researches of data processing mainly focus on a slicing process of large STL files or complicated CAD models. To improve the efficiency and reduce the slicing time, a parallel algorithm has great advantages. However, traditional algorithms can＇t make full use of multi-core CPU hardware resources. In the paper, a fast parallel algorithm is presented to speed up data processing. A pipeline mode is adopted to design the parallel algorithm. And the complexity of the pipeline algorithm is analyzed theoretically. To evaluate the performance of the new algorithm, effects of threads number and layers number are investigated by a serial of experiments. The experimental results show that the threads number and layers number are two remarkable factors to the speedup ratio. The tendency of speedup versus threads number reveals a positive relationship which greatly agrees with the Amdahl＇s law, and the tendency of speedup versus layers number also keeps a positive relationship agreeing with Gustafson＇s law. The new algorithm uses topological information to compute contours with a parallel method of speedup. Another parallel algorithm based on data parallel is used in experiments to show that pipeline parallel mode is more efficient. A case study at last shows a suspending performance of the new parallel algorithm. Compared with the serial slicing algorithm, the new pipeline parallel algorithm can make full use of the multi-core CPU hardware, accelerate the slicing process, and compared with the data parallel slicing algorithm, the new slicing algorithm in this paper adopts a pipeline parallel model, and a much higher speedup ratio and efficiency is achieved.

Modeling the Surface Cross-Contamination of <i>Salmonella</i>spp. on Ready-to-Eat Meat via Slicing Operation

Salmonella spp. surface transfer patterns/models between ready-to-eat (RTE) deli meat and a typical meat slicer are presented. A five-strain cocktail of Salmonella spp. was inoculated directly onto the rim of a round slicer blade at an initial level of ca. 4, 5, 6, 7 or 8 log CFU/blade (ca. 3, 4, 5, 6 or 7 log CFU/cm2 of the blade edge area). Thereafter, a RTE deli meat (ham) was sliced to a thickness of 1.5 - 2.0 mm. In another cross-contamination scenario, a clean blade was initially used to slice ham, which was pre-surface-inoculated with the Salmonella cocktail (ca. 2, 3, 4, 5, 6 or 7 log CFU/cm2 with a total area of 100 cm2), followed by slicing of an un-inoculated ham. The log CFU of Salmonella per ham slice was determined and empirical models were developed. The models, follow the decreasing Power law, predict the surface cross-contamination of Salmonella spp. (at any initial level) for sliced deli meat (ham) and will provide a useful tool in developing RTE meat risk assessments. Surface transfer patterns of three foodborne pathogens, i.e. Listeria monocytogenes, E. coli O157:H7 and Salmonella predicted by models are also presented.

Evaluation of 5G Core Slicing on User Plane Function

Network slicing is one of the most important features in 5G which enables a large variety of services with diverse performance requirements by network virtualization. Traditionally, the network can be viewed as a one-size-fits-all slice and its services are bundled with proprietary hardware supported by telecom equipment providers. Now with the network virtualization technology in 5G, open networking software can be deployed flexibly on commodity hardware to offer a multi-slice network where each slice can offer a different set of network services. In this research, we propose a multi-slice 5G core architecture by provisioning its User Plane Functions (UPFs) with different QoS requirements. We compare the performance of such a multi-slice system with that of one-size-fits-all single slice architecture under the same resource assignment. Our research objective is to compare the performance of a network slicing architecture with that of a “one-size-fits-all” architecture and validate that the former can achieve better performance with the same underlying infrastructure. The results validate that our proposed system can achieve better performance by slicing one UPF into three with proper resource allocation.

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.

Three Dimensional Laser Point Cloud Slicing Method for Calculating Irregular Volume

Volume parameter is the basic content of a spatial body object morphology analysis.However,the challenge lies in the volume calculation of irregular objects.The point cloud slicing method proposed in this study effectively works in calculating the volume of the point cloud of the spatial object obtained through three-dimensional laser scanning(3DLS).In this method,a uniformly spaced sequent slicing process is first conducted in a specific direction on the point cloud of the spatial object obtained through 3DLS.A series of discrete point cloud slices corresponding to the point cloud bodies are then obtained.Subsequently,the outline boundary polygon of the point cloud slicing is searched one by one in accordance with the slicing sequence and areas of the polygon.The point cloud slice is also calculated.Finally,the individual point cloud section volume is calculated through the slicing areas and the adjacent slicing gap.Thus,the total volume of the scanned spatial object can be calculated by summing up the individual volumes.According to the results and analysis of the calculated examples,the slice-based volume-calculating method for the point cloud of irregular objects obtained through 3DLS is correct,concise in process,reliable in results,efficient in calculation methods,and controllable on accuracy.This method comes as a good solution to the volume calculation of irregular objects.

Slicing 3D CAD Model Directly with ObjectARX

An algorithm for compensating the varying section contour within the extent of each layer thickness is proposed to improve the rapid prototyping part’s shape and size precision.

Satellite E2E Network Slicing Based on 5G Technology

We investigate the design of satellite network slicing for the first time to provide customized services for the diversified applications,and propose a novel scheme for satellite end-to-end(E2E) network slicing based on 5G technology,which provides a view of common satellite network slicing and supports flexible network deployment between the satellite and the ground.Specifically,considering the limited satellite network resource and the characteristics of the satellite channel,we propose a novel satellite E2E network slicing architecture.Therein,the deployment of the network functions between the satellite and the ground is coordinately considered.Subsequently,the classification and the isolation technologies of satellite network sub-slices are proposed adaptively based on 5G technology to support resource allocation on demand.Then,we develop the management technologies for the satellite E2E network slicing including slicing key performance indicator(KPI) design,slicing deployment,and slicing management.Finally,the analysis of the challenges and future work shows the potential research in the future.

Slicing Method for Reverse Engineering Based on Image Mosaic

Reverse engineering dealing with images is traditionally based on image processing and contour recognition. A new method is presented based on the combination of sectional slicing with image mosaic. Sectional contours of the target object are generated by colorful liquid or laser scanning, these images from different views are fused into a set of complete cross-sectional images, thereby the whole practical model is reconstructed in 3D space.

Cognitive RAN Slicing Resource Allocation Based on Stackelberg Game

The cognitive network has become a promising method to solve the spectrum resources shortage problem.Especially for the optimization of network slicing resources in the cognitive radio access network(RAN),we are interested in the profit of the mobile virtual network operator(MVNO)and the utility of secondary users(SUs).In cognitive RAN,we aim to find the optimal scheme for the MVNO to efficiently allocate slice resources to SUs.Since the MVNO and SUs are selfish and the game between the MVNO and SUs is difficult to reach equilibrium,we consider modeling this scheme as a Stackelberg game.Leveraging mathematical programming with equilibrium constraints(MPEC)and Karush-Kuhn-Tucker(KKT)conditions,we can obtain a single-level optimization problem,and then prove that the problem is a convex optimization problem.The simulation results show that the proposed method is superior to the noncooperative game.While guaranteeing the Quality of Service(QoS)of primary users(PUs)and SUs,the proposed method can balance the profit of the MVNO and the utility of SUs.

Dynamic Slicing of Object Oriented Programs

Program slice has many applications such as program debugging, testing, maintenance, and complexity measurement. A static slice consists of all statements in program P that may effect the value of variable v at some point p , and a dynamic slice consists only of statements that influence the value of variable occurrence for specific program inputs. In this paper, we concern the problem of dynamic slicing of object oriented programs which, to our knowledge, has not been addressed in the literatures. To solve this problem, we present the dynamic object oriented dependence graph (DODG)which is an arc classified digraph to explicitly represent various dynamic dependence between statement instances for a particular execution of an object oriented program. Based on the DODG, we present a two phase backward algorithm for computing a dynamic slice of an object oriented program.