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Adaptive Partial Task Offloading and Virtual Resource Placement in SDN/NFV-Based Network Softwarization

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Computer Systems Science & Engineering 2023年第5期45卷 2141-2154页

作者： Prohim Tam sa math Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Edge intelligence brings the deployment of applied deep learning(DL)models in edge computing systems to alleviate the core backbone network *** setup of programmable software-defined networking(SDN)control and elastic virtual computing resources within network functions virtualization(NFV)are cooperative for enhancing the applicability of intelligent edge *** offer advancement for multi-dimensional model task offloading in edge networks with SDN/NFV-based control softwarization,this study proposes a DL mechanism to recommend the optimal edge node selection with primary features of congestion windows,link delays,and allocatable bandwidth *** partial task offloading policy considered the DL-based recommendation to modify efficient virtual resource placement for minimizing the completion time and termination drop *** optimization problem of resource placement is tackled by a deep reinforcement learning(DRL)-based policy following the Markov decision process(MDP).The agent observes the state spaces and applies value-maximized action of available computation resources and adjustable resource allocation *** reward formulation primarily considers taskrequired computing resources and action-applied allocation *** defined policies of resource determination,the orchestration procedure is configured within each virtual network function(VNF)descriptor using topology and orchestration specification for cloud applications(TOSCA)by specifying the allocated *** simulation for the control rule installation is conducted using Mininet and Ryu SDN *** delay and task delivery/drop ratios are used as the key performance metrics.

关键词： Deep learning partial task offloading software-defined networking virtual machine virtual network functions

Intelligent Resource Allocations for Software-Defined Mission-Critical IoT Services

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Computers, Materials & Continua 2022年第11期73卷 4087-4102页

作者： Chaebeen Nam sa math Prohim Tam Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Heterogeneous Internet of Things(IoT)applications generate a diversity of novelty applications and services in next-generation networks(NGN),which is essential to guarantee end-to-end(E2E)communication resources for both control plane(CP)and data plane(DP).Likewise,the heterogeneous 5th generation(5G)communication applications,including Mobile Broadband Communications(MBBC),massive Machine-Type Commutation(mMTC),and ultra-reliable low latency communications(URLLC),obligate to perform intelligent Quality-of-Service(QoS)Class Identifier(QCI),while the CP entities will be suffered from the complicated massive HIOT ***,the existing management and orchestration(MANO)models are inappropriate for resource utilization and allocation in large-scale and complicated network *** cope with the issues mentioned above,this paper presents an adopted software-defined mobile edge computing(SDMEC)with a lightweight machine learning(ML)algorithm,namely support vector machine(SVM),to enable intelligent MANO for real-time and resource-constraints IoT applications which require lightweight computation ***,the SVM algorithm plays an essential role in performing QCI ***,the software-defined networking(SDN)controller allocates and configures priority resources according to the SVM classification ***,the complementary of SVM and SDMEC conducts intelligent resource MANO for massive QCI environments and meets the perspectives of mission-critical communication with resource constraint *** on the E2E experimentation metrics,the proposed scheme shows remarkable outperformance in key performance indicator(KPI)QoS,including communication reliability,latency,and communication throughput over the various powerful reference methods.

关键词： Mobile edge computing Internet of Things software defined networks traffic classification machine learning resource allocation

Multi-Agent Deep Q-Networks for Efficient Edge Federated Learning Communications in Software-Defined IoT

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Computers, Materials & Continua 2022年第5期71卷 3319-3335页

作者： Prohim Tam sa math Ahyoung Lee Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Computer Science Kennesaw State UniversityMariettaGA 30060USA Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Federated learning(FL)activates distributed on-device computation techniques to model a better algorithm performance with the interaction of local model updates and global model distributions in aggregation averaging ***,in large-scale heterogeneous Internet of Things(IoT)cellular networks,massive multi-dimensional model update iterations and resource-constrained computation are challenging aspects to be tackled *** paper introduces the system model of converging softwaredefined networking(SDN)and network functions virtualization(NFV)to enable device/resource abstractions and provide NFV-enabled edge FL(eFL)aggregation servers for advancing automation and ***-agent deep Q-networks(MADQNs)target to enforce a self-learning softwarization,optimize resource allocation policies,and advocate computation offloading *** gathered network conditions and resource states,the proposed agent aims to explore various actions for estimating expected longterm rewards in a particular state *** exploration phase,optimal actions for joint resource allocation and offloading decisions in different possible states are obtained by maximum Q-value ***-based virtual network functions(VNF)forwarding graph(VNFFG)is orchestrated to map VNFs towards eFL aggregation server with sufficient communication and computation resources in NFV infrastructure(NFVI).The proposed scheme indicates deficient allocation actions,modifies the VNF backup instances,and reallocates the virtual resource for exploitation *** neural network(DNN)is used as a value function approximator,and epsilongreedy algorithm balances exploration and *** scheme primarily considers the criticalities of FL model services and congestion states to optimize long-term *** results presented the outperformance of the proposed scheme over reference schemes in terms of Quality of Service(QoS)performance metrics,including packet

关键词： Deep Q-networks federated learning network functions virtualization quality of service software-defined networking

Real-Time Prediction Algorithm for Intelligent Edge Networks with Federated Learning-Based Modeling

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Computers, Materials & Continua 2023年第11期77卷 1967-1983页

作者： Seungwoo Kang Seyha Ros Inseok Song Prohim Tam sa math Seokhoon Kim Department of Software Convergence Soonchunhyang UniversityAsan31538Korea Department of Telecommunication and Electronic Engineering Royal University of Phnom PenhPhnom Penh12156Cambodia Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Intelligent healthcare networks represent a significant component in digital applications,where the requirements hold within quality-of-service(QoS)reliability and safeguarding *** paper addresses these requirements through the integration of enabler paradigms,including federated learning(FL),cloud/edge computing,softwaredefined/virtualized networking infrastructure,and converged prediction *** study focuses on achieving reliability and efficiency in real-time prediction models,which depend on the interaction flows and network *** response to these challenges,we introduce a modified version of federated logistic regression(FLR)that takes into account convergence latencies and the accuracy of the final FL model within healthcare *** establish the FLR framework for mission-critical healthcare applications,we provide a comprehensive workflow in this paper,introducing framework setup,iterative round communications,and model evaluation/*** optimization process delves into the formulation of loss functions and gradients within the domain of federated optimization,which concludes with the generation of service experience batches for model *** assess the practicality of our approach,we conducted experiments using a hypertension prediction model with data sourced from the 2019 annual dataset(Version 2.0.1)of the Korea Medical Panel *** metrics,including end-to-end execution delays,model drop/delivery ratios,and final model accuracies,are captured and compared between the proposed FLR framework and other baseline *** study offers an FLR framework setup for the enhancement of real-time prediction modeling within intelligent healthcare networks,addressing the critical demands of QoS reliability and privacy preservation.

关键词： Edge computing federated logistic regression intelligent healthcare networks prediction modeling privacy-aware and real-time learning

On the Rayleigh-Plateau instability

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Applied mathematics(A Journal of Chinese Universities) 2012年第2期27卷 127-138页

作者： Ali AL Riyabi Mohammed Boutat sad Hilout Laboratoire de mathématiques Université de PoitiersBoulevard Marie et Pierre CurieTéléport 2BP 3017986962 Futuroscope Chasseneuil cedexFrance

In this paper,we study the surface instability of a cylindrical pore in the absence of *** instability is called the Rayleigh-Plateau *** consider the model developed by Spencer et al.[18],Kirill et al.[10]and Boutat et al.[2]in the case without *** obtain a nonlinear parabolic PDE of order *** show the local existence and uniqueness of the solution of this problem by using Faedo-Galerkin *** main results are the global existence of the solution and the convergence to the mean value of the initial data for long *** tests are also presented in this study.

关键词： parabolic nonlinear partial differential equation initial boundary value problem local solution uniqueness stability.

On Newton’s Method for Solving Nonlinear Equations and Function Splitting

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Numerical mathematics(Theory,Methods and Applications) 2011年第1期4卷 53-67页

作者： Ioannis K.Argyros saïd Hilout Cameron University Department of Mathematics SciencesLawtonOK 73505USA Universitéde Poitiers Laboratoire de Mathématiques et ApplicationsBd.Pierre et Marie CurieTéléport 2B.P.3017986962 Futuroscope Chasseneuil CedexFrance

We provided in[14]and[15]a semilocal convergence analysis for Newton’s method on a Banach space setting,by splitting the given *** this study,we improve the error bounds,order of convergence,and simplify the sufficie... 详细信息

关键词： Newton’s method Banach space majorizing sequence semilocal convergence splitting of an operator

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随机一般多孔介质与快速扩散方程(英文)

山东大学学报（理学版） 2009年第10期44卷 1-13页

作者：王凤雨北京师范大学数学科学学院数学与系统科学实验室北京100875

基于作者和合作者的有关工作,本文介绍关于随机一般多孔介质与快速扩散方程研究的若干新进展。我们从确定性的方程出发,引入相应随机方程的一般框架,再分别介绍解的存在唯一性、Harnack不等式与应用、解的正则性和大偏差原理等。

关键词：随机多孔介质方程随机快速扩散方程 Harnack不等式大偏差遍历

HYPERSINGULAR INTEGRAL EQUATIONS FOR PERIODIC ARRAYS OF PLANAR CRACKS IN A PERIODICALLY-LAYERED ANISOTROPIC ELASTIC SPACE UNDER ANTIPLANE SHEAR STRESS

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Acta mathematica Scientia 1999年第3期19卷 343-355页

作者： W.T.Ang (Faculty of Engineering, Universiti Malaysia sarawak, 94300 Kota samarahan, Malaysia)D.L. Clements(Department of Applied mathematics, University of Adelaide, sa5005, Australia) Univ Malaysia sarawak Fac Engn Kota Samarahan 94300 Malaysia Univ Adelaide Dept Math Appl Adelaide SA 5005 Australia

Hypersingular integral equations are derived for the problem of determining the antiplane shear stress around periodic arrays of planar cracks in a periodically-layered anisotropic elastic space. The unknown functions are directly related to the jump in the displacements across opposite crack faces. Once the integral equations are solved, crack parameters of interest, such as the clack tip stress intensity factors, may be readily *** some specific examples of the problem, the integral equations are solved numerically by using a collocation technique, in order to compute the relevant stress intensity factors.

关键词： Periodically-located cracks periodically-layered anisotropic material antiplane shear stress hypersingulal integral equations

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殷墟考古的统计与模糊方法

数学的实践与认识 2002年第5期32卷 718-722页

作者：周胜生杨奇安徽工程科技学院数理系芜湖241000 天津大学数学系天津300072

以殷墟墓葬分期为实例 ,阐述模糊方法用于考古优势的思考 ,提出确定隶属度的方法 :概率法 ,以及确定权值的方法 :模糊方程法 .将数理统计与模糊数学结合起来 ,给出了墓葬分期的模糊模型。

关键词：考古殷墟幕葬模糊数学隶属度权值回归