CoopAI-Route: DRL Empowered Multi-Agent Cooperative System for Efficient QoS-Aware Routing for Network Slicing in Multi-Domain SDN

The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this context.Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations.However,the existing IP(Internet Protocol)over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators.Conventional inter-domain routing methods,like Border Gateway Protocol(BGP),cannot make routing decisions based on performance,which frequently results in traffic flowing across congested paths that are never optimal.To address these issues,we propose CoopAI-Route,a multi-agent cooperative deep reinforcement learning(DRL)system utilizing hierarchical software-defined networks(SDN).This framework enforces network slicing in multi-domain networks and cooperative communication with various administrators to find performance-based routes in intra-and inter-domain.CoopAI-Route employs the Distributed Global Topology(DGT)algorithm to define inter-domain Quality of Service(QoS)paths.CoopAI-Route uses a DRL agent with a message-passing multi-agent Twin-Delayed Deep Deterministic Policy Gradient method to ensure optimal end-to-end routes adapted to the specific requirements of network slicing applications.Our evaluation demonstrates CoopAI-Route’s commendable performance in scalability,link failure handling,and adaptability to evolving topologies compared to state-of-the-art methods.

Dynamic Routing of Multiple QoS-Required Flows in Cloud-Edge Autonomous Multi-Domain Data Center Networks

The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and convergence.In this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain collaboration.Due to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward functions.Regarding the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the flows.In addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+MADDPG.Introducing a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network environment.The LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.

Multi-domain equivalent method for prediction of elastic modulus of complex fractured rock mass

Reliable estimation of deformation and failure behaviors of fractured rock mass is important for practical engineering design.This study proposes a multi-domain equivalent method for fracture network to estimate the deformation properties of complex fractured rock mass.It comprehends both the advantages of the discrete fracture network model and the equivalent continuum model to capture the features of discontinuities explicitly while reducing computational intensity.The complex fracture network is stochastically split into a number of subfracture networks according to the domain,length or angle.An analytical solution is derived to infer theoretically the relationship between the elastic moduli of the original complex fractured rock mass and the split subfractured rock masses by introducing a correction term based on the deformation superposition principle.Numerical simulations are conducted to determine the elastic moduli of split subfractured rock masses using universal distinct element code(UDEC),while the elastic modulus of the original model is estimated based on the currently proposed analytical relationship.The results show that the estimation accuracy with the current domainbased splitting model is far superior compared to those with the other two splitting models.Thus,the estimation method of elastic modulus of complex fractured rock mass based on domain splitting mode of fracture network is identified as the multi-domain equivalent method proposed in this paper.The reliability of this method is evaluated,and its high computational efficiency is demonstrated through exemplification with regard to different geometric configurations for stochastically artificial discrete fracture network.The proposed multi-domain equivalent method constructs the theoretical framework except for the regression analysis hypothesis compared to the density-reduced model equivalent method.

Multi-Domain Malicious Behavior Knowledge Base Framework for Multi-Type DDoS Behavior Detection

Due to the many types of distributed denial-of-service attacks(DDoS)attacks and the large amount of data generated,it becomes a chal-lenge to manage and apply the malicious behavior knowledge generated by DDoS attacks.We propose a malicious behavior knowledge base framework for DDoS attacks,which completes the construction and application of a multi-domain malicious behavior knowledge base.First,we collected mali-cious behavior traffic generated by five mainstream DDoS attacks.At the same time,we completed the knowledge collection mechanism through data pre-processing and dataset design.Then,we designed a malicious behavior category graph and malicious behavior structure graph for the characteristic information and spatial structure of DDoS attacks and completed the knowl-edge learning mechanism using a graph neural network model.To protect the data privacy of multiple multi-domain malicious behavior knowledge bases,we implement the knowledge-sharing mechanism based on federated learning.Finally,we store the constructed knowledge graphs,graph neural network model,and Federated model into the malicious behavior knowledge base to complete the knowledge management mechanism.The experimental results show that our proposed system architecture can effectively construct and apply the malicious behavior knowledge base,and the detection capability of multiple DDoS attacks occurring in the network reaches above 0.95,while there exists a certain anti-interference capability for data poisoning cases.

Performance Evaluation of Topologies for Multi-Domain Software-Defined Networking

Software-defined networking(SDN)is widely used in multiple types of data center networks,and these distributed data center networks can be integrated into a multi-domain SDN by utilizing multiple controllers.However,the network topology of each control domain of SDN will affect the performance of the multidomain network,so performance evaluation is required before the deployment of the multi-domain SDN.Besides,there is a high cost to build real multi-domain SDN networks with different topologies,so it is necessary to use simulation testing methods to evaluate the topological performance of the multi-domain SDN network.As there is a lack of existing methods to construct a multi-domain SDN simulation network for the tool to evaluate the topological performance automatically,this paper proposes an automated multi-domain SDN topology performance evaluation framework,which supports multiple types of SDN network topologies in cooperating to construct a multi-domain SDN network.The framework integrates existing single-domain SDN simulation tools with network performance testing tools to realize automated performance evaluation of multidomain SDN network topologies.We designed and implemented a Mininet-based simulation tool that can connect multiple controllers and run user-specified topologies in multiple SDN control domains to build and test multi-domain SDN networks faster.Then,we used the tool to perform performance tests on various data center network topologies in single-domain and multi-domain SDN simulation environments.Test results show that Space Shuffle has the most stable performance in a single-domain environment,and Fat-tree has the best performance in a multi-domain environment.Also,this tool has the characteristics of simplicity and stability,which can meet the needs of multi-domain SDN topology performance evaluation.

Horizontal-Based Orchestration for Multi-Domain SFC in SDN/NFV-Enabled Satellite/Terrestrial Networks

It's promising to use Software-Defined Networking(SDN) and Network Functions Virtualization(NFV) to integrate satellite and terrestrial networks. To construct network service function chains in such a multi-domain environment, we propose a horizontal-based Multi-domain Service Function Chaining(Md-SFC) orchestration framework. In this framework, multi-domain orchestrators can coordinate with each other to guarantee the end-to-end service quality. Intra-domain orchestrators also coordinate SDN controllers and NFV management components to implement intra-domain service function chains. Based on this, we further propose a heuristic SFC mapping algorithm with a cooperative inter-domain path calculation method to map service function chains to infrastructures. In this method, master multi-domain orchestrator and intra-domain orchestrators coordinate to select proper inter-domain links. We compare the cooperative method with a naive uncooperative way that domains' topology information is provided to the master multi-domain orchestrator and it calculates the shortest inter-domain path between intra-domain service function chains directly. Simulation results demonstrate that our solution is feasible. It is able to construct end-to-end performance guaranteed service function chain by horizontal-based cooperation. The cooperative inter-domain path calculation method decreasesthe mapping load for the master orchestrator and gets the same end-to-end performance.

Virtual 5G Network Embedding in a Heterogeneous and Multi-Domain Network Infrastructure

The pursuit of the higher performance mobile communications forces the emergence of the fifth generation mobile communication(5G). 5G network, integrating wireless and wired domain, can be qualified for the complex virtual network work oriented to the cross-domain requirement. In this paper, we focus on the multi-domain virtual network embedding in a heterogeneous 5G network infrastructure, which facilitates the resource sharing for diverse-function demands from fixed/mobile end users. We proposed the mathematical ILP model for this problem.And based on the layered-substrate-resource auxiliary graph and an effective six-quadrant service-type-judgment method, 5G embedding demands can be classified accurately to match different user access densities. A collection of novel heuristic algorithms of virtual 5G network embedding are proposed. A great deal of numerical simulation results testified that our algorithm performed better in terms of average blocking rate, routing latency and wireless/wired resource utilization, compared with the benchmark.

A PSO Based Multi-Domain Virtual Network Embedding Approach

This paper proposed a multi-domain virtual network embedding algorithm based on multi-controller SDN architecture. The local controller first selects candidate substrate nodes for each virtual node in the domain. Then the global controller abstracts substrate network topology based on the candidate nodes and boundary nodes of each domain, and applies Particle Swarm Optimization Algorithm on it to divide virtual network requests. Each local controller then embeds the virtual nodes of the divided single-domain virtual network requests in the domain, and cooperates with other local controllers to embed the inter-domain virtual links. Simulation experimental results show that the proposed algorithm has good performance in reducing embedding cost with good stability and scalability.

Stabilized Multi-domain Simulation Algorithms and Their Application in Simulation Platform for Forging Manipulator

Most researches focused on the analytical stabilized algorithm for the modular simulation of single domain, e.g., pure mechanical systems. Only little work has been performed on the problem of multi-domain simulation stability influenced by algebraic loops. In this paper, the algebraic loop problem is studied by a composite simulation method to reveal the internal relationship between simulation stability and system topologies and simulation unit models. A stability criterion of multi-domain composite simulation is established, and two algebraic loop compensation algorithms are proposed using numerical iteration and approximate function in multi-domain simulation. The numerical stabilized algorithm is the Newton method for the solution of the set of nonlinear equations, and it is used here in simulation of the system composed of mechanical system and hydraulic system. The approximate stabilized algorithm is the construction of response surface for inputs and outputs of unknown unit model, and it is utilized here in simulation of the system composed of forging system, mechanical and hydraulic system. The effectiveness of the algorithms is verified by a case study of multi-domain simulation for forging system composed of thermoplastic deformation of workpieces, mechanical system and hydraulic system of a manipulator. The system dynamics simulation results show that curves of motion and force are continuous and convergent. This paper presents two algorithms, which are applied to virtual reality simulation of forging process in a simulation platform for a manipulator, and play a key role in simulation efficiency and stability.

Multi-domain modeling and simulation of proportional solenoid valve

A multi-domain nonlinear dynamic model of a proportional solenoid valve was presented.The electro-magnetic,mechanical and fluid subsystems of the valve were investigated,including their interactions.Governing equations of the valve were derived in the form of nonlinear state equations.By comparing the simulated and measured data,the simulation model is validated with a deviation less than 15%,which can be used for the structural design and control algorithm optimization of proportional solenoid valves.

SDN Orchestration for Dynamic End-to-End Control of Data Center Multi-Domain Optical Networking

New and emerging use cases, such as the interconnection of geographically distributed data centers(DCs), are drawing attention to the requirement for dynamic end-to-end service provisioning, spanning multiple and heterogeneous optical network domains. This heterogeneity is, not only due to the diverse data transmission and switching technologies, but also due to the different options of control plane techniques. In light of this, the problem of heterogeneous control plane interworking needs to be solved, and in particular, the solution must address the specific issues of multi-domain networks, such as limited domain topology visibility, given the scalability and confidentiality constraints. In this article, some of the recent activities regarding the Software-Defined Networking(SDN) orchestration are reviewed to address such a multi-domain control plane interworking problem. Specifically, three different models, including the single SDN controller model, multiple SDN controllers in mesh, and multiple SDN controllers in a hierarchical setting, are presented for the DC interconnection network with multiple SDN/Open Flow domains or multiple Open Flow/Generalized Multi-Protocol Label Switching( GMPLS) heterogeneous domains. I n addition, two concrete implementations of the orchestration architectures are detailed, showing the overall feasibility and procedures of SDN orchestration for the end-to-endservice provisioning in multi-domain data center optical networks.

Cost-Aware Multi-Domain Virtual Data Center Embedding

Virtual data center is a new form of cloud computing concept applied to data center. As one of the most important challenges, virtual data center embedding problem has attracted much attention from researchers. In data centers, energy issue is very important for the reality that data center energy consumption has increased by dozens of times in the last decade. In this paper, we are concerned about the cost-aware multi-domain virtual data center embedding problem. In order to solve this problem, this paper first addresses the energy consumption model. The model includes the energy consumption model of the virtual machine node and the virtual switch node, to quantify the energy consumption in the virtual data center embedding process. Based on the energy consumption model above, this paper presents a heuristic algorithm for cost-aware multi-domain virtual data center embedding. The algorithm consists of two steps: inter-domain embedding and intra-domain embedding. Inter-domain virtual data center embedding refers to dividing virtual data center requests into several slices to select the appropriate single data center. Intra-domain virtual data center refers to embedding virtual data center requests in each data center. We first propose an inter-domain virtual data center embedding algorithm based on label propagation to select the appropriate single data center. We then propose a cost-aware virtual data center embedding algorithm to perform the intra-domain data center embedding. Extensive simulation results show that our proposed algorithm in this paper can effectively reduce the energy consumption while ensuring the success ratio of embedding.

Link-Vertex Topology Aggregation for Multi-domain Path Computation with Hierarchical PCE Architecture

Inter-domain path computing is one big issue in multi-domain networks. The Hierarchical Path Computing Element (H-PCE) is a semi-central architecture for computing inter-domain path. To facilitate H-PCE in inter-domain path computing, this paper proposed a topology aggregation scheme to abstract the edge nodes and their connected inter-domain link as one vertex to achieve more optimal paths and confidentiality guarantee. The effectiveness of the scheme has been demonstrated on solving wavelength routing in multi-domain Wavelength Division Multiplexing (WDM) network via simulation. Simulation results show that this scheme reduces at least 10% inter-domain blocking probability, compared with the traditional Domain-to-the-Node (DtN) scheme.

A distributed role-based access control model for multi-domain environments

Access control in multi-domain environments is an important question in building coalition between domains. Based on the RBAC access control model and the concepts of secure domain, the role delegation and role mapping are proposed, which support the third-party authorization. A distributed RBAC model is then presented. Finally implementation issues are discussed.

Multi-domain High-Resolution Platform for Integrated Spectroscopy and Microscopy Characterizations

In recent decades,materials science has experienced rapid development and posed increasingly high requirements for the characterizations of structures,properties,and performances.Herein,we report on our recent establishment of a multi-domain(energy,space,time)highresolution platform for integrated spectroscopy and microscopy characterizations,offering an unprecedented way to analyze materials in terms of spectral(energy)and spatial mapping as well as temporal evolution.We present several proof-of-principle results collected on this platform,including in-situ Raman imaging(high-resolution Raman,polarization Raman,low-wavenumber Raman),time-resolved photoluminescence imaging,and photoelectrical performance imaging.It can be envisioned that our newly established platform would be very powerful and effective in the multi-domain high-resolution characterizations of various materials of photoelectrochemical importance in the near future.

Multi-Domain Collaborative Recommendation with Feature Selection

Collaborative f iltering, as one of the most popular techniques, plays an important role in recommendation systems. However,when the user-item rating matrix is sparse,its performance will be degenerate. Recently,domain-specific recommendation approaches have been developed to address this problem.The basic idea is to partition the users and items into overlapping domains, and then perform recommendation in each domain independently. Here, a domain means a group of users having similar preference to a group of products. However, these domain-specific methods consisting of two sequential steps ignore the mutual benefi t of domain segmentation and recommendation. Hence, a unified framework is presented to simultaneously realize recommendation and make use of the domain information underlying the rating matrix in this paper. Based on matrix factorization,the proposed model learns both user preferences of multiple domains and preference selection vectors to select relevant features for each group of products. Besides, local context information is utilized from the user-item rating matrix to enhance the new framework.Experimental results on two widely used datasets, e.g., Ciao and Epinions, demonstrate the effectiveness of our proposed model.

3D seismic response of a 2D hill-valley staggered topography modeled by a 2.5D multi-domain IBEM

A two and a half dimensional(2.5D)multi-domain indirect boundary element method(IBEM)is developed to study the wave scattering of obliquely incident P-,SV-and SH-waves by a hill-valley staggered topography in a multi-layered half-space.The IBEM algorithm includes using 2.5D full-space and half-space Green’s functions to construct scattered fields in decomposed closed and opened half-space regions,respectively,and using the dynamic stiffness method to solve the free fields.All regions are finally integrated by introducing the compatibility conditions to obtain the total wave fields.The proposed 2.5D IBEM has the flexibility in dealing with complex boundaries by directly applying the fictitious loads on the regions’boundaries,with a less storage requirement compared to the full 3D models.Besides,by combining the specific advantages of the two kinds of Green’s functions,the method is well suitable for handling coupled topographies with high accuracy.The method is validated by comparison with published results for a single valley as well as a single hill topography.The effects of height-to-width ratio of hill and layering on dynamic responses are further parametrically investigated by numerical implementations in frequency domain.Results show that the interaction between valley and hills can lead to a more significant amplification within the valley region,and dynamic responses are deeply influenced by the height-to-width of hill,simultaneously depending on incident angle and frequency.Besides,the site effects become more complex when the stratification feature is taken into account.

Approach for Local Multi-Domain Cognition in Cognitive Network

During the evolution from cognitive radio to cognitive networks,the environment cognition extended from wireless environments to network and user environments.To understand the basic theory of Local Multi-Domain Cognition(LMDC),and to provide a theoretical basis for further study in cooperative multi-domain cognition and initiative multi-domain cognition,the LMDC is investigated in this paper.A Local Single-Domain Cognitive(LSDC)approach is first proposed based on multidimensional edge detection theory.This approach can divide the parameter space that describes the single-domain environment into different areas,and can represent each area with an identifier.Using this as a foundation,the single-domain environment is extended to multi-domain environments,and an LMDC approach is presented to describe the LMDC environment.The paper concludes by introducing two examples and the corresponding analysis to illustrate the feasibility of the proposed LMDC approach.

Design of Multi-domain Collaborative Simulation System for Dual Clutch Transmission Based on CAN Bus

A multi-domain collaborative simulation(MDCS) system for dual clutch transmission(DCT) was presented based on controller area network(CAN) bus.An interface card of CAN bus was designed,in which MDCS subsystems were linked as the nodes according to the interface mode of MDCS.A DCT simulation model was established based on Matlab/Simdriveline,whose running process was accurately controlled by the designed control system.The playback system of vehicle state(VPS) was proposed whose input was the road-test data,with a real vehicle test environment for the development of transmission control unit(TCU) being provided.A DCT kinematic system model was set up,and the running status of DCT parts could be displayed in real time.The functions of MDCS were verified based on the extra-urban driving cycle(EUDC) and the vehicle road-test data respectively.The results show the functions of MDCS are accomplished,and the unified supporting platform for the development of TCU is achieved by MDCS.

Resolution for Conflicts of Inter-Operation in Multi-Domain Environment

This paper proposes a method to formalize the interoperation in multi-domain environment. Through employing the algebra method, we conclude four types of the conflicts for the interoperation, and analyzes the cause of the policy conflicts. For each type of conflicts, we formalize it and proposes the method of detection and resolution. Finally, the method is illuminated be effective through comparing our work with others.