Flow Control In Networks Research Articles

Descriptive analysis of wide area network flow control internet traffic on Metro-E 100 Mbps campus network

QoS in computer networking is the capability to provide better service to network traffic over various technologies such as ethernet and IP networks. This paper presents a descriptive analysis of WAN flow control and internet traffic on a Metro-E campus network. Issues on network congestion and delay in network QoS where internet traffic is gradually increasing, resulting in bursts of network capacity that affect network QoS. The method implies 12 months data collection and analysis on protocol, bytes and packets inbound and correlation between parameters on the Metro-E 100 Mbps campus network. The result presents heavy-tailed distributions on an inbound packet kurtosis value of 347 and an outbound packet kurtosis value of 780. Bytes outbound and inbound are skewed at 122 and right at 17 respectively. The average amount of data inbound and outbound is 458.5 MB and 34.8 MB. Protocol 6 TCP presents the highest amount of -traffic and a weak positive correlation at 0.104 exists between the inbound and outbound packets and bytes on the network. The correlation coefficient's 95% confidence interval ranges between 0.096 and 0.111. This research is significant in the future deployment of traffic scheduling, policing, and shaping algorithms for QoS bandwidth management on the WAN Metro-E campus network.

Energy Consumption Management of Residential Appliances Based on Load Signatures Decomposition

Nowadays, energy consumption management techniques in the residential side have gained significant importance due to their considerable influence on the control of power flow in distribution networks and especially the possibility of managing a huge part of domestic electrical demand during peak-load hours. Since the customer’s data are recorded in an aggregated form, therefore, in order to apply control approaches, it is necessary to use load pattern evaluation techniques (load signature). These methods capable to decomposition effective features that help control approaches to implement with more accuracy. In this article, features of residential loads have been extracted by using the signature of the aggregated consumer’s demand. Then these features have been evaluated by methods such as logistic regression, k-nearest neighborhood, and decision tree. By assessing the results, it was determined that among the extracted features, the first two features (consumed power and injected harmonics) covered more than 89% of the variance of the entire set, and with the help of using the principal component analysis method, it was determined that by reducing the number of features to 2, a considerable amount of computation is reduced and only about 4% of the accuracy is reduced. Also, the convolutional neural network approach was used to estimate the type of load, and by identifying controllable loads and applying remote home energy management methods, it was found that by increasing participation up to 80%, more than 41% of peak-load consumption could be shifted to off-peak hours.

Joint Energy-Efficiency Communication Optimization and Perimeter Traffic Flow Control for Multi-Region LTE-V2V Networks

Joint Energy-Efficiency Communication Optimization and Perimeter Traffic Flow Control for Multi-Region LTE-V2V Networks

Testing and Validation of a 200 kVA SSSC Prototype for Power Flow Control

Power flow control in transmission networks requires new approaches to deal with the uncertainties in the power flow patterns caused by the massive integration of renewable energy generators and the difficulties for constructing new transmission corridors, due to environmental restrictions and social opposition. One solution explored nowadays by utilities is the installation of a Static Synchronous Series Compensator (SSSC). This paper presents a real test bench for an SSSC. The test bench allows verifying the real control devices of a substation and the PLC close-loop control of the SSSC. The proposed SSSC test bench is a scale FACTS device of a 50MVAs real SSSC that will be placed in the Spanish transmission grid. In this paper the design of the test bench is presented, including the main magnitudes of both grid and SSSC, along with the substation SSSC control scenario and the SSSC close-loop control strategy. Besides, the SSSC test bench dynamics and response has been validated using a model of the SSSC and its controls, developed in Matlab/SimPowerSystems. The paper shows the results of the simulation and compares them with the magnitudes measured in the test bench.

Decentralized control of flow in complex networks

A decentralized control algorithm for routing flow in complex networks is proposed. The aim is to fairly distribute the supply/demand among the nodes while maintaining maximum flow in the network and satisfying the flow limits of the nodes and links. The algorithm is also used for flow re-routing after a failure in (or attack on) a network to avoid a cascading failure while maintaining the maximum flow in the network. The proposed algorithm is based only on the information about the closest neighbours of each node. Consensus rules are used to achieve fairness between the nodes in the network. The performance of the proposed algorithm is demonstrated by simulations.

On the Structure of Feedback Potential Difference Games

A static potential game is a non-cooperative game for which there exists a fictitious function, also referred to as a potential function, whose optimizers provide a Nash equilibrium of the associated non-cooperative game. In this paper, we study non-zero-sum finite-horizon difference games with feedback information structure which admit a potential game structure. We provide conditions for the existence of an optimal control problem such that the optimal solution of this problem provides a feedback Nash equilibrium of the corresponding non-cooperative game. We specialize the obtained results to a linear-quadratic setting so as to obtain these verifiable existence conditions in terms of the problem data. Finally, we illustrate our results using a network flow control problem.

Distributed Resource Allocation and Flow Control Algorithms for mmWave IAB Networks

This paper presents a new distributed slot reservation frame-work for joint resource allocation and flow control in mmWave IAB networks. We derive the Dynamic Slot Reservation (DSR) algorithm from a novel approach to solve a minimum clearing time linear program in a completely distributed manner. The algorithm to solve this problem, the Static Slot Reservation (SSR) algorithm, is also a contribution of the paper. We compare the delay performance of the DSR algorithm with a well known optimal, centralized algorithm, the joint-MWM algorithm, for a realistic IAB network scenario of multi-hop flows. We show that flows that traverse several links have significantly lower delays under DSR than under the joint-MWM algorithm. This paper also provides an instantaneous rate control policy for IAB networks which changes flow rates based on the number of flows at each node in the network. The flow rates under this policy are the same as the steady-state flow rates achieved by the DSR algorithm. We prove that the proposed flow control policy provides stability for all flow arrival rate vectors that are achievable by any flow control policy. This paper provides distributed admission control policies to provide rate and/or latency guarantees to flows under dynamic scenarios with stochastic flow arrivals and changing access link rates.

Cooling Pipe Network System in the Quenching Green Equipment Design Method Based on the “Solid Contact-Fluid Heat Transfer” Mode

As a typical thin plate part, a circular saw blade matrix is prone to deformation and cracking due to uneven surface cooling rate during heat treatment. Simultaneously, the traditional quenching method is easy to produce a low product qualification rate and serious environmental severe when processing thin plate parts. The quenching device designed in this paper is to achieve the non-contact quenching between the processed parts and the quenching medium through the heat transfer of the fluid in the cooling pipe. The structure design of the internal cooling channel will directly affect the temperature field distribution of the quenching device, thus determining the microstructure and final performance of the product. Therefore, based on the microstructure transformation mechanism and pipe network flow control theory, combined with the heat transfer theory and other relevant theoretical bases, this paper established the mathematical model of internal cooling system parameters. Finally, MATLAB is applied to solve the fluid network topology model. It provides a reliable and general research method for cooling pipe networks in quenching devices based on the “Solid Contact-Fluid Heat Transfer” Mode.

SECURING CENTRALIZED SDN CONTROL WITH DISTRIBUTED BLOCKCHAIN TECHNOLOGY

Software Defined Networks (SDN) advocates segregation of network control logic, forwarding functions and management applications into different planes to achieve network programmability, automated and dynamic flow control in next generation networks. It promotes deployment of novel and augmented network management functions to have flexible, robust, scalable and cost-effective network deployments. All these features introduce new research challenges and require secure communication protocols among the segregated network planes. This manuscript focuses on the security issue of southbound interface which operates between the SDN control and data plane. We have highlighted the security threats associated with an unprotected southbound interface and the issues related with the existing TLS based security solution. A lightweight blockchain based decentralized security solution is proposed for southbound interface to secure the resources of logically centralized SDN controllers and distributed forwarding devices from opponents. The proposed mechanism can operate in multi-domain SDN deployment and can be used with wide range of network controllers and data plane devices. In addition to it, the proposed security solution is analyzed in terms of security features, communication and reauthentication overhead.

Guest Editorial: Recent trends of power flow control in power system networks

Guest Editorial: Recent trends of power flow control in power system networks

Electromagnetic transient model and field-circuit coupling numerical calculation of Sen transformer based on finite-element method

• A finite-element (FE) model of electromagnetic transient of Sen transformer (ST) with field-circuit coupling is proposed, and the proposed model can characterize the effects of core and winding topology on the internal magnetic field distribution. • The proposed FE model can characterize the electromagnetic field changes of the ST device under different conditions, such as short-circuit fault, injected harmonics, and dynamic power flow control in the external power system. • The electromagnetic transient field-circuit co-simulation of the ST device and external power system is realized. The conventional electromagnetic transient model of Sen transformer (ST) is mainly established by the magnetic equivalent circuit method, which can be used for the fast calculation of transient characteristics for ST. Unfortunately, this approach may lead to oversimplification and missing significant information in the modeling process. To accurately calculate the transient electromagnetic field and reveal the internal magnetic field distribution of the ST under different operating conditions, an electromagnetic transient model and field-circuit coupling numerical calculation of ST based on finite-element (FE) method is proposed in this paper. The proposed model can characterize the effects of core and winding topology on the internal magnetic field distribution, as well as the complex nonlinear property of core materials, such as saturation, eddy current, and hysteresis. The field-circuit coupling method enables the FE model to establish a connection with external networks and realize the electromagnetic transient field-circuit co-simulation of the ST device and external power system. The case studies are performed on a FE model of the ST and a two-machine transmission system. The corresponding winding voltage and current variations of the ST in the presence of short-circuit fault, injected harmonics, and dynamic power flow control in the external networks are analyzed. The numerical calculation and co-simulation results of the proposed FE model of the ST and the external networks are compared with the commercial FE software, which demonstrates the effectiveness of the proposed FE model of the ST. Moreover, the co-simulation results of dynamic power flow control show that the ST can adjust the power flow distribution of two transmission lines through changing compensation voltage.

Communication‐free decentralized power flow control of unified power flow controllers and phase‐shifting transformers in high voltage transmission systems

AbstractConventional phase‐shifting transformers (PST) have been utilized for power flow control in transmission networks for many years. Compared to the slow reacting PSTs, recently trending unified power flow controllers (UPFC) enable much faster power flow control. This paper introduces a decentralized power flow control scheme for power flow controllers (PFCs) without the need for communication between the PFCs. For each PFC, an influence area is defined. The line loading of the transmission lines in this influence area is monitored in real‐time operation and if there is an overloading of a line, a feedback control scheme is used to mitigate the overloading of the line. As the power flow control of UPFC is dependent of the network topology and the UPFC converter limit, additional control measures are introduced to circumvent potential critical scenarios. Supplementary control measures are also developed to increase the robustness of control scheme for the simultaneous operation of UPFC with slow reacting PST. Using RMS simulation in DIgSILENT PowerFactory, the developed control method is validated in the IEEE 68‐Bus NETS/NYPS test bench network. The method is also validated for UPFCs with overlapping influence areas and the combination of fast acting UPFCs and slow acting PST devices.

A decentralized feedback approach for flow control in highway traffic networks

Finite-time optimal feedback control for highway traffic networks under information constraints is studied. The primary objective is to design a fully decentralized state-feedback controller with ramp metering and variable speed limit control actions, with no information exchange between local controllers, that ensures feasibility and improves a global performance index. The design of a decentralized feedback controller with a one-hop information structure is examined, wherein the optimum outflow rate from each segment of the network depends only on the state of that segment and the state of all other segments directly connected to the downstream junction of that segment. It is demonstrated that when cost/constraints can be modeled or approximated by piecewise-affine functions, the control law has a closed-form state-feedback realization. The decentralization is based on the truncation of non-local variables in local optimization problems. The resulting decentralized control scheme has a simple closed-form representation and is scalable to arbitrary large networks; moreover, we demonstrate that, under certain conditions, with respect to certain meaningful performance indexes, the performance loss due to decentralization is zero; namely, the centralized optimal controller has a decentralized realization with a one-hop information structure.

Construction of Intelligent Substation-Optimized Networking Communication Network Based on Source-Network-Load Interaction Environment.

Smart grids, which possess flexibility, cleanliness, safety, economy, and friendliness, have drawn a lot of attention from all over the world in an era of rapid social and economic development, power technology change, and energy and environmental constraints. However, there are still issues with the design, installation, and operation of smart substations, such as insufficient LAN integration, difficulty quantifying network performance, and inability to keep track of communication. The basic meaning and key technologies of substation communication standards are used as the research object in this paper, and the basic attributes of substation data flow, such as source, type, and function, are qualitatively analyzed. The mathematical model that is most closely fitted is 2.8% more effective. The research object is the topology of the process bus. Through the comparison of various solutions, including star topology, ring topology, bus topology, and mesh topology, the advantages and disadvantages of each topology networking scheme are revealed along with the particular functional requirements of the substation process layer. Further discussion is given to the crucial topology-related technologies of network congestion and flow control.

Pandemic policy assessment by artificial intelligence

Mobility-control policy is a controversial nonpharmacological approach to pandemic control due to its restriction on people’s liberty and economic impacts. Due to the computational complexity of mobility control, it is challenging to assess or compare alternative policies. Here, we develop a pandemic policy assessment system that employs artificial intelligence (AI) to evaluate and analyze mobility-control policies. The system includes three components: (1) a general simulation framework that models different policies to comparable network-flow control problems; (2) a reinforcement-learning (RL) oracle to explore the upper-bound execution results of policies; and (3) comprehensive protocols for converting the RL results to policy-assessment measures, including execution complexity, effectiveness, cost and benefit, and risk. We applied the system to real-world metropolitan data and evaluated three popular policies: city lockdown, community quarantine, and route management. For each policy, we generated mobility-pandemic trade-off frontiers. The results manifest that the smartest policies, such as route management, have high execution complexity but limited additional gain from mobility retention. In contrast, a moderate-level intelligent policy such as community quarantine has acceptable execution complexity but can effectively suppress infections and largely mitigate mobility interventions. The frontiers also show one or two turning points, reflecting the safe threshold of mobility retention when considering policy-execution errors. In addition, we simulated different policy environments and found inspirations for the current policy debates on the zero-COVID policy, vaccination policy, and relaxing restrictions.

Distributed model predictive control methods for intermodal transport cooperative planning based on ADMM

The cooperative planning in intermodal transport networks can obtain the global optimal decision under the premise of ensuring the data privacy of each role in the cooperation and avoiding massive data transmission. For the control of container flow in intermodal transport networks, the distributed model predictive control (DMPC) method can effectively realize cooperative planning, but the convergence speed of the existing DMPC methods is slow. Therefore, this study attempts to construct faster DMPC methods for cooperative planning. The Jacobi proximal distributed model predictive control (JP-DMPC) and dual consensus distributed model predictive control (DC-DMPC) methods are constructed for container flow control based on two variants of alternating direction method of multipliers (ADMM). The simulation experiments prove that the convergence speed of JP-DMPC and DC-DMPC methods is higher than that of the state-of-the-art method on the premise that the time cost and interaction data volume of each iteration do not change much, and the DC-DMPC method improves planning speed particularly significantly. This study provides new methods for intermodal transport cooperative planning and has significance for the development of synchromodal transport.

Generalized Control of the Power Flow in Local Area Energy Networks

Local area energy networks (E-LANs) are cyber-physical systems whose physical layer is a meshed low-voltage microgrid fed by a multiplicity of sources, i.e., utilities, energy storage systems, and distributed power sources. The cyber layer includes distributed measurement, control, and communication units, located at end-user premises, as well as centralized supervision and dispatchment control. As compared with standard microgrid, the E-LAN encompasses the ability for end-users to actively contribute to the operation of the microgrid while acting as independent energy traders in the electrical market. Operational goals include active contribution of end-users to power sharing, loss reduction, voltage stability, demand response, fault identification and clearing, isolation of sub-grids for maintenance, islanding, and black start. Economic goals include the possibility, for each end-user, to decide in every moment, based on convenience, how his energy and power capacity is shared with other users, e.g., for demand response or to trade energy in the electric market. This paper introduces a comprehensive theoretical approach of E-LAN control to achieve all the above operational goals while providing a high level of dynamic protection against faults or other events affecting the system functionality, e.g., overloads or fast transients. It shows that meshed microgrids are the necessary infrastructure to implement the desired functionalities.

Intelligent Network Traffic Control Based on Deep Reinforcement Learning

This paper studies the problems of load balancing and flow control in data center network, and analyzes several common flow control schemes in data center intelligent network and their existing problems. On this basis, the network traffic control problem is modeled with the goal of deep reinforcement learning strategy optimization, and an intelligent network traffic control method based on deep reinforcement learning is proposed. At the same time, for the flow control order problem in deep reinforcement learning algorithm, a flow scheduling priority algorithm is proposed innovatively. According to the decision output, the corresponding flow control and control are carried out, so as to realize the load balance of the network. Finally, experiments show, the network traffic bandwidth loss rate of the proposed intelligent network traffic control method is low. Under the condition of random 60 traffic density, the average bisection bandwidth obtained by the proposed intelligent network traffic control method is 4.0mbps and the control error rate is 2.25%. The intelligent network traffic control method based on deep reinforcement learning has high practicability in the practical application process, and fully meets the research requirements.

Research of functioning processes of wireless sensor networks

The article is devoted to the research of problems of optimal control of data flow routing in heterogeneous sensor networks of variable topology under conditions of constraints and uncertainties. To solve the problem of synthesis of optimal data transmission routes in sensor networks, it is necessary to synthesize a graph model, formally define the optimization problem, investigate the processes of functioning of network elements and obtain formalized descriptions of the dependence of network elements. The mathematical model of functioning of the distributed system of intelligent data flow control in sensor networks of variable topology is considered based on the formal model of the functioning of the distributed system of intelligent network management, the properties of the processes of optimal load management of nodes and the data network as a whole are investigated. The results of the research allowed to obtain formal descriptions of the dependence of the load of the computing system of the sensor network on the time of the data transmission process, waiting time, service time on the load of the computing system of the sensor network, to determine quantitative indicators of delay and loss of data packets depending on the functioning modes.

Dynamics of water conveying SWCNT nanoparticles and swimming microorganisms over a Riga plate subject to heat source/sink

Electromagnetohydrodynamic (EMHD) is very important because of its numerous advantages such as flow control in fluidics networks, fluid pumping, thermal reactors, mixing, fluid stirring, liquid chromatography, and micro coolers. Based on the above applications in this article discussed the electromagnetic forces on the SWCNT/water flow with microorganisms over a Riga plate subject to slip effects. In addition, the uniform heat source/sink effect is used in the energy equation, as well as the thermophoretic effect in the concentration equation. The governing nonlinear system of partial differential equations (PDEs) was reduced to ordinary differential equations (ODEs) by applying the appropriate similarity variables. Hence, Runge-Kutta-Fehlberg (RKF-45) method was applied to numerically solve the extremely nonlinear system. Based on the analysis of the results, it is worth concluding that raising the role of slip effects lowers the velocity, temperature, and concentration curves, while increasing the solid volume fraction increases the temperature, concentration, and motile microorganism density.