Reliable and Load Balance-Aware Multi-Controller Deployment in SDN

Software Defined Networking(SDN) provides flexible network management by decoupling control plane and data plane. However, such separation introduces the issues regarding the reliability of the control plane and controller load imbalance in the distributed SDN network, which will cause the low network stability and the poor controller performance. This paper proposes Reliable and Load balance-aware Multi-controller Deployment(RLMD) strategy to address the above problems. Firstly, we establish a multiple-controller network model and define the relevant parameters for RLMD. Then, we design the corresponding algorithms to implement this strategy. By weighing node efficiency and path quality, Controller Placement Selection(CPS) algorithm is introduced to explore the reliable deployments of the controllers. On this basis, we design Multiple Domain Partition(MDP) algorithm to allocate switches for controllers according to node attractability and controller load balancing rate, which could realize the reasonable domain planning. Finally, the simulations show that, compared with the typical strategies, RLMD has the better performance in improving the reliability of the control plane and balancing the distribution of the controller loads.

A Distributed Decision Mechanism for Controller Load Balancing Based on Switch Migration in SDN

Software Defined Networking(SDN) provides flexible network management by decoupling control plane from data plane. And multiple controllers are deployed to improve the scalability and reliability of the control plane, which could divide the network into several subdomains with separate controllers. However, such deployment introduces a new problem of controller load imbalance due to the dynamic traffic and the static configuration between switches and controllers. To address this issue, this paper proposes a Distribution Decision Mechanism(DDM) based on switch migration in the multiple subdomains SDN network. Firstly, through collecting network information, it constructs distributed migration decision fields based on the controller load condition. Then we choose the migrating switches according to the selection probability, and the target controllers are determined by integrating three network costs, including data collection, switch migration and controller state synchronization. Finally, we set the migrating countdown to achieve the ordered switch migration. Through verifying several evaluation indexes, results show that the proposed mechanism can achieve controller load balancing with better performance.

A Sender-Initiated Fuzzy Logic Contrnol Method for Network Load Balancing

In this paper, a sender-initiated protocol is applied which uses fuzzy logic control method to improve computer networks performance by balancing loads among computers. This new model devises sender-initiated protocol for load transfer for load balancing. Groups are formed and every group has a node called a designated representative (DR). During load transferring processes, loads are transferred using the DR in each group to achieve load balancing purposes. The simulation results show that the performance of the protocol proposed is better than the compared conventional method. This protocol is more stable than the method without using the fuzzy logic control.

A Receiver-Initiated Approach with Fuzzy Logic Control in Load Balancing

This paper proposes a new approach for load balancing by using receiver-initiated load transfer method. Usually data transfer for load balancing starts from a sender node. This is what called a sender-initiated method. In this paper, instead, a load balancing action starts from a receiver node;the receiver node initiates load balancing for asking a sender node for load transfer. Fuzzy logic control is applied in this approach to avoid using a fixed threshold value in load balancing in ad-hoc networks. Performance for the receiver-initiated approach is evaluated and compared with other load balancing approaches—BID protocol, fuzzy logic sender-initiated algorithm and non-fuzzy (threshold based) receiver-initiated algorithm. The results show that the receiver-initiated approach improves network performance by comparing with the other three.

Adaptive Server Load Balancing in SDN Using PID Neural Network Controller

Web service applications are increasing tremendously in support of high-level businesses.There must be a need of better server load balancing mechanism for improving the performance of web services in business.Though many load balancing methods exist,there is still a need for sophisticated load bal-ancing mechanism for not letting the clients to get frustrated.In this work,the ser-ver with minimum response time and the server having less traffic volume were selected for the aimed server to process the forthcoming requests.The Servers are probed with adaptive control of time with two thresholds L and U to indicate the status of server load in terms of response time difference as low,medium and high load by the load balancing application.Fetching the real time responses of entire servers in the server farm is a key component of this intelligent Load balancing system.Many Load Balancing schemes are based on the graded thresholds,because the exact information about the networkflux is difficult to obtain.Using two thresholds L and U,it is possible to indicate the load on particular server as low,medium or high depending on the Maximum response time difference of the servers present in the server farm which is below L,between L and U or above U respectively.However,the existing works of load balancing in the server farm incorporatefixed time to measure real time response time,which in general are not optimal for all traffic conditions.Therefore,an algorithm based on Propor-tional Integration and Derivative neural network controller was designed with two thresholds for tuning the timing to probe the server for near optimal perfor-mance.The emulation results has shown a significant gain in the performance by tuning the threshold time.In addition to that,tuning algorithm is implemented in conjunction with Load Balancing scheme which does not tune thefixed time slots.

Load Balancing Algorithm for Migrating Switches in Software-Dened Vehicular Networks

In Software-Dened Networks(SDN),the divergence of the control interface from the data plane provides a unique platform to develop a programmable and exible network.A single controller,due to heavy load trafc triggered by different intelligent devices can not handle due to it’s restricted capability.To manage this,it is necessary to implement multiple controllers on the control plane to achieve quality network performance and robustness.The ow of data through the multiple controllers also varies,resulting in an unequal distribution of load between different controllers.One major drawback of the multiple controllers is their constant conguration of the mapping of the switch-controller,quickly allowing unequal distribution of load between controllers.To overcome this drawback,Software-Dened Vehicular Networking(SDVN)has evolved as a congurable and scalable network,that has quickly achieved attraction in wireless communications from research groups,businesses,and industries administration.In this paper,we have proposed a load balancing algorithm based on latency for multiple SDN controllers.It acknowledges the evolving characteristics of real-time latency vs.controller loads.By choosing the required latency and resolving multiple overloads simultaneously,our proposed algorithm solves the loadbalancing problems with multiple overloaded controllers in the SDN control plane.In addition to the migration,our algorithm has improved 25%latency as compared to the existing algorithms.

Load balancing strategy of heterogeneous wireless networks based on multi-hop routing algorithm of ad hoc network

Because of different system capacities of base station （BS） or access point （AP） and ununiformity of traffic distribution in different cells, quantities of new call users may be blocked in overloaded cell in communication hot spots. Whereas in some neighboring under-loaded cells, bandwidth may be superfluous because there are only few users to request services. In order to raise resource utilization of the whole heterogeneous networks, several novel load balancing strategies are proposed, which combine the call ad- mission control policy and multi-hop routing protocol of ad-hoc network for load balancing. These loadbalancing strategies firstly make a decision whether to admit a new call or not by considering some parameters like load index and route cost, etc., and then transfer the denied users into neighboring under-loaded cell with surplus channel according to optimum multi-hop routing algorithm. Simulation results show that the proposed load balancing strategies can distribute traffics to the whole heterogeneous wireless netorks, improve the load balance index efficiently, and avoid the call block phenomenon almost absolutely.

Effectively Handling Network Congestion and Load Balancing in Software-Defined Networking

The concept of Software-Defined Networking(SDN)evolves to overcome the drawbacks of the traditional networks with Internet Protocol(I.P.)packets sending and packets handling.The SDN structure is one of the critical advantages of efficiently separating the data plane from the control plane tomanage the network configurations and network management.Whenever there aremultiple sending devices inside the SDNnetwork,theOpenFlow switches are programmed to handle the limited number of requests for their interface.When the recommendations are exceeded from the specific threshold,the load on the switches also increases.This research article introduces a new approach named LBoBS to handle load balancing by adding the load balancing server to the SDN network.Besides,it is used to maximize SDN’s reliability and efficiency.It also works in coordination with the controller to effectively handle the load balancing policies.The load balancing server is implemented to manage the switches load effectively.Results are evaluated on the NS-3 simulator for packet delivery,bandwidth utilization,latency control,and packet decision ratios on the OpenFlow switches.It has been found that the proposed method improved SDN’s load balancing by 70%compared to the previous state-of-the-art methods.

Optimal Algorithms for Load Balancing in Optical Burst Switching Networks

Data packet drop can happen in Optical Burst-Switched(OBS)when two data bursts are competing on the same wavelength.Recently,many techniques have been developed to solve this problem but they do not consider the congestion.Also,it is necessary to balance the load system in the OBS network.The Ant Colony Optimization(ACO)technique can be applied to determine the straight and the safest route.However,the ACO technique raises both power utilization as well as the execution time.In this study,Cuckoo Search(CS)and ACO methods based approach is proposed to avoid the congestion and load balancing in the OBS network.This strategy evaluates the intensity of hotspot data and then launches the congestion rate optimization process that depends on their load situations.The congestion rate optimization represents the available bandwidth,data distribution rate,queue size,and access rate,and also these factors are optimized through the CS technique.The fitness utility in the CS technique adjusts the distribution rate in the OBS network,and the proposed ACO technique solves the energy utilization problem.The simulation results proved that the presented strategy evades both the end-to-end delay as well as the possibility of packet drop.

Optimal Control Strategy for Buck Converter Under Successive Load Current Change

A new control algorithm is presented for digitally controlled dc-dc converters to achieve a fast response under a successive load-change.Under the steady-state condition,the tight voltage regulation is processed by the conventional digital PID compensator.If the load disturbance is significant,the controller switches to an optimal control scheme.With the integration of the capacitor current,the proposed algorithm predicts the optimal switch over time based on the charge balance control,and the minimal voltage derivation and recovery time are thus achieved when the load current has a successive load-change.The method for calculating the optimal switch over time is described,and the implementation of the proposed algorithm with a digital controller is treated in detail.Furthermore,the simulation and experiment results are provided to validate the effectiveness of the approaches.

Balance control of grid currents for UPQC under unbalanced loads based on matching-ratio compensation algorithm

In three-phase four-wire systems, unbalanced loads can cause grid currents to be unbalanced, and this may cause the neutral point potential on the grid side to shift. The neutral point potential shift will worsen the control precision as well as the performance of the threephase four-wire unified power quality conditioner(UPQC),and it also leads to unbalanced three-phase output voltage,even causing damage to electric equipment. To deal with unbalanced loads, this paper proposes a matching-ratio compensation algorithm(MCA) for the fundamental active component of load currents, and by employing this MCA,balanced three-phase grid currents can be realized under 100% unbalanced loads. The steady-state fluctuation and the transient drop of the DC bus voltage can also be restrained. This paper establishes the mathematical model of the UPQC, analyzes the mechanism of the DC bus voltage fluctuations, and elaborates the interaction between unbalanced grid currents and DC bus voltage fluctuations;two control strategies of UPQC under three-phase stationary coordinate based on the MCA are given, and finally, the feasibility and effectiveness of the proposed control strategy are verified by experiment results.

Enabling Reachability Across Multiple Domains Without Controller Synchronization in SDN

Software-defined networking(SDN)makes network agile and flexible due to its programmable approach.An extensive network has multiple domains in SDN for the scalability and performance of the network.However,the inter-domain link is also crucial for the stability of the entire network on the data plane layer.More than one inter-domain connection enhances the scalability of the data plane layer.However,it faces a reachability problem with the principal root,which causes forwarding loops and packet drops in the network,thereby degrading network performance.The proposed solution is a multiple controller architecture;however,this approach increases the complexity and affects network performance.Thus,in this study,we propose a framework that avoids forwarding loops and packet drops without the synchronization of multiple-domain controllers in the network using an avoid loop with test packet scheme.Moreover,we collect the link status for improved routing and load balancing for the upcoming flow across inter-domain links to prevent congestion and increase throughput in real time.Our proposed methodology can significantly reduce the controller workload against multiple controller architecture,minimize flow setup latency,and improve throughput.

Metaheuristic Based Resource Scheduling Technique for Distributed Robotic Control Systems

The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently.The distributed robotic control system can be used in real time for resolving various challenges such as localization,motion controlling,mapping,route planning,etc.The distributed robotic control system can manage different kinds of heterogenous devices.Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements.For instance,scheduling of resources(such as communication channel,computation unit,robot chassis,or sensor input)to the various system components turns out to be an essential requirement for completing the tasks on time.Therefore,resource scheduling is necessary for ensuring effective execution.In this regard,this paper introduces a novel chaotic shell game optimization algorithm(CSGOA)for resource scheduling,known as the CSGOA-RS technique for the distributed robotic control system environment.The CSGOA technique is based on the integration of the chaotic maps concept to the SGO algorithm for enhancing the overall performance.The CSGOA-RS technique is designed for allocating the resources in such a way that the transfer time is minimized and the resource utilization is increased.The CSGOA-RS technique is applicable even for the unpredicted environment where the resources are to be allotted dynamically based on the early estimations.For validating the enhanced performance of the CSGOA-RS technique,a series of simulations have been carried out and the obtained results have been examined with respect to a selected set of measures.The resultant outcomes highlighted the promising performance of the CSGOA-RS technique over the other resource scheduling techniques.

生成式大模型承载网络架构与关键技术探索

生成式大模型训练需要超大规模低时延、高带宽、高可用的网络承载底座。对生成式大模型下高性能网络基础设施的技术发展路线和实现方案进行了研究,认为商用部署时需针对不同训练阶段的工作负载和流量模式,开展定制化网络架构设计和传输协议优化。流控/拥塞控制技术、负载均衡技术、自动化运维技术和面向广域远程直接内存访问(RDMA)的确定性网络传输技术是未来的重点研究方向。

基于云计算的舰船通信网络动态负载均衡控制方法

针对舰船通信网络通信环境复杂、用户需求不确定、影响通信均衡性等问题、提出基于云计算的舰船通信网络动态负载均衡控制方法。利用Ryu控制器获取监控舰船通信网络状态,获取网络负载。创建云计算平台虚拟机,实现执行舰船通信网络动态负载均衡任务调度任务。选取最高迁移概率的物理机结果作为云计算平台虚拟机迁移结果,通过虚拟机的迁移与关闭操作,更新虚拟机的综合权值,实现舰船通信网络动态负载均衡控制。实验结果表明,该方法可实现舰船通信网络的动态负载均衡控制,负载均衡度高于0.7,可有效提升舰船通信网络的资源利用率。

一种三相线电压级联单位功率因数整流器负载不均衡特性分析及电压均衡控制策略

该文对一种由三个三相单开关整流器线电压级联构成的三相单位功率因数整流器的负载不均衡特性和输出电压均衡控制策略进行分析和研究,首先详细阐述此类整流器在三个直流侧负载不均衡时,交流输入端电流能自动保持均衡的独特特性及相应工作机理;然后研究系统整体分层控制策略。在传统的基于电压外环PI控制、电流内环PR控制的上层控制基础上,针对各整流模块参数不一致及负载功率不一致引起的各模块输出电压不均衡问题,通过加入偏差因子调制波补偿的底层控制,实现了对每个模块输出功率的独立调节,进而实现了各整流模块输出电压的均衡控制。仿真和实验结果验证了所研究拓扑结构的优越性和控制策略的可行性。

多执行器载荷差异储能均衡系统特性

针对阀控多执行器复合作业系统节流损失大、动势能浪费严重等问题,提出一种多执行器载荷差异储能均衡原理。首先对多执行器系统功率分配特性进行分析,明确了载荷差异产生节流损失的原因是动力源压力与最大负载相匹配,导致其他执行器控制阀产生过大的压力损失。然后建立了载荷储能均衡液压挖掘机联合仿真模型。并设计电液储能单元控制各执行器进油腔的压力相等,从而消除执行器载荷差异造成的节流损失。在动臂、铲斗同时动作时,与流量匹配系统相比,所提系统节流损失降低达75%,系统效率提升39%;同时,电液储能单元实现了传统压力补偿器的压差调控功能,显著提升了系统运行平稳性。

基于OPC UA的分布式数据采集处理系统架构研究

随着物联网与互联网融合的不断深化,感知层与应用层之间的互联互通要求不断提高。针对现有数据采集系统存在的规范性、扩展性和适应性不足的问题,文章提出一套基于对象连接与嵌入过程控制统一架构(object linking and embedding for process control unified architecture,OPC UA)协议的分布式数据采集处理系统架构。对数据采集处理系统各个模块进行功能解耦和架构重组,分别介绍该系统硬件和软件架构;针对发布订阅模式下负载的特异性,提出一种改进的适用于OPC UA分布式订阅的负载均衡算法;最后在某车企实例验证该系统架构。结果表明,基于OPC UA的分布式数据采集处理系统数据采集处理效果良好,证明了该系统架构的可行性及有效性。

引入负载扰动观测的Boost变换器定频滑模控制

针对传统线性控制方法下Boost变换器存在系统动态性能差和对负载扰动鲁棒性不强的问题,从功率平衡的角度提出1种定频滑模电流控制方法。首先,利用负载电流观测值计算维持输出电压稳定所需的输入功率;其次,通过控制电感电流调整变换器输入功率,从而将系统的状态轨迹限制在对负载扰动具有不变性的滑模面上,保证系统大信号稳定并提升其动态性能;最后,基于等效控制原理,通过PWM技术实现等效滑模控制,避免了传统滑模控制中存在的抖振及开关频率不稳定问题。在Simulink中对Boost变换器负载阶跃变换的工况进行仿真,将所提方法与传统线性控制方法对比。结果表明,采用所提方法,系统的动态性能更好,且能保证系统在负载大范围扰动下的大信号稳定。

Vienna整流器低开关频率双矢量模型预测控制策略研究

为了解决Vienna整流器传统有限集模型预测控制计算量大、控制精度依赖于采样频率的问题,同时降低Vienna整流器的开关频率,提出一种应用于Vienna整流器的低开关频率双矢量有限集模型预测控制策略。首先,建立基于电压预测的代价函数,并在进行预测计算之前确定参考电压矢量所在的扇区以减少参与预测计算的矢量个数。其次,在控制周期中引入第二矢量与最优矢量共同作用,以提高控制系统的跟踪精度,减小传统有限集模型预测控制对采样频率的依赖。再者,为了减小系统的开关损耗,对输出的双矢量组合进行限定并对矢量的作用顺序进行调整。此外,利用冗余矢量对中点电压的相反影响解决直流侧中点电压的波动问题。最后,通过仿真和实验证明所提控制策略的有效性和可行性。