The SDN balancing controller based on load announcement is prone to overload when it carries out network communication control, which results in low efficiency and poor stability of network communication transmission. Design and implement a new network communication equalization controller, which includes application layer, control layer and infrastructure layer. The dynamic updating and equalization module in the controller module collects flow group and interface flow, completes channel allocation and equalization strategy according to flow group information; the pre-processing module adjusts the order of information transmission, and the equalization shunt module processes routers to implement equalization management of flow in network communication. The software of the controller is designed by using the PID algorithm, and the problem of excessive load of the controller is solved by the switch selection program. The experimental results show that the network communication under the designed controller has the advantages of high transmission efficiency and strong stability.Network communication; Balancing controller; Channel allocation; Balancing strategy; Balancing shunt; PID algorithm; LoadChinese Library Classification Number: TN715? 34 Document Identification Number: A Article Number: 1004? 373X (2018) 16? 0072?04Abstract: The problem of overloading of the controller is prone to occur when the SDN equalization controller based on on load notification is used for network communication control, resulting in low transmission efficiency and poor stability of network communication. The dynamic update and balance module in the functional modules of the controller collects flow groups and interface traffic, and accomplishes the channel The preprocessing module is used to adjust the sequence of information transmission. The balanced shunting module processes the router and implements balanced management of shunts in network communications. The PID algorithm is u.
Sed to design the software of the controller. The switcher selection program is used to resolve the problem of overloading of the controller. The experimental results show that the network communication control by the design controller has the advantages of high transmission efficiency and str Ong stability.Keywords: network communication; equilibrium controller; channel allocation; balance strategy; balanced shunting; PID algorithm; loadBecause there are a lot of protocols running in the network communication system and mass information transmission [1], the balanced control of network communication is very important to improve the quality of network operation [2].
Traditional SDN balancing controller based on load announcement makes use of the ability of load announcement to complete the balancing decision as soon as possible in the process of network communication control, but it is prone to the problem of excessive load of the controller, resulting in low efficiency and poor stability of network communication transmission [3]. Therefore, this paper designs and implements a new network communication equalization controller, which can effectively equalize the network communication channel allocation, improve the network communication transmission efficiency and reduce transmission errors.Design and Implementation of Balance Controller in Network CommunicationController Overall Architecture DesignAccording to the hierarchical architecture, the balancing controller in network communication designed in this paper is divided into three parts: application layer, control layer and infrastructure layer. The overall architecture of the balancing controller is shown in Figure 1. The controller realizes the communication between the control layer and the application layer and the diffusion activity between the control layer and the infrastructure layer through the north-facing interface and the south-facing interface respectively.The application layer includes OpenStack channel resource scheduling platform. The platform uses the northward interface in the control layer to dominate the switches in the infrastructure layer, and achieves the overall control of channel resource balanced allocation in all network communications [4].The control layer contains the key module of the network communication controller (controller). The controller uses the southward interface to control the process of data flow table generation, resource allocation scheme planning and information storage of the switch, and uses the northward interface to equalize channel resources allocation to users in the application layer channel resource scheduling platform to equalize channel resources allocation in network communication.Infrastructure layer includes balanced controller switches, which implement channel resource combination and matching based on the flow chart standard reflected by the controller, and control resource diffusion activities.Design and Preprocessing Module of Controller Function ModuleAs network communication users may have more special problems, the quality of network communication channel equalization is greatly reduced. Therefore, it is necessary to pre-process channel allocation, adjust the order of information transmission in the process of pre-processing, give priority to effective information transmission, delay or delete invalid information, and then implement channel equalization allocation [6].Design of Equilibrium Shunt Module) The initial parameters of the router are set.
Users analyze the parameters of the router interface address and mask. The router traffic is regulated by the dynamic Hash algorithm balanced shunting scheme.) Based on the setting documents of routers, users set the association rules among different routers, and use dynamic Hash algorithm to balance the router traffic.) Equilibrium shunt module collects router status and data information in network communication based on user setting time cycle.) The balanced shunt module uses dynamic Hash algorithm to calculate and manage the traffic information of router interface, so as to ensure that the traffic meets the application specifications of different network communication users [7].Logic Design of Controller OperationThe operation logic of the equalization controller in network communication based on OpenFlow protocol is shown in Figure 2.Controller Software DesignSoftware Design Using PID AlgorithmsUsing the PID algorithm in A/D converter to design the whole software of the equalization controller in this paper, the following parameters need to be set first:The PID control algorithm obtains the data information of OpenStack channel resource scheduling platform in the controller through the NFC chip in the converter, and processes and transforms the data information under the MCGS configuration environment in the converter. OpenStack Channel Resource Scheduling Platform executes the command from OTP chip in the converter to connect 128 control points at the same time, realizes the control of the equalization controller in network communication [8], and finally realizes the software design of the equalization controller in the overall network communication.Design of Switch Selection ProgramThe switches controlled by the controller are sorted according to the information arrival rate.
In the formula, [Thrtar], [Ltar], [Lmig] respectively represent the threshold value of the controller, thermostatic element the load value of the controller and the load transferred to the controller. Formula (3) realizes that the migrated load is lower than the difference between the controller load threshold and the load [1a], so as to solve the problem of excessive load of the controller.2. Experimental analysisIn the experiment, the equalization controller in the network communication designed in this paper, the equalization controller based on reliability evaluation and the equalization controller based on rotation method are selected to carry out a series of performance-related experimental analysis. In order to verify the performance advantages of network communication under this controller, the throughput of a logistics company network channel under three controllers is compared, and the comparison results are shown in Figure 3.Analysis of Figure 3 shows that the throughput of experimental logistics network communication channel increases with the increase of average signal-to-noise ratio under the three controllers.
When the average signal-to-noise ratio is high, the throughput of the logistics network channel under the controller is much higher than that of the other two controllers, which shows that the controller can effectively control the network communication and improve the network communication performance. In order to verify the channel average fairness advantage of network communication under this controller, the channel average fairness index of network communication under three controllers is obtained and compared, as shown in Figure 4.Analysis of Figure 4 shows that when the average signal-to-noise ratio is 0 dB, the average fairness index of the logistics network under this controller is about 0.06 higher than that under the rotation-based controller; when the average signal-to-noise ratio is 30 dB, the average fairness index of the logistics network under this controller is about 0.0 higher than that under the reliability-based evaluation controller.
14. It shows that the fairness of the logistics network under the controller is higher than that of other logistics networks.
In order to verify the stability of the experimental logistics network communication under the controller, the average channel interruption probability of the logistics network under three controllers is compared. Fig. 5 is the result of the comparison.From Fig. 5, we can see that under the condition that the average signal-to-noise ratio of the channel is less than 15 dB, the average outage probability of the logistics network communication under the controller in this paper is smaller than that under the other two controllers; under the condition that the average signal-to-noise ratio of the channel is greater than 15 dB, the outage probability of the network communication under the three controllers follows the channel. The average signal-to-noise ratio increases with the increase of the average signal-to-noise ratio, but the average outage probability growth curve of the network communication under this controller is relatively flat, and is significantly lower than that under the other two controllers, which shows that the network communication under this controller has better stability.
In order to verify the delay of network communication under the controller, 100 experiments were carried out using the experimental network communication under three controllers, and the transmission delay of network communication under different controllers was recorded and compared.Table 1 shows the comparison results of transmission delay of logistics network communication under different controllers. The analysis shows that the transmission delay fluctuation of the logistics network communication under the controller is small and far lower than that under the other two controllers, which shows that the transmission delay of the logistics network communication under the controller is low.The error test of logistics network communication under three controllers is carried out, and the results are shown in Table 2.The analysis table 2 shows that the average error of logistics network communication under the controller is smaller than that under the other two controllers. It proves that the accuracy of logistics network communication under the controller is higher and the channel equilibrium can be accurately allocated in network communication.3 ConclusionThis paper designs and implements a new balancing controller in network communication, which solves the shortcomings of low efficiency and poor stability when using SDN balancing controller based on load notification in network communication control. The controller can ensure the normal work of network communication and improve the equalization of channel resource allocation in network communication. It has a positive effect on improving the performance of network communication system. It can be widely used in many fields such as communication, medical treatment, aviation and so on.