{"title":"基于状态感知的动态控制模型","authors":"Anying Chai, Yue Ma, Zhenyu Yin, Mingshi Li, Zhihao Zhao","doi":"10.1109/ICCC47050.2019.9064363","DOIUrl":null,"url":null,"abstract":"The monitoring system built on the OPC UA (object linking and embedding (OLE) for process control unified architecture) protocol cannot detect the congestion of each terminal network and the load pressure of the cluster server nodes in real time. In the case that the number of terminal accesses is increasing and the traffic volume is gradually increasing, some server nodes of the system are overloaded or crash. In response to these questions, this paper presents a dynamic control model based on state perception. This model can perceive the communication state of client and server in real time, and uses the current resource occupancy index of the server and the network congestion indicators of each client as the adjustment conditions. The model algorithm can dynamically adjust the client served by the overload node to the server node with small load. Meanwhile, the model uses the congestion estimation method based on bandwidth estimation to accurately estimate the network conditions of each client and improve the validity of state-aware information. The simulation results show that the model can sense the load of each server and make reasonable adjustments to achieve a good load balancing effect. At the same time, the experiment verifies the feasibility and efficiency of the model.","PeriodicalId":6739,"journal":{"name":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","volume":"6 1","pages":"1406-1411"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Dynamic Control Model Based on State Perception\",\"authors\":\"Anying Chai, Yue Ma, Zhenyu Yin, Mingshi Li, Zhihao Zhao\",\"doi\":\"10.1109/ICCC47050.2019.9064363\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The monitoring system built on the OPC UA (object linking and embedding (OLE) for process control unified architecture) protocol cannot detect the congestion of each terminal network and the load pressure of the cluster server nodes in real time. In the case that the number of terminal accesses is increasing and the traffic volume is gradually increasing, some server nodes of the system are overloaded or crash. In response to these questions, this paper presents a dynamic control model based on state perception. This model can perceive the communication state of client and server in real time, and uses the current resource occupancy index of the server and the network congestion indicators of each client as the adjustment conditions. The model algorithm can dynamically adjust the client served by the overload node to the server node with small load. Meanwhile, the model uses the congestion estimation method based on bandwidth estimation to accurately estimate the network conditions of each client and improve the validity of state-aware information. The simulation results show that the model can sense the load of each server and make reasonable adjustments to achieve a good load balancing effect. At the same time, the experiment verifies the feasibility and efficiency of the model.\",\"PeriodicalId\":6739,\"journal\":{\"name\":\"2019 IEEE 5th International Conference on Computer and Communications (ICCC)\",\"volume\":\"6 1\",\"pages\":\"1406-1411\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 5th International Conference on Computer and Communications (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCC47050.2019.9064363\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 5th International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCC47050.2019.9064363","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
基于OPC UA (object linking and embedding, OLE)协议的监控系统无法实时检测各终端网络的拥塞情况和集群服务器节点的负载压力。在终端接入数量不断增加,流量逐渐增大的情况下,系统的部分服务器节点会出现过载或崩溃的情况。针对这些问题,本文提出了一种基于状态感知的动态控制模型。该模型可以实时感知客户端和服务器的通信状态,并以服务器当前的资源占用指标和各客户端的网络拥塞指标作为调整条件。该模型算法可以将过载节点所服务的客户端动态调整为负载较小的服务器节点。同时,该模型采用基于带宽估计的拥塞估计方法,准确估计各客户端的网络状况,提高状态感知信息的有效性。仿真结果表明,该模型能够感知各服务器的负载,并进行合理调整,达到良好的负载均衡效果。同时,通过实验验证了该模型的可行性和有效性。
The monitoring system built on the OPC UA (object linking and embedding (OLE) for process control unified architecture) protocol cannot detect the congestion of each terminal network and the load pressure of the cluster server nodes in real time. In the case that the number of terminal accesses is increasing and the traffic volume is gradually increasing, some server nodes of the system are overloaded or crash. In response to these questions, this paper presents a dynamic control model based on state perception. This model can perceive the communication state of client and server in real time, and uses the current resource occupancy index of the server and the network congestion indicators of each client as the adjustment conditions. The model algorithm can dynamically adjust the client served by the overload node to the server node with small load. Meanwhile, the model uses the congestion estimation method based on bandwidth estimation to accurately estimate the network conditions of each client and improve the validity of state-aware information. The simulation results show that the model can sense the load of each server and make reasonable adjustments to achieve a good load balancing effect. At the same time, the experiment verifies the feasibility and efficiency of the model.