Implementation of Optimal Pacing Scheme in Xinjiang's Oil and Gas Pipeline Leak Monitoring Network

Abstract

Flow against Xingjian’s oil and gas pipeline leakage and the pipe network sudden burst pipe to pipeline leakage flow for the application objects, Optimal pacing scheme is designed in pipeline leak monitoring. Based on the property of Markov chain for network data, a new estimator with particle filter is proposed for congestion control in this paper. In the context of a reconfigurable transport protocol framework, we propose a QoS aware Transport Protocol ( QSTP ), specifically designed to operate over QoS (Quality of Service) enabled networks with bandwidth guarantee. The proposed scheme can adaptively adjust the network rate in real -time, so that it can efficiently avoid the traffic congestion. It proposes a Link Layer Adaptive Pacing ( LLAP ) scheme that adaptively controls the offered load into the network. The algorithms actively probe the underlay network and compute virtual multicast trees by dynamically selecting the least loaded available paths on the overlay network. The low computational complexity of the proposed algorithms leads to time and resource saving, as shown through extensive experiments. The Simulation results show that Network congestion avoidance strategy with optimal pacing scheme can efficiently improve the bandwidth utilization, Transmission Control Protocol ( TCP ) friendliness and reduce the packet drop rate in Pipeline Flux Leak Monitoring networks. Flood flow identified by the National Centre for testing: discussion group first proposed the use of particle filters to solve the new model can estimate the network congestion control problem. The results are sound, stable performance, efficiency 29%. Adaptive algorithm using the model proposed optimization scheme, to achieve accurate positioning of the leak, 0.05 % measurement accuracy, positioning accuracy is improved 32%, more than 17% of the nodes in a more reliable routing path, reliable routing path of increase of 40%.