Research on Service Controlling Algorithm of Electric Power Communication Network based on QoS Traffic Recognition and Routing Optimization

With rapid progress in power communication networking, the present power communication network has become an integrated transmission network that supports various services (e.g., control data, service data, voices, and images). Compared with traditional network services, real-time services in the present power communication network have stricter requirements on delays, delay jitters, and packet losses. QoS techniques can guarantee the network service qualities overall, provide different QoS for different power communication network services, and improve network resource utilization, as well as satisfying the requirements of key services (e.g., relay protection and power dispatching). After analyzing the problems and challenges facing the QoS routing of the present power communication network, a QoS routing module is proposed under the service classification system. The most prominent feature of the proposed model is its ability to match different network services with suitable QoS. Our model consists of the service recognition and classification module, the routing module, and the client service analysis module. In the system tests, the proposed method for classifying power communication network services is used to implement the routing model under the service classification system. At the client end, the service types of the data are statistically analyzed, and service type maps are plotted. The statistical analysis shows that the proposed model has excellent QoS performance

[1]  P. L. So,et al.  Modeling and Analysis of Common-Mode Current Propagation in Broadband Power-Line Communication Networks , 2008, IEEE Transactions on Power Delivery.

[2]  Feng Li-na Risk evaluation of electric power communication network based on tolerant rough-fuzzy set , 2010 .

[3]  Ma Rui Reliability of power telecom network based on the efficient energy model , 2012 .

[4]  Hui-Sheng Gao,et al.  Application of vulnerability analysis in electric power communication network , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[5]  Yang Sheng A Model for Web Service Discovery with QoS Constraints , 2005 .

[6]  Zou Ling A QoS based distributed multicast routing algorithm in Ad Hoc networks , 2003 .

[7]  Gao Yan QoS for Composite Web Services and Optimizing , 2006 .

[8]  Wang Yuan Research on QoS in Next Generation Network , 2008 .

[9]  Giuseppe Bianchi,et al.  A Survey of Medium Access Mechanisms for Providing QoS in Ad-Hoc Networks , 2013, IEEE Communications Surveys & Tutorials.

[10]  Zhang Wei A Trust-QoS Enhanced Grid Service Scheduling , 2006 .

[11]  Yang Bin Energy-balanced QoS routing algorithms for WMSNs , 2014 .

[12]  Ma Hua-dong The QoS Guarantee Problem for Wireless Multimedia Sensor Networks , 2008 .

[13]  Wang Jian-pin QoS-MAC Model of Wireless Sensor Networks for Smart Distribution Power Grid Data Communication , 2014 .

[14]  Y. Serizawa,et al.  Simulation study of QoS guaranteed ATM transmission for future power system communication , 1999 .

[15]  Zhigang Cao,et al.  Quality of Service Routing: Problems and Solutions , 2003 .

[16]  Lutz H.-J. Lampe,et al.  Power line communication networks for large-scale control and automation systems , 2010, IEEE Communications Magazine.