Efficient Trajectory Error Detection: Router Group Monitoring with Adaptive Interface Selection Strategy

In networking setting police investigation packet forwarding errors is very important to operational networks. Many completely different traffic mechanical phenomenon watching techniques like mechanical phenomenon Sampling, PSAMP, and fatih are often used for traffic mechanical phenomenon error detection. However, direct application of those algorithms can incur the overhead at the same time watching all network interfaces during a network for the packets of interest. In this paper, we have a tendency to propose a completely unique technique known as adaptative router cluster observance with irregular router interface choice strategy to boost the potency of mechanical phenomenon error detection by solely observance the exiting interfaces of routers. Router cluster interface choice strategy to be applied to pick exiting interfaces among elect router teams. Our projected Router interface choice formula and router cluster observance that monitors totally different set of packets throughout different observance amount. Our proposed design will monitor during each traffic (Period by period) to cover all the traffic. In order to reduce the monitoring overhead, exiting interfaces of traffic trajectory routers are to be monitored. In real time, the proper FEC scheme to be implemented to provide the best performance to the application. We evaluate the performance of parity-based FEC schemes using an analytical loss model. Finally, we show that the router group monitoring technique can significantly enhance the efficiency of trajectory error detection based on Trajectory Sampling or Fatih