Anomaly detection using forecasting methods ARIMA and HWDS
Rs3,500.00
10000 in stock
SupportDescription
It is important to ensure network capacity utilization and improved delay and loss performance in software defined network. Software Defined Networking (SDN) is a new networking paradigm that separates the control and forwarding planes in a network. Traffic engineering aims to distribute traffic so as to “optimize” some performance criterion. This optimal distribution of traffic depends on both the routing protocol and the forwarding mechanisms in use in the network. Our proposed GEAR protocol first is that these protocols use shortest path routing with destination based forwarding. The second is that when the protocols generate multiple equal cost paths or next hops for a given destination routing prefix, the forwarding mechanism equally splits the corresponding traffic across them to balance the load. A significant problem related to network management is anomalies detection. We also proposed a method called ARIMA (Auto Regressive Integrated moving Average) which is providing the forecasting error and the information about the nodes. Our simulation result shows, our proposed GEAR and ARIMA provides better energy consumption, tolerate delay and traffic and achieve 40% better transmission.
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