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Wireless sensor networks (WSN) mainly comprise of small sensor nodes which have limited resources. Base stations in WSN connect these sensor nodes with the rest of the world. The base stations are responsible for handling large amount of data and must have built in computational abilities capable of dealing with those data. Network processors (NP) are intended to replace conventional processors in the base station and they can bring the new levels of performances in information processing. This paper discusses the design of co-processor which could assist the packet classification for NPs. In this work we use neural network to classify the packets based on nature of the data to overcome the traffic in WSN. The classification is done using conventional feed-forward back propagation network (BPN), to give optimum result.