Compressive sensing with perceptron based routing for varying traffic intensity based on capsule networks. (October 2019) - Alagirisamy, Mukil; Chow, Chee-Onn; Noordin, Kamarul Ariffin Bin
Abstract: Compressive sensing with data acquisition at wireless sensor nodes has overcome the rigid sampling procedure to acquire sensor data. Transfer of network data efficiently is considerably reduced in congested links within the topology of sensor nodes. Hence, in this research, optimization is provided using compressive sensing with a discrete wavelet transform (DWT) for data acquisition, and data are transferred through perceptron-based forwarding. Two protocols are proposed, namely: Perceptron-based Optimal Routing (POR) and Perceptron-based Routing with Moderate Traffic Intensity (PRMTI). POR uses a bipolar logic with a target value at the relay node for forwarding. If the target response is not satisfactory, then weight update is performed iteratively, until the incoming data meets the target response. PRMTI forwards when the link capacity exceeds the defined data-forwarding threshold at the relay node. Simulation validation has been performed for both protocols.