An Efficient Stochastic Gradient Diffusion Search For Wsn Using Parallel Computing Technique
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Abstract
The past few years have witnessed increased interest within the potential use of wireless sensor networks (WSNs) during a wide selection of applications and it's become a hot research area. Based on network structure, routing protocols in WSNs are often divided into two categories: Flat routing and hierarchical or clustering routing. Owing to aspread of benefits, clustering is becoming alively branch of routing technology in WSNs. Since WSN protocols are application specific, the focus has been given to the routing protocols that might differ depending on the application and network architecture. In this paper, we addressed an efficient optimize technique using deep learning model i.e. Stochastic Gradient Diffusion (SGD). We compared with few exiting algorithms for betterment of our own result
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