An Efficient Stochastic Gradient Diffusion Search For Wsn Using Parallel Computing Technique
Main Article Content
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
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.