Fog computational-based deep learning model for optimization of micro grid connected WSN with load balancing
Dr. Bharat Batham
Assistant professor Computer science & Application department Atal Bihari Vajpayee Hindi Vishwavidyalaya, Bhopal
Keywords: Cloud Computing; Fog Computing; Load Balancing; Smart Grid; WSNs.
ABSTRACT
IoT applications for the smart environments have proliferated with the introduction of the Cloud Computing. However, delay-sensitive programmes can’t use these resources because of how far apart they are. Fog computing has arisen to give such capabilities in close proximity to end devices via dispersed resources, and it plays a crucial role in optimizing the connection between load balancing, microgrids, and WSNs. Using the idea of the “stateless micro-Fog service replicas”, these constrained resources may work together to support dispersed IoT application operations, ensuring service availability even in the face of failures. Through load balancing, workloads are distributed between Fog nodes in an equitable manner, maximizing the use of computation and network resources while reducing lag time for application execution.
Journal Details
ISSN : 2583 – 7117


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