Quality of Service Aware Reliable Resource Allocation with Energy Efficient Comprehensive Learning Strategy for Smart Internet Communication

Quality of Service (QoS) Aware Reliable Resource Allocation efficiently manages network resources for specific service demands. To overcome this, the QoS-aware Reliable Resource and Energy-efficient Comprehensive System (QRRECS) system is an integrated framework of the Internet of Things (IoT), fog, and cloud computing that aims at resource efficiency, energy savings, and reliable data transmission. It makes use of a three-tier architecture comprising IoT devices that collect commands to start local processing at fog nodes, through a Decentralized Decision System (DDS). Cloud acts as a central data storage for heavy post-processing. The Energy Efficient Comprehensive Learning Strategy (EECLS) extends learning capacity and intentionally keeps a premature convergence from happening by enabling learning rates to be adaptively evaluated. The system tracks QoS parameters like latency and reliability to facilitate smooth communication in the entire network. The evaluation parameter is used to calculate network lifetime, alive sensors, dead sensors, energy consumption, and compare through calculations.