Heuristic Load-Balancing Optimization Model For Cognitive Radio Networks Using Iot

Abstract

The Internet of Things (IoT), via different communication models, connects network resources through the Internet. A main IoT technology is the cognitive radio network, which can resolve spectrum problems in IoT applications effectively. A novel approach is proposed in our paper for IoT sensor networks to achieve the channel status in typical Cognitive-IoT model produces more spectrum holes which it leads a Quality-of-Service issue due to the channel allocation and spectrum allocation errors. To minimize the error rate, we proposed a Heuristic Load-balancing optimization model (HLBO) for OFDM-based Cognitive radio network model. Proposed model categorizes channel scheduling process by considering resource allocation and load. The proposed HLBO employs a load optimization algorithm to enhance channel status, based on different traffic states the load optimization model predict the spectrum allocation rate based on the channel and sub-channel status.