Performance Analysis of a Quality of Service-Aware Resource Allocation for Internet of Things

Nowadays, IoT (or the Internet of Things) touches nearly every aspect of our everyday lives. There is a considerable likelihood of encountering difficulties while sharing network resources effectively as IoT is applied to both huge connection sensors and vital functions like emergency-monitoring health care systems. The urgent need for effective approaches to overcome limits associated with resource management across different IoT applications is a key factor in the solution to the resource allocation challenge. Therefore, for practical applications, crucial IoT services need a systematic transformation and a fast response time, both of which boost system efficiency and further protect the large traffic transmission. In this work, we suggest an efficient means of allocating resources in order to raise QoS standards for challenges involving the Internet of Things (IoT) and its associated infrastructure. The goal of the proposed approach is to categorise IoT traffic into two groups: critical IoT traffic (CIoT) and massive IoT traffic (MIoT). In addition, a powerful technique of allocating resources is put in place to transmit essential IoT services in a way that guarantees high resource utilisation and keeps the minimum QoS necessary for MIoT. Using a 3D Markov series and a matrix analysis technique, an analytical model is created to assess the efficacy of the suggested system. The results demonstrate a substantial enhancement in the transmission of MIoT traffic with no detriment to CIoT performance. The results of these experiments also demonstrate a notable increase in MIoT throughput and a marked decrease in its loss probability.