Hybrid Optimization Model for Congestion-Free Multipath Routing and Load Balancing in IoT

The internet of things (IoT) has become popular as a means of connecting people and things in order to gather and share data through embedded sensors. Consequently, robust multipath routing techniques are required to guarantee network lifetime and enhance energy efficiency. The main challenge to secure the network longevity of IoT networks is the load balancing issue in a priority-based, congested-free communication infrastructure. This research intends to propose multipath routing and load balancing in IoT. The steps carried out in the research are: (i) multipath routing, and (ii) traffic scheduling. In multipath routing, the route will be estimated via an optimization algorithm, termed a hybrid dwarf mongoose-insisted pelican optimization algorithm (HDMPOA) model which is the combination of pelican optimization algorithm (POA) and dwarf mongoose optimization (DMO). The routing will be done by considering parameters such as message priority (improved computation) and congestion control (improved computation). Further, the traffic scheduling process will be carried out via a hybrid HDMPOA model under the consideration of balanced energy consumption and collision rate. Finally, the proposed suggested work is evaluated over various methods using a range of metrics, such as message priority, collision rate, congestion control, latency, distance, throughput, and so on. The collision rate of HDMPOA scheme-based multipath routing in IoT for numbers of round 20,000 is approximately 5.2, which is minimal when compared to existing techniques. The HDMPOA scheme yielded a higher congestion control of 1.85 at round 1500 (Node = 100) while conventional methods achieved minimal rates.