A Novel Load Balancing Method for Internet of Things Systems Based on Particle Swarm Optimization Algorithm in Cloud Computing

The internet of things and cloud systems can effectively integrate into the management of monitoring systems in different small and large environments. The internet of things typically has sensing, processing, and networking resources that are limited in this type of processing. Hence, computational tasks are properly requested from cloud systems, where more logical and comprehensive decisions can be made. Cloud processing systems allow for analysis and processing of a huge amount of information coming from different sources in a widespread network and this is done to control the intelligent objects. In this paper, a new method for optimizing the monitoring system for places, based on internet of things in cloud computing environment, is presented using the particle swarm optimization algorithm. In the proposed method, the goal is to provide load balancing and focus on issues related to the monitoring system of places and cloud space. The proposed method is implemented using MATLAB software; the implementation results indicate that there is a significant improvement in the mean runtime and logical load balances in the system.

Keywords:

Internet of things , cloud computing , load balancing , particle swarm optimization algorithm.