Improve the efficiency of Internet of Things (IoT) routing with the goal of better data transmission using the Cheetah optimization algorithm

The Internet of Things (IoT) is a network of various. objects such as vehicles, buildings, devices, and appliances that are connected to the internet and interact with each other and their users. One of the key challenges in these networks is the routing problem, which aims to find suitable paths for transmitting data from nodes to the desired destinations. Traditional routing methods are not effective for large-scale IoT networks due to their high energy consumption, lack of consideration for sensor node constraints, and the impact of different paths on each other. In this thesis, a solution is proposed. using the meta-heuristic algorithm called Cheetah. This solution iteratively finds paths from different nodes to the destination node, taking into account their impact on other node paths. To optimize energy consumption, the proposed solution is centralized and implemented at the base station. The results of comparing the proposed solution with an existing approach demonstrate that the proposed solution has successfully reduced the average energy consumption of nodes and increased the network's lifespan.

Keywords:

Internet of Things , routing: data transmission: Cheetah optimization algorithm