A QoS-driven Service Selection Optimization Algorithm for Internet of Things

Abstract Currently, the smart devices have been widely deployed in Internet of Things (IoT). With the scale of IoT continues to increase, it brings big challenges for service composition in a large-scale IoT. For solving this problem, a QoS-driven service selection method based on the enhanced Genetic algorithm (EGS ~ QoS) is proposed in this paper. To decrease the scale of service composition, we use the lexicographic optimization approach and QoS constraint relaxation technique to find the candidate service with height QoS. Then, the IoT service composition problem is transformed into a single-objective optimization problem adopting a simple weighting method, and the final composite service meeting the user's QoS needs is found from the candidate service. Compared with the related algorithm, the simulation results show that EGS ~ QoS can efficiently and quickly select a composite service satisfying user's QoS needs, and is more suitable for solving the service composite problem in large-scale IoT services.