Cost-based hierarchy genetic algorithm for service scheduling in robot cloud platform

Abstract

Abstract Service robot cloud platform is effective method to improve the intelligence of robots. An efficient cloud service scheduling algorithm is the basis of ensuring service quality and platform concurrency. In this paper, Hierarchy Genetic Algorithm of robot service(RHGA) is presented to solve the scheduling problem with the crucial constraints. Firstly, the limitations and attributes of the cloud service robots and cloud services are presented and boiled down to an important optimization goal. Secondly, three factors (i.e. evolutionary factor, hunting factor and parent similarity) are integrated with RHGA to promote the efficiency of small-scale service invocations and improve the performance of large-scale service invocations on the platform. Finally, a series of experiments are conducted on several service scheduling algorithms, including four traditional efficient algorithms and two state-of-art algorithms. The experimental results demonstrate that the RHGA can enhance the performance on small-scale service scheduling and ensure its excellent ability in large-scale service scheduling. Moreover, the empirical studies also prove that our proposal has a better performance in service scheduling completion time and cost-savings with comparison to other methods.