Cloud manufacturing service composition based on QoS with geo-perspective transportation using an improved Artificial Bee Colony optimisation algorithm

TLDR: In this paper, the authors proposed a method based on QoS evaluation along with the geo-perspective correlation from one cloud service to another for transportation impact analysis, and also insure the veracity of the manufacturing time evaluation by resource availability overtime.

Abstract: Cloud Manufacturing (CMfg) ambitions to create dedicated manufacturing clouds (ie virtual enterprises) for complex manufacturing demands through the association of various service providers’ resources and capabilities In order to insure a dedicated manufacturing cloud to match the level of customer’s requirements, the cloud service selection and composition appear to be a decisive process This study takes common aspects of cloud services into consideration such as quality of service (QoS) parameters but extend the scope to the physical location of the manufacturing resources Unlike the classic service composition, manufacturing brings additional constraints Consequently, we propose a method based on QoS evaluation along with the geo-perspective correlation from one cloud service to another for transportation impact analysis We also insure the veracity of the manufacturing time evaluation by resource availability overtime Since the composition is an exhaustive process in terms of computational time