Business optimization of quantitative analytics for trade-off between cost and system availability in cloud logistics

Abstract Cost item is one of the main issues that will drive the design of logistics on cloud computing (CC), especially of those devoted to provide services in a long-term and steady manner. The high availability of cloud platform has emerged to an essential requirement for CC business. To keep the service level agreement committed to cloud customers, the CC platform should adopt necessary cloud logistic approach to backup breakdown servers. Aiming at searching for a feasible architecture with optimal running cost, two control parameters of standbys and repairmen in the cloud logistics has been considered to maintain regulated service quality for the cloud enterprise. Based on the queuing theory, quantitative exploration with MRP (Machine Repair Problem) model has been adopted and conducted for optimal methodology. The proposed cloud logistic framework has been designed in systematic profile. Comprehensive mathematical materials have been elaborated in details between cost pattern and system availability. Relevant numerical experiments have been conducted to verify the feasibility for trade-off between cost and availability as well. On engineering application, the proposed approach indeed provides a feasibly cost-effective decision-making support to adapt cloud-based logistics.