In the Cloud Computing model, the computing resources are provided in an on-demand and dynamic fashion. For improving system reliability and availability on server farm, the concept of redundancy is adopted to allow the system to continue operation even when some servers fail. The selection on the amount of standby servers emerges to be an issue to explore. The goal of this research is to provide an effective decision support for cloud logistics to get around the selection on spares quantities in a haphazard way. The kernel point of the proposed approach is that a novel design pattern is developed for approaching optimal profit on logistics using the finite-source queuing theory. To formulate the proposed approach, the mathematical analysis on profit pattern has been made quantitatively in detail. Relevant simulations have also been conducted to validate the proposed optimization model. The design illustration is presented to demonstrate engineering application scenario in cloud environment, hence the proposed approach indeed provides a feasibly profit-oriented framework to meet logistic economy.
['Fuu-Cheng Jiang', 'Chao-Tung Yang', 'Yung-Hsin Chen', 'Wei-Tao Huang', 'Hsin-Yu Chao']
Decision Support for Cloud Logistics by Optimizing the Quantities of Standby Servers in Cloud Environment