Abstract
Conference Title: 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Conference Start Date: 2018, Aug. 20 Conference End Date: 2018, Aug. 24 Conference Location: Munich, Germany In a cloud computing environment, cloud service providers offer cloud services to users. How to achieve reasonable and efficient service resource allocation to meet a user's demands is an important problem. Considering a multi-user and multi-provider environment, we propose a service resource allocation framework to optimize an objective function of load and completion time. We design an improved differential evolution algorithm for optimal resource allocation given a batch of multiple tasks. Experimental results show that proposed method can better balance loads among computing resources while achieving better optimized results for the entire system than some existing methods.