Abstract As cloud computing becomes widely deployed, more and more cloud services are 8 offered to end users in a pay-as-you-go manner. Today's increasing number of end user-oriented 9 cloud services are generally operated by SaaS (Software as a Service) providers using rental 10 virtual resources from third-party infrastructure vendors. As far as SaaS providers are concerned, 11 how to process the dynamic user service requests more cost-effectively without any SLA violation 12 is an intractable problem. To deal with this challenge, we first establish a cloud service request 13 model with SLA constraints, and then present a cost-aware service request scheduling approach 14 based on genetic algorithm. According to the personalized features of user requests and the current 15 system load, our approach can not only lease and reuse virtual resources on demand to achieve 16 optimal scheduling of dynamic cloud service requests in reasonable time, but also can minimize 17 the rental cost of the overall infrastructure for maximizing SaaS providers' profits while meeting 18 SLA constraints. The comparison of simulation experiments indicates that our proposed approach 19 outperforms other revenue-aware algorithms in terms of virtual resource utilization, rate of return 20 on investment and operation profit, and provides a cost-effective solution for service request 21 scheduling in cloud computing environments. 22
In REF , the authors proposed an approach that uses genetic algorithm (GA) to find optimal solution to address the issue related to benefits and costs in cloud computing, and the results showed effectiveness of the approach in terms of virtual resource utilization, rate of return on investment and operation profit.
Cost-Aware Cloud Service Request Scheduling for SaaS Providers
Comput. J.
Comput. J.
Computer Science