Reciprocal Resource Fairness: Towards Cooperative Multiple-Resource Fair Sharing in IaaS Clouds

Resource sharing in virtualized environments have been demonstrated significant benefits to improve application performance and resource/energy efficiency. However, resource sharing, especially for multiple resource types, poses several severe and challenging problems in pay-as-you-use cloud environments, such as sharing incentive, free-riding, lying and economic fairness. To address those problems, we propose Reciprocal Resource Fairness (RRF), a novel resource allocation mechanism to enable fair sharing multiple types of resource among multiple tenants in new-generation cloud environments. RRF implements two complementary and hierarchical mechanisms for resource sharing: inter-tenant resource trading and intra-tenant weight adjustment. We show that RRF satisfies several highly desirable properties to ensure fairness. Experimental results show that RRF is promising for both cloud providers and tenants. Compared to existing cloud models, RRF improves virtual machine (VM) density and cloud providers´ revenue by 2.2X. For tenants, RRF improves application performance by 45% and guarantees 95% economic fairness among multiple tenants.