Towards min-cost virtual infrastructure embedding

Cloud computing has emerged as a prevailing platform for internet service hosting. To best utilize Cloud resources for profit making, Cloud providers rely on intelligent resource allocation algorithms when provisioning the virtualized environments for tenant service hosting. Conventional resource allocation proposals mainly focus on efficient allocation of the computing and storage resources, with little effort on ensuring the network performance of tenant services. To address this issue, a number of recent efforts abstract tenant services in the form of virtual infrastructures for resource allocation. A virtual infrastructure specifies the tenant's demand of both the computing resources for hosting virtual servers, and the network bandwidth for inter-virtual server communications. With the problem of resource allocation for virtual infrastructures being NP-hard in general networks, heuristic algorithms have been proposed for this problem. In this paper, we propose a novel optimization technique, named sequential rounding, to tackle the resource allocation problem for virtual infrastructures. The proposed technique extends the rounding technique used for the traditional virtual network embedding problem, while minimizing mapping conflicts introduced by the virtual infrastructure embed- ding problem. Experiments show that our proposed algorithm outperforms existing algorithms regarding both the acceptance ratio and average embedding cost of virtual requests.