Resource optimization for survivable embedding of virtual clusters in cloud data centers

With the popularity of cloud computing, optimizing cloud resource consumption while providing predictable cloud service has become one of the focuses of research in recent years. In order to ensure a predictable performance, the requests from tenants are abstracted as Virtual Clusters, which not only specify the computing demands, but also establish the communication requirements among virtual machines. While much work has been done on virtual cluster embedding under a variety of goals, very few people have studied this issue in consideration of service survivability, which also plays a vital role in ensuring the performance in cloud data centers. In this paper, we study the resource optimization for survivable embedding of virtual clusters and aim to minimize the consumption of cloud resources in terms of server and bandwidth, while ensuring that both the resource constraints and the survivability constraints are not violated. We formally define this problem and analyze its complexity, and design efficient algorithms to solve the problem. Comprehensive experimental results verify that the overall resource consumption can be significantly reduced by applying our proposals.