Novel resource allocation mechanism for SDNbased data center networks Abstract   With the development of virtualization technologies, Service Providers (SP) can offer services to customers by renting various kinds of hardware resources from Data Centers (DC) instead of purchasing hardware equipment frequently, which not only increases the flexibility, but also decreases the cost. For the multitenant DC environment, each SP can be regarded as a DC tenant. Then, the request of each tenant could be abstracted as a Virtual Data Center (VDC) which is implemented by mapping the required virtual nodes and links onto physical servers and optical paths. Such process is also referred to as the VDC mapping, during which the corresponding resources will be allocated. It is aware that the VDC mapping problem is essentially different from the virtual network mapping problem, and the former one is much more complex than the latter one. Therefore, the solution of VDC mapping still faces many challenges. In this work, we focus on addressing the VDC mapping problem with a flexible and efficient resource allocation. Firstly, the concepts of Software Defined Networking (SDN) and Network Function Virtualization (NFV) are both introduced to construct a logically centralized and physically distributed resource allocation framework which decouples the server resource control and the network resource control. In this way, the whole resource allocation process can be managed in a more flexible and targeted way towards achieving high resource utilization. Secondly, a locationaware VDC partition process is introduced before VDC mapping based on the label propagation algorithm, which clusters the virtual nodes of a VDC request according to the communication frequency between any two virtual nodes. Generally, the higher the communication frequency, the more cost will be spent on network resource consumption, such that the virtual nodes clustered in the same group will be mapped onto the same DC to avoid excessive backbone network consumption. Lastly, a cost and security aware VDC mapping mechanism is proposed to address the corresponding resource allocation problem, which aims at minimizing the overall cost with both the basic resource constraints, mapping constraints, the wavelength continuity constraint and the security constraint taken into consideration. The experiment indicates that the proposed mechanism can decrease the overall VDC mapping cost by about 10%xe2x80x9325%, and increases the VDC acceptance rate and the total revenue by up to 34% and 71% respectively compared to the stateoftheart benchmarks.

Joint CorrelationAware VNF Selection and Placement in Cloud Data Center Networks Network Function Virtualization (NFV) brings great flexibility and scalability to the deployment of network services by decoupling network functions from dedicated devices, which has attracted more attention from both academia and industry. Network services in NFV are deployed in the form of Service Function Chain (SFC), which consists of multiple ordered Virtual Network Functions (VNFs). However, how to effectively place VNFs remains a problem to be solved. In this paper, we investigate joint correlationaware VNF selection and placement problem. We first formulate the problem as an Integer Linear Programming (ILP) problem and propose a method based on selflearning matrix to partition VNF correlation. Then, we design a Joint Correlationaware VNF Placement (JCVP) algorithm based on Dynamic Programming to transform the problem into several VNF mapping subproblems. Extensive simulation results show that compared with the previous algorithms our approach has better performance in link occupancy, SFC acceptance, and VNF utilization rate.