Abstract
Recently, the virtual data center embedding (VDCE) problem has drawn significant attention because of a growing need for efficient means of data center resource allocation. By ensuring a set of virtual data center (VDC) integration requests coming from his customers, among the main concern of an infrastructure provider is the maximization of the utilization rate of data center resources and benefits. However, existing VDCE solutions mostly focus on consolidating virtual machines in a single physical data center. Therefore, in this work, we improve the consolidated targets techniques, that consider only the virtual machines integration, by the consideration of network devices and fabrics (e.g., switches and paths/links). We consider new unreleased constraints such as multiple virtual nodes of the same request co-location, and intermediate node requirements when a virtual link is mapped. To address the above problem, in this paper, we propose a binary linear programming-based model, called BLP-VDCE, to solve the VDCE problem with network-aware consideration. This model ensures a simultaneous consolidated embedding of virtual nodes and virtual links. Extensive simulations show that solving the proposed BLP-VDCE model can efficiently embed VDC requests with a high physical resource utilization rate.
Mahdi Khemakhem
Associate Professor
My research interests are mainly in artificial intelligence including complex systems modeling, heuristics, meta-heuristics, and exact algorithms for combinatorial optimization problems in transportation and networks, resources management, cloud computing, IoT, etc.