Abstract
Cloud computing has been a cost-efficient paradigm for deploying various applications in datacenters in recent years. Therefore, efficient provisioning for virtual data center (VDC) requests from different service providers (SPs) over physical data centers plays a vital role in improving the quality of service (QoS) and reducing the operational cost of SPs. Therefore, a significant attention has been paid for the VDC provisioning problem. However, few approaches have been proposed for the problem of reliable VDC embedding across multiple data centers, as most of them only consider the problem of VDC mapping within a single data center. In this paper, we study the problem of QoS-aware VDC provisioning across multiple data centers, such that the total bandwidth consumption in the inter-data center backbone network is minimized while satisfying the reliability requirement of each VDC request. We formulate this problem as a mathematical optimization problem by using integer linear programming (ILP) and propose an efficient heuristic algorithm called reliable VDC embedding (RVDCE) algorithm to solve this NP-hard problem. The simulation results show that the proposed algorithm performs better in terms of blocking ratio, CPU resource consumption, and bandwidth consumption of backbone network than the existing solution. In addition, this paper has also incorporated integrated security to minimize security vulnerabilities seen in other similar approaches. Apart from demonstrating how to resolve security challenges in our VDC proposal, cost calculations have been implemented to demonstrate the robustness, resiliency, validity, and effectiveness of the VDC provisioning solution for cloud computing.
Highlights
Cloud computing has become a promising paradigm that enables users to share the various distributed resources [1], [2]
A resource request from a user can be abstracted as a request in virtual data center (VDC) [4], which is a collection of demands on virtual machines (VMs) with computing, memory, and storage resources and virtual links with bandwidth resources
The main challenge associated with VDC management in cloud data centers is efficient VDC provisioning, which aims at finding a mapping of VMs and virtual links to physical components [5] while complying with the service level agreements (SLAs) that have been agreed upon with the customers or users
Summary
Cloud computing has become a promising paradigm that enables users to share the various distributed resources [1], [2]. The main challenge associated with VDC management in cloud data centers is efficient VDC provisioning (i.e., mapping or embedding), which aims at finding a mapping of VMs and virtual links to physical components (i.e., servers, switches and physical links) [5] while complying with the service level agreements (SLAs) that have been agreed upon with the customers or users. In this work, we study the problem of reliable VDC embedding (RVDCE) across multiple data centers, such that the total bandwidth consumption of backbone network is minimized, while satisfying the QoS requirements of VDC request, and propose an efficient resource scheduling algorithm for solving the studied problem. The authors in [5] studied the problem of virtual data center embedding across distributed infrastructures They had proposed a management framework, Greenhead, for the problem of VDC mapping across multiple infrastructures. We assume that each data center has a Fat-Tree [31] topology
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
