Integrating IPsec within OpenFlow Architecture for Secure Group Communication

Network security protocols such as IPsec have been used for many years to ensure robust end⁃to⁃end communication and are important in the context of SDN. Despite the widespread installation of IPsec to date, per⁃packet protection offered by the protocol is not very compatible with OpenFlow and flow⁃like behavior. OpenFlow architecture cannot aggregate IPsec⁃ESP flows in transport mode or tunnel mode because layer⁃3 information is encrypted and therefore unreadable. In this paper, we propose using the Security Parameter Index (SPI) of IPsec within the OpenFlow architecture to identify and direct IPsec flows. This enables IPsec to conform to the packet⁃based behavior of OpenFlow architecture. In addition, by distinguishing between IPsec flows, the architecture is particularly suited to secure group communication

Off-Peak Energy-Wise Link Reconfiguration for Virtualized Network Environment

Abstract-Energy consumption in Information and Communication Technology (ICT) is 10% of the total energy consumed in industrial countries. Recently, Virtualized Network Environment (VNE) has been emerged in this technology. Therefore, it is essential to develop novel techniques that reduce VNE's energy consumption. In this paper, we formulate a Binary Integer Linear Program (BILP) that reconfigures already allocated virtual networks to minimize VNE's link power consumption, during off-peak periods. Because the formulated BILP is N P-hard, a novel heuristic algorithm is also suggested. The simulation results confirm the proposed solutions save notable amount of energy in VNE's substrate links, during off-peak hours

Off-peak energy optimization for links in Virtualized Network Environment

Energy consumption in Information and Communication Technology (ICT) is estimated to be 10% of the total energy consumed in industrial countries. Besides, the population of ICT customers is growing. In order to handle the increasing traffic demands, service providers need to expand their network infrastructure. The recent proposed network virtualization technology helps slow down the infrastructure expansion by allowing the coexistence of multiple virtual networks over a single physical network. Although Virtualized Network Environment (VNE) slows down the infrastructure expansion and therefore controls power consumption, it is essential to develop new techniques to decrease VNE's energy consumption. In this paper, we discuss multiple novel energy saving reconfiguration methods that globally/locally optimize VNE's link power consumption, during off-peak time. The proposed fine-grained local reconfiguration enables the providers to adjust level of the reconfiguration, and accordingly control possible traffic disruptions. An Integer Linear Program (ILP) is formulated for each solution according to two power models, and considering the impact of traffic splitability. Because the formulated ILPs are not scalable to large network sizes, a novel heuristic algorithm is also suggested. The simulation results prove the proposed solutions are able to save notable amount of energy in physical links during off-peak time

GreenMap: Green mapping of MapReduce-based virtual networks onto a data center network and managing incast queueing delay

Energy consumption is a first-order concern for today's data centers. MapReduce is a cloud computing approach that is widely deployed in many data centers. Toward virtualizing data centers, we consider MapReduce-based virtual networks that need to be embedded onto a data center network. In this paper, we propose GreenMap, a novel energy-efficient embedding method that maps heterogeneous MapReduce-based virtual networks onto a heterogeneous data center network. Besides, we introduce a new incast problem that specially may happen in Virtualized Data Centers (VDCs). GreenMap also controls the incast queueing delay. We formulate a Mixed-Integer Disciplined Convex Program (MIDCP) for this method. Because the formulated MIDCP is NP-hard, we also propose a novel and scalable heuristic for GreenMap. Simulation results prove that both of the MIDCP and the heuristic reduce a data center network's energy consumption effectively, and control the incast queueing delay