Dynamic resource management in SDN-based virtualized networks

Network virtualization allows for an abstraction between user and physical resources by letting a given physical infrastructure to be shared by multiple service providers. However, network virtualization presents some challenges, such as, efficient resource management, fast provisioning and scalability. By separating a network's control logic from the underlying routers and switches, software defined networking (SDN) promises an unprecedented simplification in network programmability, management and innovation by service providers, and hence, its control model presents itself as a candidate solution to the challenges in network virtualization. In this paper, we use the SDN control plane to efficiently manage resources in virtualized networks by dynamically adjusting the virtual network (VN) to substrate network (SN) mappings based on network status. We extend an SDN controller to monitor the resource utilisation of VNs, as well as the average loading of SN links and switches, and use this information to proactively add or remove flow rules from the switches. Simulations show that, compared with three state-of-art approaches, our proposal improves the VN acceptance ratio by about 40% and reduces VN resource costs by over 10%

A Multi-Step Reconfiguration Model for Active Distribution Network Restoration Integrating DG Start-Up Sequences

The ever-increasing penetration of Distributed Generators (DGs) in distribution networks suggests to enable their potentials in better fulfilling the restoration objective. The objective of the restoration problem is to resupply the maximum energy of loads considering their priorities using minimum switching operations. Basically, it is desired to provide a unique configuration that is valid regarding the load and generation profiles along the entire restorative period. However, this unique configuration may not satisfy at the same time: I) the DG start-up requirements at the beginning of the restoration plan and II) the topological conditions that would allow the DG to provide later on the most efficient support for the supply of loads. Therefore, it is proposed in this paper to allow a limited number of reconfiguration steps according to the DG start-up requirements. In addition, this paper presents a novel formulation for the reconfiguration problem that accounts for partial restoration scenarios where the whole unsupplied area cannot be restored. The decision variables of the proposed multi-step restoration problem are: I) the line switching actions at each step of the reconfiguration process, II) the load switching actions during the whole restorative period and, III) the active/reactive power dispatch of DGs during the whole restorative period. A relaxed AC power flow formulation is integrated to the optimization problem in order to ensure the feasibility of the solution concerning the operational safety constraints. The overall model is formulated in terms of a mixed-integer second-order cone programming. Two simulation scenarios are studied in order to illustrate different features of the proposed strategy and to demonstrate its effectiveness particularly in the case of large-scale outages in distribution networks

Management of Spectral Resources in Elastic Optical Networks

Recent developments in the area of mobile technologies, data center networks, cloud computing and social networks have triggered the growth of a wide range of network applications. The data rate of these applications also vary from a few megabits per second (Mbps) to several Gigabits per second (Gbps), thereby increasing the burden on the Inter- net. To support this growth in Internet data traffic, one foremost solution is to utilize the advancements in optical networks. With technology such as wavelength division multiplexing (WDM) networks, bandwidth upto 100 Gbps can be exploited from the optical fiber in an energy efficient manner. However, WDM networks are not efficient when the traffic demands vary frequently. Elastic Optical Networks (EONs) or Spectrum Sliced Elastic Optical Path Networks (SLICE) or Flex-Grid has been recently proposed as a long-term solution to handle the ever-increasing data traffic and the diverse demand range. EONs provide abundant bandwidth by managing the spectrum resources as fine-granular orthogonal sub-carriers that makes it suitable to accommodate varying traffic demands. However, the Routing and Spectrum Allocation (RSA) algorithm in EONs has to follow additional constraints while allocating sub-carriers to demands. These constraints increase the complexity of RSA in EONs and also, make EONs prone to the fragmentation of spectral resources, thereby decreasing the spectral efficiency. The major objective of this dissertation is to study the problem of spectrum allocation in EONs under various network conditions. With this objective, this dissertation presents the author\u27s study and research on multiple aspects of spectrum allocation in EONs: how to allocate sub-carriers to the traffic demands, how to accommodate traffic demands that varies with time, how to minimize the fragmentation of spectral resources and how to efficiently integrate the predictability of user demands for spectrum assignment. Another important contribution of this dissertation is the application of EONs as one of the substrate technologies for network virtualization

Self-adaptive online virtual network migration in network virtualization environments

This is the peer reviewed version of the following article: Zangiabady, M, Garcia‐Robledo, A, Gorricho, J‐L, Serrat‐Fernandez, J, Rubio‐Loyola, J. Self‐adaptive online virtual network migration in network virtualization environments. Trans Emerging Tel Tech. 2019; 30:e3692. https://doi.org/10.1002/ett.3692, which has been published in final form at https://doi.org/10.1002/ett.3692. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.In Network Virtualization Environments, the capability of operators to allocate resources in the Substrate Network (SN) to support Virtual Networks (VNs) in an optimal manner is known as Virtual Network Embedding (VNE). In the same context, online VN migration is the process meant to reallocate components of a VN, or even an entire VN among elements of the SN in real time and seamlessly to end-users. Online VNE without VN migration may lead to either over- or under-utilization of the SN resources. However, VN migration is challenging due to its computational cost and the service disruption inherent to VN components reallocation. Online VN migration can reduce migration costs insofar it is triggered proactively, not reactively, at critical times, avoiding the negative effects of both under- and over-triggering. This paper presents a novel online cost-efficient mechanism that self-adaptively learns the exact moments when triggering VN migration is likely to be profitable in the long term. We propose a novel self-adaptive mechanism based on Reinforcement Learning that determines the right trigger online VN migration times, leading to the minimization of migration costs while simultaneously considering the online VNE acceptance ratio.Peer ReviewedPostprint (author's final draft