Combination of Advanced Reservation and Resource Periodic Arrangement for RMSA in EON with Deep Reinforcement Learning

The Elastic Optical Networks (EON) provide a solution to the massive demand for connections and extremely high data traffic with the Routing Modulation and Spectrum Assignment (RMSA) as a challenge. In previous RMSA research, there was a high blocking probability because the route to be passed by the K-SP method with a deep neural network approach used the First Fit policy, and the modulation problem was solved with Modulation Format Identification (MFI) or BPSK using Deep Reinforcement Learning. The issue might be apparent in spectrum assignment because of the influence of Advanced Reservation (AR) and Resource Periodic Arrangement (RPA), which is a decision block on a connection request path with both idle and active data traffic. The study’s limitation begins with determining the modulation of m = 1 and m = 4, followed by the placement of frequencies, namely 13 with a combination of standard block frequencies 41224–24412, so that the simulation results are less than 0.0199, due to the combination of block frequency slices with spectrum allocation rule techniques.

Access and metro network convergence for flexible end-to-end network design

This paper reports on the architectural, protocol, physical layer, and integrated testbed demonstrations carried out by the DISCUS FP7 consortium in the area of access - metro network convergence. Our architecture modeling results show the vast potential for cost and power savings that node consolidation can bring. The architecture, however, also recognizes the limits of long-reach transmission for low-latency 5G services and proposes ways to address such shortcomings in future projects. The testbed results, which have been conducted end-to-end, across access - metro and core, and have targeted all the layers of the network from the application down to the physical layer, show the practical feasibility of the concepts proposed in the project

Towards a Virtualized Next Generation Internet

A promising solution to overcome the Internet ossification is network virtualization in which Internet Service Providers (ISPs) are decoupled into two tiers: service providers (SPs), and infrastructure providers (InPs). The former maintain and customize virtual network(s) to meet the service requirement of end-users, which is mapped to the physical network infrastructure that is managed and deployed by the latter via the Virtual Network Embedding (VNE) process. VNE consists of two major components: node assignment, and link mapping, which can be shown to be NP-Complete. In the first part of the dissertation, we present a path-based ILP model for the VNE problem. Our solution employs a branch-and-bound framework to resolve the integrity constraints, while embedding the column generation process to effectively obtain the lower bound for branch pruning. Different from existing approaches, the proposed solution can either obtain an optimal solution or a near-optimal solution with guarantee on the solution quality. A common strategy in VNE algorithm design is to decompose the problem into two sequential sub-problems: node assignment (NA) and link mapping (LM). With this approach, it is inexorable to sacrifice the solution quality since the NA is not holistic and not-reversible. In the second part, we are motivated to answer the question: Is it possible to maintain the simplicity of the Divide-and-Conquer strategy while still achieving optimality? Our answer is based on a decomposition framework supported by the Primal-Dual analysis of the path-based ILP model. This dissertation also attempts to address issues in two frontiers of network virtualization: survivability, and integration of optical substrate. In the third part, we address the survivable network embedding (SNE) problem from a network flow perspective, considering both splittable and non-splittable flows. In addition, the explosive growth of the Internet traffic calls for the support of a bandwidth abundant optical substrate, despite the extra dimensions of complexity caused by the heterogeneities of optical resources, and the physical feature of optical transmission. In this fourth part, we present a holistic view of motivation, architecture, and challenges on the way towards a virtualized optical substrate that supports network virtualization

Path protection in optical flexible networks with distance-adaptive modulation formats

International audienceThanks to a flexible frequency grid, Elastic Optical Networks (EONs) will support a more efficient usage of the spectrum resources. On the other hand, this efficiency may lead to even more disruptive effects of a failure on the number of involved connections with respect to traditional networks. In this paper, we study the problem of providing path protection to the lightpaths against a single fiber failure event in the optical layer. Our optimization task is to minimize the spectrum requirements for the protection in the network. We develop a scalable exact mathematical model using column generation for both shared and dedicated path protection schemes. The model takes into account practical constraints such as the modulation format, regenerators, and shared risk link groups. We demonstrate the effectiveness of our model through extensive simulation on two real-world topologies of different sizes. Finally, we compare the two protection schemes under different scenario assumptions, studying the impact of factors such as number of regenerators and demands on their performances

A novel predictive PCE-based protection strategy for resilient transport networks

© 2016. The ever increasing requirements of new Internet applications are pushing to optimize the design of optical networks. A key design criterion in network design is the ability to recover from failures in an agile and efficient manner. Protection capabilities are highly required in optical networks since the failure of an optical link might potentially lead to a significant traffic loss. Under this context, Network Coding Protection (NCP) has emerged as an innovative solution to proactively enable protection in an agile and efficient manner by means of throughput improvement techniques such as Network Coding (NC). Nevertheless, the benefits of NC can be reduced by the negative effects of inaccurate Network State Information (NSI), which are common in dynamic scenarios.In this paper, we propose a novel proactive protection strategy based on NC jointly with a Path Computation Element (PCE) architecture called Predictive Network Coding Protection (PNCP). PNCP leverages predictive techniques in order to mitigate the negative impact of the inaccurate NSI on the blocking probability. In addition, PNCP computes resilient lightpaths with a low amount of network resources devoted for path protection.By means of extensive simulation results we show that in comparison with proactive protection strategies such as Dedicated Path Protection (DPP), and conventional dynamic NCP, PNCP reduces the blocking probability as well as the network resources allocated for path protection in dynamic scenarios.Postprint (author's final draft