Ignacio de Miguel

Dynamic Routing and Wavelength Assignment in Optical Networks by Means of Genetic Algorithms

We propose a novel genetic algorithm for solving the dynamic routing and wavelength assignment (DRWA) problem in wavelength-routed optical networks. The algorithm not only obtains low call blocking probability, but it also employs a very short computation time. Moreover, it is capable of providing fairness among connections, that is, to offer approximately the same quality of service (in terms of blocking probability) for all source-destination node pairs. Since requirements on optical network availability are highly severe, we also propose an extension of the algorithm to provide fault-tolerance capability at the optical layer. It is achieved by means of protection, where each optical connection request is provided with a pair of lightpaths (a primary and a backup lightpath). Again, the genetic algorithm proves to be highly efficient, in this case, at performing routing and wavelength assignment of pairs of lightpaths.

Cognitive dynamic optical networks [invited]

The use of cognition is a promising element for the control of heterogeneous optical networks. Not only are cognitive networks able to sense current network conditions and act according to them, but they also take into account the knowledge acquired through past experiences; that is, they include learning with the aim of improving performance. In this paper, we review the fundamentals of cognitive networks and focus on their application to the optical networking area. In particular, a number of cognitive network architectures proposed so far, as well as their associated supporting technologies, are reviewed. Moreover, several applications, mainly developed in the framework of the EU FP7 Cognitive Heterogeneous Reconfigurable Optical Network (CHRON) project, are also described.

Polymorphic architectures for optical networks and their seamless evolution towards next generation networks

This paper proposes a novel polymorphic framework for optical networking and a seamless evolution path from optical circuit-switched towards optical packet-switched networks. We show that by simultaneously supporting several optical switching paradigms in a single physical topology, efficient and flexible optical networks can be built. The supported paradigms are associated with different Classes of Service (CoS) in order to provide service differentiation at the optical layer. Two polymorphic architectures are presented, one based on optical circuit switching paradigms with different grades of dynamism, and a second one based on optical labeled burst-switched networks with the added capability of dynamic lightpath provisioning. These architectures provide a seamless evolution path towards an efficient IP-over-WDM approach with service differentiation. Moreover, the proposed polymorphic architectures are fully compatible with the GMPLS unified control plane. We present in a detailed form the proposed polymorphic framework, including the selection of switching paradigms, its support for CoS, the network and control architecture, and a possible seamless evolution towards optical packet-switched networks. Possible implementation examples of optical network nodes that support the proposed polymorphic architectures are also presented.

Genetic Algorithm for Joint Routing and Dimensioning of Dynamic WDM Networks

The dynamic operation of WDM networks might lead to significant wavelength savings, when compared with their static counterpart, at the expense of facing nonzero blocking probability. Hence, efficient dimensioning (i.e., determining each link capacity) and control methods are required to operate these networks. Typically, the dimensioning of WDM networks is carried out only after the routing algorithm has been defined. However, this way of designing the network might result in inefficient solutions in terms of wavelength requirements. We propose a novel genetic algorithm to solve the joint routing and dimensioning problem in dynamic WDM networks, with the aim of obtaining a network cost close to minimum while guaranteeing an upper bound on the blocking probability. Used prior to network operation, the algorithm determines which route should be used for each potential connection and also dimensions the number of wavelengths required in each link. The efficiency of the algorithm is validated in ring and mesh topologies, providing wavelength savings of up to 17% when compared with the best existing algorithm to date. Moreover, since the routes provided by the genetic algorithm are stored in routing tables, it also ensures extremely fast on-line network operation.

Next generation flexible and cognitive heterogeneous optical networks

Optical networking is the cornerstone of the Future Internet as it provides the physical infrastructure of the core backbone networks. Recent developments have enabled much better quality of service/experience for the end users, enabled through the much higher capacities that can be supported. Furthermore, optical networking developments facilitate the reduction of complexity of operations at the IP layer and therefore reduce the latency of the connections and the expenditures to deploy and operate the networks. New research directions in optical networking promise to further advance the capabilities of the Future Internet. In this book chapter, we highlight the latest activities of the optical networking community and in particular what has been the focus of EU funded research. The concepts of flexible and cognitive optical networks are introduced and their key expected benefits are highlighted. The overall framework envisioned for the future cognitive flexible optical networks are introduced and recent developments are presented.

EPON bandwidth allocation algorithm based on automatic weight adaptation to provide client and service differentiation

In this article, a new dynamic bandwidth allocation algorithm for the upstream channel of Ethernet Passive Optical Networks, called DySLa, is proposed not only to provide service differentiation but also to offer subscriber differentiation. In contrast to previous methods in which the performance of each class of service is not insured, DySLa is continuously evaluating the mean packet delay and guarantees that the highest priority services fulfil the packet delay requirements in the access network for every type of client. Simulation results show that DySLa can maintain both the mean packet delay and packet loss ratio below the maximum upper bounds permitted for the most sensitive services of every class of customer. Moreover, DySLa outperforms other dynamic bandwidth allocation algorithms which provide service and client differentiation and it makes a fairer bandwidth distribution than those methods.

Provision of end-to-end delay guarantees in wavelength-routed optical burst-switched networks

In Wavelength-Routed Optical Burst-Switched Networks (WR-OBS), lightpaths are dynamically established for the transmission of bursts (aggregation of packets in edge routers) through a bufferless optical core. In this paper, we show how WR-OBS can provide end-to-end delay guarantees, and introduce methods to achieve fairness in the network. The conditions under which WR-OBS bring operational advantages when compared to wavelength-routed optical networks (WRONs) are identified using an example of a real network and taking into account the diameter of the network and the number of wavelengths required.

Virtual topology reconfiguration in optical networks by means of cognition: Evaluation and experimental validation [invited]

In optical networking, virtual topologies have been introduced mainly to provide service providers with logical connections equipped with a reserved amount of bandwidth, which can be exploited to interconnect their equipment at the edges of the transport infrastructure. Virtual topologies are thus basically an abstraction of the real substrate, created by means of a process called virtual topology design (VTD). VTD is a complex task, affected by many parameters and constraints, and among them current traffic conditions are very relevant. Indeed, it is possible that after a certain time a virtual topology becomes inappropriate to serve current traffic. In such cases, the virtual topology can be reconfigured by creating new lightpaths or modifying or deleting existing ones, thus possibly creating some service interruptions. In this paper a new virtual topology reconfiguration technique is presented. In this technique, a cognitive entity designs and reconfigures virtual topologies by exploiting traffic forecasting solutions and taking advantage of past history. Moreover, a new transition method is also proposed to reduce the impact of instable routing tables during the reconfiguration process. We demonstrate, by means of simulation, the advantages of the proposed methods, as they reduce both the operational costs and the resources in operation while maintaining low packet loss ratio. Furthermore, we validate the operation of the proposed solutions in an emulated testbed.

An auto-tuning PID control system based on genetic algorithms to provide delay guarantees in Passive Optical Networks

Abstract Passive Optical Networks (PONs) are the most important access architectures since their deployment is massive all around the world. However, the QoS (Quality of Service) and the efficient management of the network resources have become the key point, especially with the new emerging services and applications. In particular, the delay and the bandwidth are becoming important limiting factors for the user experience. As a consequence, in a previous research we proposed the implementation of PID (Proportional-Integral-Derivative) control strategies to manage these networks parameters in PONs, demonstrating higher efficiency and more robustness than other previous existing algorithms. It is worth emphasizing that this is the first time to apply this control strategy in PONs access networks. However, in this paper we improve the PID control strategy by automating the tuning process with a genetic algorithm. Indeed, we have developed a novel automatic tuning technique based on genetic algorithms to tune a P controller that provides delay guarantees. Simulation results show that the control strategy reduces the tuning time up to 64% in comparison with the Ziegler–Nichols manual technique (ZN). On the other hand, it is demonstrated that our proposal is more accurate and robust that ZN since the genetic algorithm automatically evolves to the best solutions of the tuning parameters in contrast to the manual experiments required for the ZN method. Furthermore, we have complemented the use of the P controller with a new dynamic Admission Control (AC) module. This module implements a policy to selectively transmit or drop packets and leads a better delay control. The simulation analysis reveals that the real time evolution of the delay with the dynamic AC is more stable when compare to a conventional and simple fixed AC, reaching differences near one order of magnitude in the delay fluctuations.

Experimental demonstration of a cognitive quality of transmission estimator for optical communication systems

We report on the experimental performance of a case-based reasoning technique to predict whether optical channels fulfill quality of transmission requirements, thus supporting impairment-aware networking. Validation is performed in a WDM 80 Gb/s PDM-QPSK testbed.