Virtualisation and resource allocation in MECEnabled metro optical networks

The appearance of new network services and the ever-increasing network traffic and number of connected devices will push the evolution of current communication networks towards the Future Internet. In the area of optical networks, wavelength routed optical networks (WRONs) are evolving to elastic optical networks (EONs) in which, thanks to the use of OFDM or Nyquist WDM, it is possible to create super-channels with custom-size bandwidth. The basic element in these networks is the lightpath, i.e., all-optical circuits between two network nodes. The establishment of lightpaths requires the selection of the route that they will follow and the portion of the spectrum to be used in order to carry the requested traffic from the source to the destination node. That problem is known as the routing and spectrum assignment (RSA) problem, and new algorithms must be proposed to address this design problem. Some early studies on elastic optical networks studied gridless scenarios, in which a slice of spectrum of variable size is assigned to a request. However, the most common approach to the spectrum allocation is to divide the spectrum into slots of fixed width and allocate multiple, consecutive spectrum slots to each lightpath, depending on the requested bandwidth. Moreover, EONs also allow the proposal of more flexible routing and spectrum assignment techniques, like the split-spectrum approach in which the request is divided into multiple "sub-lightpaths". In this thesis, four RSA algorithms are proposed combining two different levels of flexibility with the well-known k-shortest paths and first fit heuristics. After comparing the performance of those methods, a novel spectrum assignment technique, Best Gap, is proposed to overcome the inefficiencies emerged when combining the first fit heuristic with highly flexible networks. A simulation study is presented to demonstrate that, thanks to the use of Best Gap, EONs can exploit the network flexibility and reduce the blocking ratio. On the other hand, operators must face profound architectural changes to increase the adaptability and flexibility of networks and ease their management. Thanks to the use of network function virtualisation (NFV), the necessary network functions that must be applied to offer a service can be deployed as virtual appliances hosted by commodity servers, which can be located in data centres, network nodes or even end-user premises. The appearance of new computation and networking paradigms, like multi-access edge computing (MEC), may facilitate the adaptation of communication networks to the new demands. Furthermore, the use of MEC technology will enable the possibility of installing those virtual network functions (VNFs) not only at data centres (DCs) and central offices (COs), traditional hosts of VFNs, but also at the edge nodes of the network. Since data processing is performed closer to the enduser, the latency associated to each service connection request can be reduced. MEC nodes will be usually connected between them and with the DCs and COs by optical networks. In such a scenario, deploying a network service requires completing two phases: the VNF-placement, i.e., deciding the number and location of VNFs, and the VNF-chaining, i.e., connecting the VNFs that the traffic associated to a service must transverse in order to establish the connection. In the chaining process, not only the existence of VNFs with available processing capacity, but the availability of network resources must be taken into account to avoid the rejection of the connection request. Taking into consideration that the backhaul of this scenario will be usually based on WRONs or EONs, it is necessary to design the virtual topology (i.e., the set of lightpaths established in the networks) in order to transport the tra c from one node to another. The process of designing the virtual topology includes deciding the number of connections or lightpaths, allocating them a route and spectral resources, and finally grooming the traffic into the created lightpaths. Lastly, a failure in the equipment of a node in an NFV environment can cause the disruption of the SCs traversing the node. This can cause the loss of huge amounts of data and affect thousands of end-users. In consequence, it is key to provide the network with faultmanagement techniques able to guarantee the resilience of the established connections when a node fails. For the mentioned reasons, it is necessary to design orchestration algorithms which solve the VNF-placement, chaining and network resource allocation problems in 5G networks with optical backhaul. Moreover, some versions of those algorithms must also implements protection techniques to guarantee the resilience system in case of failure. This thesis makes contribution in that line. Firstly, a genetic algorithm is proposed to solve the VNF-placement and VNF-chaining problems in a 5G network with optical backhaul based on star topology: GASM (genetic algorithm for effective service mapping). Then, we propose a modification of that algorithm in order to be applied to dynamic scenarios in which the reconfiguration of the planning is allowed. Furthermore, we enhanced the modified algorithm to include a learning step, with the objective of improving the performance of the algorithm. In this thesis, we also propose an algorithm to solve not only the VNF-placement and VNF-chaining problems but also the design of the virtual topology, considering that a WRON is deployed as the backhaul network connecting MEC nodes and CO. Moreover, a version including individual VNF protection against node failure has been also proposed and the effect of using shared/dedicated and end-to-end SC/individual VNF protection schemes are also analysed. Finally, a new algorithm that solves the VNF-placement and chaining problems and the virtual topology design implementing a new chaining technique is also proposed. Its corresponding versions implementing individual VNF protection are also presented. Furthermore, since the method works with any type of WDM mesh topologies, a technoeconomic study is presented to compare the effect of using different network topologies in both the network performance and cost.Departamento de Teoría de la Señal y Comunicaciones e Ingeniería TelemáticaDoctorado en Tecnologías de la Información y las Telecomunicacione

Optimization in Telecommunication Networks

Network design and network synthesis have been the classical optimization problems intelecommunication for a long time. In the recent past, there have been many technologicaldevelopments such as digitization of information, optical networks, internet, and wirelessnetworks. These developments have led to a series of new optimization problems. Thismanuscript gives an overview of the developments in solving both classical and moderntelecom optimization problems.We start with a short historical overview of the technological developments. Then,the classical (still actual) network design and synthesis problems are described with anemphasis on the latest developments on modelling and solving them. Classical results suchas Menger’s disjoint paths theorem, and Ford-Fulkerson’s max-flow-min-cut theorem, butalso Gomory-Hu trees and the Okamura-Seymour cut-condition, will be related to themodels described. Finally, we describe recent optimization problems such as routing andwavelength assignment, and grooming in optical networks.operations research and management science;

What comes after optical-bypass network? A study on optical-computing-enabled network

A new architectural paradigm, named, optical-computing-enabled network, is proposed as a potential evolution of the currently used optical-bypass framework. The main idea is to leverage the optical computing capabilities performed on transitional lightpaths at intermediate nodes and such proposal reverses the conventional wisdom in optical-bypass network, that is, separating in-transit lightpaths in avoidance of unwanted interference. In optical-computing-enabled network, the optical nodes are therefore upgraded from conventional functions of add-drop and cross-connect to include optical computing / processing capabilities. This is enabled by exploiting the superposition of in-transit lightpaths for computing purposes to achieve greater capacity efficiency. While traditional network design and planning algorithms have been well-developed for optical-bypass framework in which the routing and resource allocation is dedicated to each optical channel (lightpath), more complicated problems arise in optical-computing-enabled architecture as a consequence of intricate interaction between optical channels and hence resulting into the establishment of the so-called integrated / computed lightpaths. This necessitates for a different framework of network design and planning to maximize the impact of optical computing opportunities. In highlighting this critical point, a detailed case study exploiting the optical aggregation operation to re-design the optical core network is investigated in this paper. Numerical results obtained from extensive simulations on the COST239 network are presented to quantify the efficacy of optical-computing-enabled approach versus the conventional optical-bypass-enabled one.Comment: 17 pages, 3 figures, 4 tables; the author's version that has been accepted to Optical Fiber Technology Journal 202

Design and operation of mesh-restorable WDM networks

The explosive growth of Web-related services over the Internet is bringing millions of new users online, thus creating a growing demand for bandwidth. Wavelength Division Multiplexed (WDM) networks, employing wavelength routing has emerged as the dominant technology to satisfy this growing demand for bandwidth. As the amount of traffic carried is larger, any single failure can be catastrophic. Survivability becomes indispensable in such networks. Therefore, it is imperative to design networks that can quickly and efficiently recover from failures.;In this dissertation, we explore the design and operation of survivable optical networks. We study several survivability paradigms for surviving single link failures. A restoration model is developed based on a combination of these paradigms. We propose an optimal design and upgrade scheme for WDM backbone networks. We formulate an integer programming-based design problem to minimize the total facility cost. This framework provides a cost effective way of upgrading the network by identifying how much resources to budget at each stage of network evolution. This results in significant cost reductions for the network service provider.;As part of network operation, we capture multiple operational phases in survivable network operation as a single integer programming formulation. This common framework incorporates service disruption and includes a service differentiation model based on lightpath protection. However, the complexity of the optimization problem makes the formulation applicable only for network provisioning and o2ine reconfiguration. The direct use of such methods for online reconfiguration remains limited to small networks with few tens of wavelengths. We develop a heuristic algorithm based on LP relaxation technique for fast, near optimal, online reconfiguration. Since the ILP variables are relaxed, we provide a way to derive a feasible solution from the relaxed problem. Most of the current approaches assume centralized information. They do not scale well as they rely on per-flow information. This motivates the need for developing dynamic algorithms based on partial information. The partial information we use can be easily obtained from traffic engineering extensions to routing protocols. Finally, the performance of partial information routing algorithms is compared through simulation studies

Performance Analysis of Artificial Bee-Colony Algorithm for Routing and Wavelength Assignment in DWDM Transport Network

Setting up lightpaths for a set of requested connection of wavelength division multiplexing (WDM) network, is by routing and assigning wavelengths to each connection. So as to minimize the use of network resources or maximize the traffic served, is called the routing and wavelength assignment (RWA) problem. A new idea based on Artificial Bee Colony (ABC) algorithm is introduced for solving RWA problem which is known to be an NP-hard problem. In the proposed ABC-RWA approach every food source represents a possible and feasible candidate lightpath between each original and destination node span in demand matrix. The situation of the food source is modified by some artificial bee in the population where the aim is to discover the places of food sources. The food source with the highest nectar value seems to be a solution which is evaluated by the fitness function. This thesis proposes solutions to solve the RWA problem using artificial bee-colony algorithm in order to achieve better performance of the network connection to serve a given demand matrix of an optical network to reach RWA global solution. The work will evaluate the path length (propagation delay) for solving RWA problem with ABC algorithm in a real-world optical networks test bench to find optimal routes for connection request in demand matrix according to objective function and some physical and operational constraints in Dense Wavelength Division Multiplexing (DWDM) optical networks. Based on simulation with several generated traffic distribution, ABC algorithm can be used to solve routing and wavelength problem at DWDM transport network as shown that in line with iteration process the path length observed toward minimum value. The number of iteration needed to reach the fitness value depends on several parameter such as number of connection request, number of wavelength and alternative path, the distribution of generated traffic and also population size

Particle swarm optimization for routing and wavelength assignment in next generation WDM networks.

PhDAll-optical Wave Division Multiplexed (WDM) networking is a promising technology for long-haul backbone and large metropolitan optical networks in order to meet the non-diminishing bandwidth demands of future applications and services. Examples could include archival and recovery of data to/from Storage Area Networks (i.e. for banks), High bandwidth medical imaging (for remote operations), High Definition (HD) digital broadcast and streaming over the Internet, distributed orchestrated computing, and peak-demand short-term connectivity for Access Network providers and wireless network operators for backhaul surges. One desirable feature is fast and automatic provisioning. Connection (lightpath) provisioning in optically switched networks requires both route computation and a single wavelength to be assigned for the lightpath. This is called Routing and Wavelength Assignment (RWA). RWA can be classified as static RWA and dynamic RWA. Static RWA is an NP-hard (non-polynomial time hard) optimisation task. Dynamic RWA is even more challenging as connection requests arrive dynamically, on-the-fly and have random connection holding times. Traditionally, global-optimum mathematical search schemes like integer linear programming and graph colouring are used to find an optimal solution for NP-hard problems. However such schemes become unusable for connection provisioning in a dynamic environment, due to the computational complexity and time required to undertake the search. To perform dynamic provisioning, different heuristic and stochastic techniques are used. Particle Swarm Optimisation (PSO) is a population-based global optimisation scheme that belongs to the class of evolutionary search algorithms and has successfully been used to solve many NP-hard optimisation problems in both static and dynamic environments. In this thesis, a novel PSO based scheme is proposed to solve the static RWA case, which can achieve optimal/near-optimal solution. In order to reduce the risk of premature convergence of the swarm and to avoid selecting local optima, a search scheme is proposed to solve the static RWA, based on the position of swarm‘s global best particle and personal best position of each particle. To solve dynamic RWA problem, a PSO based scheme is proposed which can provision a connection within a fraction of a second. This feature is crucial to provisioning services like bandwidth on demand connectivity. To improve the convergence speed of the swarm towards an optimal/near-optimal solution, a novel chaotic factor is introduced into the PSO algorithm, i.e. CPSO, which helps the swarm reach a relatively good solution in fewer iterations. Experimental results for PSO/CPSO based dynamic RWA algorithms show that the proposed schemes perform better compared to other evolutionary techniques like genetic algorithms, ant colony optimization. This is both in terms of quality of solution and computation time. The proposed schemes also show significant improvements in blocking probability performance compared to traditional dynamic RWA schemes like SP-FF and SP-MU algorithms