Energy management in communication networks: a journey through modelling and optimization glasses

The widespread proliferation of Internet and wireless applications has produced a significant increase of ICT energy footprint. As a response, in the last five years, significant efforts have been undertaken to include energy-awareness into network management. Several green networking frameworks have been proposed by carefully managing the network routing and the power state of network devices. Even though approaches proposed differ based on network technologies and sleep modes of nodes and interfaces, they all aim at tailoring the active network resources to the varying traffic needs in order to minimize energy consumption. From a modeling point of view, this has several commonalities with classical network design and routing problems, even if with different objectives and in a dynamic context. With most researchers focused on addressing the complex and crucial technological aspects of green networking schemes, there has been so far little attention on understanding the modeling similarities and differences of proposed solutions. This paper fills the gap surveying the literature with optimization modeling glasses, following a tutorial approach that guides through the different components of the models with a unified symbolism. A detailed classification of the previous work based on the modeling issues included is also proposed

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

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

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Exploring optimal solutions for planning optical networks with graph coloring techniques

Optical networks are crucial in today’s communications, so their planning is of paramount importance. Routing and Wavelength Assignment (WA) are essential planning functions to transport the data in these networks. This work aims to study different graph coloring techniques for WA in static optical networks. We analyze and compare different graph coloring algorithms such as the Greedy heuristic, an exact algorithm based on Integer Linear Programming (ILP) and the Tabu Search meta-heuristic, for WA in optical networks. The studies are performed considering several real network scenarios, different logical and path topologies, and the number of colors and computation time of each one of the studied algorithms is analysed. We have concluded that the exact algorithm based on ILP, although giving always the optimum number of colors, is only applicable to networks with less than 20 nodes, due to its higher computation time. It was also concluded that the Tabu Search algorithm gives always the same results as the exact algorithm, for the real networks studied, but in a much faster computation time. Finally, we have concluded that the common Greedy algorithm performs as well as the Tabu Search algorithm, for all the real networks studied, but in some scenarios, with random path matrices, the Tabu Search gives a lower number of colors than the Greedy algorithm. For example, the Tabu Search gives less 35 colors than the Greedy algorithm for a random path matrix with 1000 paths and a 50% probability that each path has one or more links being used by the other paths.As redes óticas são fundamentais para as comunicações atuais, tendo o seu planeamento uma grande importância. O encaminhamento e a atribuição de comprimentos de onda são funções essenciais no planeamento do transporte de dados nestas redes. Este trabalho pretende estudar diferentes técnicas de coloração de grafos para a atribuição de comprimentos de onda nas redes óticas. Analisamos e comparamos diferentes algoritmos de atribuição de comprimentos de onda, como a heurística Greedy, um algoritmo exato baseado em Programação Linear Inteira (PLI) e um algoritmo de procura meta-heurístico, o Tabu Search. Estudaram-se estes algoritmos para diferentes redes reais, diferentes topologias lógicas e de caminhos, com o objetivo de analisar o número de cores e o tempo computacional obtidos por cada algoritmo estudado. Concluímos que o algoritmo exato baseado em PLI, embora devolva sempre um número de cores ótimo, aplica-se apenas a redes com menos de 20 nós, devido ao seu tempo computacional elevado. Também se concluiu que o Tabu Search devolve sempre os mesmos resultados que o algoritmo exato, para as redes reais, mas com mais rapidez computacional. Concluiu-se também para as redes reais, que o Greedy estima o mesmo número de cores que o Tabu Search. No entanto, com matrizes geradas aleatoriamente, nalguns casos, o Tabu Search retorna menos cores que o Greedy. Por exemplo, o Tabu Search devolve menos 35 cores que o Greedy para uma matriz de 1000 caminhos e 50% de probabilidade de cada caminho ter uma ou mais ligações pertencentes aos restantes caminhos

Planning and Management of Cloud Computing Networks

Résumé L’évolution de l’internet a un effet important sur une grande partie de la population mondiale. On l’utilise pour communiquer, consulter de l’information, travailler et se divertir. Son utilité exceptionnelle a conduit à une explosion de la quantité d’applications et de ressources informatiques. Cependant, la croissance du réseau entraîne une importante consommation énergétique. Si la consommation énergétique des réseaux de télécommunications et des centres de données était celle d’un pays, il se classerait 5e pays du monde. Pis, le nombre de serveurs dans le monde devrait être multiplié par 10 entre 2013 et 2020. Ce contexte nous a motivé à étudier des techniques et des méthodes pour affecter les ressources d’une façon optimale par rapport aux coûts, à la qualité de service, à la consommation énergétique et `a l’impact écologique. Les résultats que nous avons obtenus minimisent les dépenses d’investissement (CAPEX) et les dépenses d’exploitation (OPEX), réduisent d’un facteur 6 le temps de réponse, diminuent la consommation énergétique de 30% et divisent les émissions de CO2 par un facteur 60. L’infonuagique permet l’accès dynamique aux ressources informatiques comme un service. Les programmes sont exécutés sur des serveurs connectés `a l’internet, et les usagers peuvent les utiliser depuis leurs ordinateurs et dispositifs mobiles. Le premier avantage de cette architecture est de réduire le temps de mise en place des applications et l’interopérabilité. En effet, un nouvel utilisateur n’a besoin que d’un navigateur web. Il n’est forcé ni d’installer de programmes sur son ordinateur, ni de posséder un système d’exploitation spécifique. Le deuxième avantage est la disponibilité des applications et de l’information de fa ̧con continue. Celles-ci peuvent être utilisées `a partir de n’importe quel endroit et de n’importe quel dis- positif connecté `a l’internet. De plus, les serveurs et les ressources informatiques peuvent être affectés aux applications de fa ̧con dynamique, selon la quantité d’utilisateurs et la charge de travail. C’est ce que l’on appelle l’élasticité des applications.---------- Abstract The evolution of the Internet has a great impact on a big part of the population. People use it to communicate, query information, receive news, work, and as entertainment. Its extraordinary usefulness as a communication media made the number of applications and technological resources explode. However, that network expansion comes at the cost of an important power consumption. If the power consumption of telecommunication networks and data centers is considered as the power consumption of a country, it would rank at the 5th place in the world. Furthermore, the number of servers in the world is expected to grow by a factor of 10 between 2013 and 2020. This context motivates us to study techniques and methods to allocate cloud computing resources in an optimal way with respect to cost, quality of service (QoS), power consumption, and environmental impact. The results we obtained from our test cases show that besides minimizing capital expenditures (CAPEX) and operational expenditures (OPEX), the response time can be reduced up to 6 times, power consumption by 30%, and CO2 emissions by a factor of 60. Cloud computing provides dynamic access to IT resources as a service. In this paradigm, programs are executed in servers connected to the Internet that users access from their computers and mobile devices. The first advantage of this architecture is to reduce the time of application deployment and interoperability, because a new user only needs a web browser and does not need to install software on local computers with specific operating systems. Second, applications and information are available from everywhere and with any device with an Internet access

Exhaustive Search for Optimal Offline Spectrum Assignment in Elastic Optical Networks

Heuristic-based approaches are widely deployed in solving Spectrum Assignment problem. This causes the results to be unreliable in some test cases when the results are very far from the lowerbound. This paper presents an exhaustive search approach that starts with an initial seed of a solution achieved by a heuristic-based algorithm called “Longest First Fit” (LFF) and tries all possible permutations starting from this initial seed. The algorithm skips some branches and all its descendant permutations if it meets certain criteria that guarantees that those permutations will not lead to a better result. The experimental results show that the new algorithm has succeeded in achieving the lower-bound in 93% of the randomly generated test cases while the heuristic solver LFF can achieve 65%. The algorithm achieves these results in a reasonable running time of less than 10 seconds

Tabu Search Energy Optimization of Optical Grid Networks

The exponential growth in the Information and Communication Technology (ICT) sector has resulted in increased power consumption and there is growing recognition of the need to develop more energy efficient networks. It has been shown in the literature that energy aware routing schemes for wavelength division multiplexing (WDM) optical networks can significantly reduce the overall energy consumption on the network. Much of the recent work has concentrated on switching off the unused network components during low utilization periods. In this thesis, we present a comprehensive heuristic algorithm that performs routing and wavelength assignment (RWA) and minimizes the overall energy consumption of a set of static lightpath demands, using Tabu search principle. We consider both unicast and anycast traffic models and investigate whether the additional flexibility of anycast routing can be exploited to further reduce network energy consumption