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

Improvement at Network Planning using Heuristic Algorithm to Minimize Cost of Distance between Nodes in Wireless Mesh Networks

Wireless Mesh Networks (WMN) consists of wireless stations that are connected with each other in a semi-static configuration. Depending on the configuration of a WMN, different paths between nodes offer different levels of efficiency. One areas of research with regard to WMN is cost minimization. A Modified Binary Particle Swarm Optimization (MBPSO) approach was used to optimize cost. However, minimized cost does not guarantee network performance. This paper thus, modified the minimization function to take into consideration the distance between the different nodes so as to enable better performance while maintaining cost balance. The results were positive with the PDR showing an approximate increase of 17.83% whereas the E2E delay saw an approximate decrease of 8.33%

Contribution to spectrum management in cognitive radio networks: a cognitive management framework

To overcome the current under-utilization of spectrum resources, the CR (Cognitive Radio) paradigm has gained an increasing interest to perform the so-called Dynamic Spectrum Access (DSA). In this respect, Cognitive Radio networks (CRNs) have been strengthened with cognitive management support to push forward their deployment and commercialization. This dissertation has assessed the relevance of exploiting several cognitive management functionalities in various scenarios and case studies. Specifically, this dissertation has constructed a generic cognitive management framework, based on the fittingness factor concept, to support spectrum management in CRNs. Under this framework, the dissertation has addressed two of the most promising CR applications, namely an Opportunistic Spectrum Access (OSA) to licensed bands and open sharing of license-exempt bands. In the former application, several strategies that exploit temporal statistical dependence between primary activity/inactivity durations to perform a proactive spectrum selection have been discussed. A set of guidelines to select the most relevant strategy for a given environment have been provided. In the latter application, a fittingness factor-based spectrum selection strategy has been proposed to efficiency exploit the different bands. Several formulations of the fittingness factor have been compared, and their relevance have been assessed under different settings. Drawing inspiration from these applications, a more general proactive strategy exploiting a characterization of spectrum resources at both the time and frequency domains has been developed to jointly assist spectrum selection (SS) and spectrum mobility (SM) functionalities. Several variants of the proposed strategy, each combining different choices and options of implementation, have been compared to identify which of its components have the most significant impact on performance depending on the working conditions of the CRN. To assess rationality of the proposed strategy with respect to other strategies, a cost-benefit analysis has been conducted to confront the introduced gain in terms of user satisfaction level to the incurred cost in terms of signaling amount. Finally, the dissertation has conducted an analysis of practicality aspects in terms of robustness to environment uncertainty and applicability to realistic environments. With respect to the former aspect, robustness has been assessed in front of two sources of uncertainty, namely imperfection of the acquisition process and non-stationarity of the environment, and additional functionalities have been developed, when needed, to improve robustness. With respect to the latter, the proposed framework has been applied to a Digital Home (DH) environment to validate the obtained key findings under realistic conditions.Postprint (published version

Particle Swarm Optimization

Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field

Priority Based Cooperative Spectrum Sharing In Cognitive Radio Networks

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2011Bu tez çalışmasında, bilişsel radyo ağlarda, spektrum olanaklarını, herhangi bir lisans veya ödeme yapmayan ikincil kullanıcılar arasında dağıtan spektrum paylaşım mekanizmaları incelenmiş, özgün bir spektrum paylaşım mekanizması önerilmiş ve test edilmiştir. Önerilen yöntem, ikincil kullanıcıların bireysel spektrum kararları, öncelik değerleri ve mesajlaşma mekanizmasına dayanan, dağıtık bir spektrum paylaşım yöntemdir. Önerilen sistemdeki ağ modelinde, ikincil kullanıcılar arasındaki mesajlaşma ortak kontrol kanalı aracılığı ile gerçekleştirilmektedir. Mesajlaşma mekanizması kullanıcılar arasındaki iş birliğini, öncelik değerlerinin çevrel olarak ilerletilmesi ise kullanıcılar arasındaki adaleti sağlamaktadır. Bunun yanında, mesajlaşma topolojisi yardımıyla ortak kontrol kanalındaki mesajlaşma eksiklikleri modellenmektedir. Ağ modeli ve önerilen spektrum paylaşım yöntemi MATLAB Simulink ortamında simule edilmiş Trafik İsteği Karşılanma Oranı, Kanal Kaplama Oranı ve kullanıcılar arası Adalet metrikleri incelenmiştir. Elde edilen sonuçlar, kural tabanlı çalışan, bencil ve rasgele spektrum paylaşım stratejileri ile karşılaştırılmıştır. Performans metrikleri çeşitli ortamlarda incelenmiş ve önerilen sistemin performansının pek çok ortamda, koparılan mesajlaşma bağlantılarının belirli seviyenin üstüne çıkmadığı durumlarda, diğer yöntemlerden daha yüksek olduğu gözlemlenmiştir.In this thesis, spectrum sharing mechanisms are explored which distribute spectrum opportunities among secondary users do not have any license or payment right on the spectrum, a novel spectrum sharing mechanism is proposed and tested. Proposed scheme is a distributed spectrum sharing mechanism that is based on individual spectrum decisions, priority and messaging mechanism between cognitive radio users. Messaging among secondary users in the system model of the proposed study is achieved via common control channel. Messaging framework achieves cooperation and priority chaining ensures fairness among these users. In addition, a messaging topology is modeled that represents the deficiencies in the common control channel. The network model and proposed spectrum sharing system is simulated via MATLAB Simulink environment and Traffic Request Satisfaction Rate, Channel Occupancy Rate and Fairness among cognitive radio users metrics are extracted. The obtained results are compared with other techniques employing rule based channel selection strategies as selfish and random channel selection. Performance results are studied in variety of environments and it is observed that the proposed system performance outperforms other schemes at many cases especially when the number of broken messaging links is remained at a certain level.Yüksek LisansM.Sc