Multilayer optimization in radio resource allocation for the packet transmission in wireless networks

Na última década tem-se assistido a um crescimento exponencial das redes de comunicações sem fios, nomeadamente no que se refere a taxa de penetração do serviço prestado e na implementação de novas infra-estruturas em todo o globo. É ponto assente neste momento que esta tendência irá não só continuar como se fortalecer devido à convergência que é esperada entre as redes móveis sem fio e a disponibilização de serviços de banda larga para a rede Internet fixa, numa evolução para um paradigma de uma arquitectura integrada e baseada em serviços e aplicações IP. Por este motivo, as comunicações móveis sem fios irão ter um papel fundamental no desenvolvimento da sociedade de informação a médio e longo prazos. A estratégia seguida no projecto e implementação das redes móveis celulares da actual geração (2G e 3G) foi a da estratificação da sua arquitectura protocolar numa estrutura modular em camadas estanques, onde cada camada do modelo é responsável pela implementação de um conjunto de funcionalidades. Neste modelo a comunicação dá-se apenas entre camadas adjacentes através de primitivas de comunicação pré-estabelecidas. Este modelo de arquitectura resulta numa mais fácil implementação e introdução de novas funcionalidades na rede. Entretanto, o facto das camadas inferiores do modelo protocolar não utilizarem informação disponibilizada pelas camadas superiores, e vice-versa acarreta uma degradação no desempenho do sistema. Este paradigma é particularmente importante quando sistemas de antenas múltiplas são implementados (sistemas MIMO). Sistemas de antenas múltiplas introduzem um grau adicional de liberdade no que respeita a atribuição de recursos rádio: o domínio espacial. Contrariamente a atribuição de recursos no domínio do tempo e da frequência, no domínio espacial os recursos rádio mapeados no domínio espacial não podem ser assumidos como sendo completamente ortogonais, devido a interferência resultante do facto de vários terminais transmitirem no mesmo canal e/ou slots temporais mas em feixes espaciais diferentes. Sendo assim, a disponibilidade de informação relativa ao estado dos recursos rádio às camadas superiores do modelo protocolar é de fundamental importância na satisfação dos critérios de qualidade de serviço exigidos. Uma forma eficiente de gestão dos recursos rádio exige a implementação de algoritmos de agendamento de pacotes de baixo grau de complexidade, que definem os níveis de prioridade no acesso a esses recursos por base dos utilizadores com base na informação disponibilizada quer pelas camadas inferiores quer pelas camadas superiores do modelo. Este novo paradigma de comunicação, designado por cross-layer resulta na maximização da capacidade de transporte de dados por parte do canal rádio móvel, bem como a satisfação dos requisitos de qualidade de serviço derivados a partir da camada de aplicação do modelo. Na sua elaboração, procurou-se que o standard IEEE 802.16e, conhecido por Mobile WiMAX respeitasse as especificações associadas aos sistemas móveis celulares de quarta geração. A arquitectura escalonável, o baixo custo de implementação e as elevadas taxas de transmissão de dados resultam num processo de multiplexagem de dados e valores baixos no atraso decorrente da transmissão de pacotes, os quais são atributos fundamentais para a disponibilização de serviços de banda larga. Da mesma forma a comunicação orientada à comutação de pacotes, inenente na camada de acesso ao meio, é totalmente compatível com as exigências em termos da qualidade de serviço dessas aplicações. Sendo assim, o Mobile WiMAX parece satisfazer os requisitos exigentes das redes móveis de quarta geração. Nesta tese procede-se à investigação, projecto e implementação de algoritmos de encaminhamento de pacotes tendo em vista a eficiente gestão do conjunto de recursos rádio nos domínios do tempo, frequência e espacial das redes móveis celulares, tendo como caso prático as redes móveis celulares suportadas no standard IEEE802.16e. Os algoritmos propostos combinam métricas provenientes da camada física bem como os requisitos de qualidade de serviço das camadas superiores, de acordo com a arquitectura de redes baseadas no paradigma do cross-layer. O desempenho desses algoritmos é analisado a partir de simulações efectuadas por um simulador de sistema, numa plataforma que implementa as camadas física e de acesso ao meio do standard IEEE802.16e.

Performance analysis of 4G wireless networks using system level simulator

In the last decade, mobile wireless communications have witnessed an explosive growth in the user’s penetration rate and their widespread deployment around the globe. In particular, a research topic of particular relevance in telecommunications nowadays is related to the design and implementation of mobile communication systems of 4th generation (4G). 4G networks will be characterized by the support of multiple radio access technologies in a core network fully compliant with the Internet Protocol (all IP paradigms). Such networks will sustain the stringent quality of service (QoS) requirements and the expected high data rates from the type of multimedia applications (i.e. YouTube and Skype) to be available in the near future. Therefore, 4G wireless communications system will be of paramount importance on the development of the information society in the near future. As 4G wireless services will continue to increase, this will put more and more pressure on the spectrum availability. There is a worldwide recognition that methods of spectrum managements have reached their limit and are no longer optimal, therefore new paradigms must be sought. Studies show that most of the assigned spectrum is under-utilized, thus the problem in most cases is inefficient spectrum management rather spectrum shortage. There are currently trends towards a more liberalized approach of spectrum management, which are tightly linked to what is commonly termed as Cognitive Radio (CR). Furthermore, conventional deployment of 4G wireless systems (one BS in cell and mobile deploy around it) are known to have problems in providing fairness (users closer to the BS are more benefited relatively to the cell edge users) and in covering some zones affected by shadowing, therefore the use of relays has been proposed as a solution. To evaluate and analyse the performances of 4G wireless systems software tools are normally used. Software tools have become more and more mature in recent years and their need to provide a high level evaluation of proposed algorithms and protocols is now more important. The system level simulation (SLS) tools provide a fundamental and flexible way to test all the envisioned algorithms and protocols under realistic conditions, without the need to deal with the problems of live networks or reduced scope prototypes. Furthermore, the tools allow network designers a rapid collection of a wide range of performance metrics that are useful for the analysis and optimization of different algorithms. This dissertation proposes the design and implementation of conventional system level simulator (SLS), which afterwards enhances for the 4G wireless technologies namely cognitive Radios (IEEE802.22) and Relays (IEEE802.16j). SLS is then used for the analysis of proposed algorithms and protocols.

Governance structures and performance management systems in universities: a comparative study between the UK and Portugal

À semelhança do que aconteceu em muitas instituições públicas, as universidades têm enfrentado pressões crescentes para mudar, tendo de repensar as suas formas de governança e de gestão, dando mais ênfase à implementação de sistemas de gestão do desempenho (SGD). Apesar de existirem vários estudos sobre o desempenho, estes têm ignorado o uso dado à informação recolhida. Além disso, e apesar de terem ocorrido várias reformas na governança destas instituições, existem ainda poucos estudos que relacionam a governança e o desempenho. Assim, esta pesquisa visa explorar a forma como as universidades medem, reportam e gerem o desempenho e como as estruturas de governança se relacionam com estas práticas. Para alcançar o objetivo proposto, um estudo comparativo entre universidades britânicas e portuguesas foi realizado. Os dados foram recolhidos através da utilização de uma metodologia qualitativa, sendo os métodos utilizados a análise documental e entrevistas semi-estruturadas a membros dos órgãos de governo e gestão de cada instituição. A análise dos dados mostrou a inexistência de um sistema completamente integrado de gestão de desempenho (SGD) em ambas as instituições, essencialmente devido à falta de práticas de gestão de desempenho. De facto, apesar de alguns dos entrevistados terem reportado o "uso positivo" de dados sobre o desempenho, alguns relataram o "não uso" desses dados, principalmente em relação ao desempenho individual, e outros o "mau uso" dessa informação, tendo sido reportadas práticas de gaming e deturpação dos resultados. Como forma de ultrapassar alguns destes problemas, verificou-se a co-existência de duas estruturas de governança: uma 'formal', da qual fazem parte todos os órgão de governo, com um valor mais 'simbólico'; e uma estrutura 'paralela', constituída por órgãos mais ágeis, que gerem a universidade no dia a dia. Verificou-se terem sido vários os fatores a afetarem, negativa e positivamente, os SGD em ambas as instituições, tendo sido rotulados de "inibidores" e "determinantes", respetivamente. A pesquisa mostrou que, apesar de as estruturas de governança serem importantes para a implementação e funcionamento de um SGD, há outros fatores que precisam de ser levados em consideração, nomeadamente, o nível de comunicação e o nível de envolvimento dos atores no processo. Estes dois fatores são considerados relevantes para a integração bem sucedida de práticas de medição, reporte e gestão de desempenho. Esta integração, juntamente com outras mudanças que ocorreram em termos de governança, contribuirá certamente para que se passe de um sistema em que se governa o desempenho para um sistema em que se governa para o desempenho.

Decentralizing IP mobility management in future networks

The massive adoption of sophisticated mobile devices and applications led to the increase of mobile data in the last decade, which it is expected to continue. This increase of mobile data negatively impacts the network planning and dimension, since core networks are heavy centralized. Mobile operators are investigating atten network architectures that distribute the responsibility of providing connectivity and mobility, in order to improve the network scalability and performance. Moreover, service providers are moving the content servers closer to the user, in order to ensure high availability and performance of content delivery. Besides the e orts to overcome the explosion of mobile data, current mobility management models are heavy centralized to ensure reachability and session continuity to the users connected to the network. Nowadays, deployed architectures have a small number of centralized mobility anchors managing the mobile data and the mobility context of millions of users, which introduces issues related to performance and scalability that require costly network mechanisms. The mobility management needs to be rethought out-of-the box to cope with atten network architectures and distributed content servers closer to the user, which is the purpose of the work developed in this Thesis. The Thesis starts with a characterization of mobility management into well-de ned functional blocks, their interaction and potential grouping. The decentralized mobility management is studied through analytical models and simulations, in which di erent mobility approaches distinctly distribute the mobility management functionalities through the network. The outcome of this study showed that decentralized mobility management brings advantages. Hence, it was proposed a novel distributed and dynamic mobility management approach, which is exhaustively evaluated through analytical models, simulations and testbed experiments. The proposed approach is also integrated with seamless horizontal handover mechanisms, as well as evaluated in vehicular environments. The mobility mechanisms are also speci ed for multihomed scenarios, in order to provide data o oading with IP mobility from cellular to other access networks. In the pursuing of the optimized mobile routing path, a novel network-based strategy for localized mobility is addressed, in which a replication binding system is deployed in the mobility anchors distributed through the access routers and gateways. Finally, we go further in the mobility anchoring subject, presenting a context-aware adaptive IP mobility anchoring model that dynamically assigns the mobility anchors that provide the optimized routing path to a session, based on the user and network context. The integration of dynamic and distributed concepts in the mobility management, such as context-aware adaptive mobility anchoring and dynamic mobility support, allow the optimization of network resources and the improvement of user experience. The overall outcome demonstrates that decentralized mobility management is a promising direction, hence, its ideas should be taken into account by mobile operators in the deployment of future networks.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

Technical and economic resources management in smart grids using heuristic optimization methods

Intensive use of Distributed Generation (DG) represents a change in the paradigm of power systems operation making small-scale energy generation and storage decision making relevant for the whole system. This paradigm led to the concept of smart grid for which an efficient management, both in technical and economic terms, should be assured. This paper presents a new approach to solve the economic dispatch in smart grids. The proposed methodology for resource management involves two stages. The first one considers fuzzy set theory to define the natural resources range forecast as well as the load forecast. The second stage uses heuristic optimization to determine the economic dispatch considering the generation forecast, storage management and demand response

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

A long-term risk management tool for electricity markets using swarm intelligence

This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

Demand response management in power systems using a particle swarm optimization approach

Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.

Space-time monitoring of prescribed burnt soils performance – an effective tool for forest management

Among the most important measures to prevent wild forest fires is the use of prescribed and controlled burning actions in order to reduce the availability of fuel mass. However, the impact of these activities on soil physical and chemical properties varies according to the type of both soil and vegetation and is not fully understood. Therefore, soil monitoring campaigns are often used to measure these impacts. In this paper we have successfully used three statistical data treatments - the Kolmogorov-Smirnov test followed by the ANOVA and the Kruskall-Wallis tests – to investigate the variability among the soil pH, soil moisture, soil organic matter and soil iron variables for different monitoring times and sampling procedures.

Acqusition and data analysis of the eco-efficiency for the establishment of indicators parameters for industrial environmental sustainability

The industrial activity is inevitably associated with a certain degradation of the environmental quality, because is not possible to guarantee that a manufacturing process can be totally innocuous. The eco-efficiency concept is globally accepted as a philosophy of entreprise management, that encourages the companies to become more competitive, innovative and environmentally responsible by promoting the link between its companies objectives for excellence and its objectives of environmental excellence issues. This link imposes the creation of an organizational methodology where the performance of the company is concordant with the sustainable development. The main propose of this project is to apply the concept of eco-efficiency to the particular case of the metallurgical and metal workshop industries through the development of the particular indicators needed and to produce a manual of procedures for implementation of the accurate solution.

Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

O capital intelectual e a performance das empresas do PSI 20

Num contexto de crescente complexidade e disponibilidade de informação, a gestão do capital intelectual assume cada vez mais preponderância como vantagem competitiva para as empresas que procuram maximizar o valor gerado. Esta investigação usa como metodologia príncipal o VAIC (coeficiente intelectual do valor adicionado), para assim estudar a existência de relação entre capital intelectual e a performance bolsista e financeira das empresas do PSI20. O VAIC é decomposto nos seus três indicadores de eficiência, tais como: capital humano, capital estrutural e capital físico. Os dados contemplam quinze empresas e nove anos de análise (2003 - 2011). Elaborou-se uma abordagem que recorre à utilização de técnicas econométricas para reduzir potênciais falhas no tratamento de dados em painel. Os resultados da análise demonstram uma relação positiva entre a aposta em capital intelectual a performance bolsista e financeira, ou seja, a utilização e gestão eficientes do capital intelectual contribuem de forma significativa na avaliação bolsista e financeira das empresas do PSI20.