Incentive-driven QoS in peer-to-peer overlays

A well known problem in peer-to-peer overlays is that no single entity has control over the software, hardware and configuration of peers. Thus, each peer can selfishly adapt its behaviour to maximise its benefit from the overlay. This thesis is concerned with the modelling and design of incentive mechanisms for QoS-overlays: resource allocation protocols that provide strategic peers with participation incentives, while at the same time optimising the performance of the peer-to-peer distribution overlay. The contributions of this thesis are as follows. First, we present PledgeRoute, a novel contribution accounting system that can be used, along with a set of reciprocity policies, as an incentive mechanism to encourage peers to contribute resources even when users are not actively consuming overlay services. This mechanism uses a decentralised credit network, is resilient to sybil attacks, and allows peers to achieve time and space deferred contribution reciprocity. Then, we present a novel, QoS-aware resource allocation model based on Vickrey auctions that uses PledgeRoute as a substrate. It acts as an incentive mechanism by providing efficient overlay construction, while at the same time allocating increasing service quality to those peers that contribute more to the network. The model is then applied to lagsensitive chunk swarming, and some of its properties are explored for different peer delay distributions. When considering QoS overlays deployed over the best-effort Internet, the quality received by a client cannot be adjudicated completely to either its serving peer or the intervening network between them. By drawing parallels between this situation and well-known hidden action situations in microeconomics, we propose a novel scheme to ensure adherence to advertised QoS levels. We then apply it to delay-sensitive chunk distribution overlays and present the optimal contract payments required, along with a method for QoS contract enforcement through reciprocative strategies. We also present a probabilistic model for application-layer delay as a function of the prevailing network conditions. Finally, we address the incentives of managed overlays, and the prediction of their behaviour. We propose two novel models of multihoming managed overlay incentives in which overlays can freely allocate their traffic flows between different ISPs. One is obtained by optimising an overlay utility function with desired properties, while the other is designed for data-driven least-squares fitting of the cross elasticity of demand. This last model is then used to solve for ISP profit maximisation

Evaluation of optimal solutions in multicriteria models for intelligent decision support

La memoria se enmarca dentro de la optimización y su uso para la toma de decisiones. La secuencia lógica ha sido la modelación, implementación, resolución y validación que conducen a una decisión. Para esto, hemos utilizado herramientas del análisis multicrerio, optimización multiobjetivo y técnicas de inteligencia artificial. El trabajo se ha estructurado en dos partes (divididas en tres capítulos cada una) que se corresponden con la parte teórica y con la parte experimental. En la primera parte se analiza el contexto del campo de estudio con un análisis del marco histórico y posteriormente se dedica un capítulo a la optimización multicriterio en el se recogen modelos conocidos, junto con aportaciones originales de este trabajo. En el tercer capítulo, dedicado a la inteligencia artificial, se presentan los fundamentos del aprendizaje estadístico , las técnicas de aprendizaje automático y de aprendizaje profundo necesarias para las aportaciones en la segunda parte. La segunda parte contiene siete casos reales a los que se han aplicado las técnicas descritas. En el primer capítulo se estudian dos casos: el rendimiento académico de los estudiantes de la Universidad Industrial de Santander (Colombia) y un sistema objetivo para la asignación del premio MVP en la NBA. En el siguiente capítulo se utilizan técnicas de inteligencia artificial a la similitud musical (detección de plagios en Youtube), la predicción del precio de cierre de una empresa en el mercado bursátil de Nueva York y la clasificación automática de señales espaciales acústicas en entornos envolventes. En el último capítulo a la potencia de la inteligencia artificial se le incorporan técnicas de análisis multicriterio para detectar el fracaso escolar universitario de manera precoz (en la Universidad Industrial de Santander) y, para establecer un ranking de modelos de inteligencia artificial de se recurre a métodos multicriterio. Para acabar la memoria, a pesar de que cada capítulo contiene una conclusión parcial, en el capítulo 8 se recogen las principales conclusiones de toda la memoria y una bibliografía bastante exhaustiva de los temas tratados. Además, el trabajo concluye con tres apéndices que contienen los programas y herramientas, que a pesar de ser útiles para la comprensión de la memoria, se ha preferido poner por separado para que los capítulos resulten más fluidos

Parallel and Distributed Systems

Congreso Iberoamericano de Filosofía de la Ciencia y la Tecnología (4o. 2017. Salamanca, España

Sensors Science

Congreso Iberoamericano de Filosofía de la Ciencia y la Tecnología (4o. 2017. Salamanca, España

Knowledge extraction and representation

Congreso Iberoamericano de Filosofía de la Ciencia y la Tecnología (4o. 2017. Salamanca, España

Portfolio structure, real estate investment and the performance of defined contribution pension funds

With the growing importance of defined contribution (DC) pension funds around the world, concerns have arisen over their ability to provide adequate income replacement for members and the liquidity of their invesments. The first part of this thesis focuses on the illiquidity associated with real estate investments. The first chapter provides a discussion of liquidity within the context of DC pension funds. The second empirical chapter employs the tracking error optimisation procedure in the construction of portfolios that include direct real estate and selected liquid, publicly traded assets. We find that this helps to improve the performance of these blended portfolios. In the second part of this thesis, we look at various ways in which the real value of DC pension contributions can be preserved. The third empirical uses contemporary econometric approaches in the analysis of the dynamic relationship between asset returns and inflation/interest rate changes. Real estate and bonds were found to be a hedge against all the inflation/interest rates measures analysed. Some non-UK assets were also found to be a good hedge against selected benchmarks. The fourth empirical chapter of this PhD thesis examines the optimal allocation within portfolios designed to hedge against the various inflation and interest rate benchmarks. When the investment objective is to strictly track these benchmarks, bonds and real estate dominate the portfolios. Real estate, stocks and alternative assets receive significant allocations within the portfolios constructed to provide maximum risk adjusted returns relative to the minimum return benchmarks. We observe that the allocation to real estate reduced significantly following the global financial crisis period with bonds appearing to take its place. On the whole, this thesis contributes to the discussion on how best DC pension portfolios could be designed to comply with current investment regulations regarding liquidity and minimum returns requirements