Autonomous grid scheduling using probabilistic job runtime scheduling

Computational Grids are evolving into a global, service-oriented architecture – a universal platform for delivering future computational services to a range of applications of varying complexity and resource requirements. The thesis focuses on developing a new scheduling model for general-purpose, utility clusters based on the concept of user requested job completion deadlines. In such a system, a user would be able to request each job to finish by a certain deadline, and possibly to a certain monetary cost. Implementing deadline scheduling is dependent on the ability to predict the execution time of each queued job, and on an adaptive scheduling algorithm able to use those predictions to maximise deadline adherence. The thesis proposes novel solutions to these two problems and documents their implementation in a largely autonomous and self-managing way. The starting point of the work is an extensive analysis of a representative Grid workload revealing consistent workflow patterns, usage cycles and correlations between the execution times of jobs and its properties commonly collected by the Grid middleware for accounting purposes. An automated approach is proposed to identify these dependencies and use them to partition the highly variable workload into subsets of more consistent and predictable behaviour. A range of time-series forecasting models, applied in this context for the first time, were used to model the job execution times as a function of their historical behaviour and associated properties. Based on the resulting predictions of job runtimes a novel scheduling algorithm is able to estimate the latest job start time necessary to meet the requested deadline and sort the queue accordingly to minimise the amount of deadline overrun. The testing of the proposed approach was done using the actual job trace collected from a production Grid facility. The best performing execution time predictor (the auto-regressive moving average method) coupled to workload partitioning based on three simultaneous job properties returned the median absolute percentage error centroid of only 4.75%. This level of prediction accuracy enabled the proposed deadline scheduling method to reduce the average deadline overrun time ten-fold compared to the benchmark batch scheduler. Overall, the thesis demonstrates that deadline scheduling of computational jobs on the Grid is achievable using statistical forecasting of job execution times based on historical information. The proposed approach is easily implementable, substantially self-managing and better matched to the human workflow making it well suited for implementation in the utility Grids of the future

Autonomous grid scheduling using probabilistic job runtime forecasting.

Computational Grids are evolving into a global, service-oriented architecture a universal platform for delivering future computational services to a range of applications of varying complexity and resource requirements. The thesis focuses on developing a new scheduling model for general-purpose, utility clusters based on the concept of user requested job completion deadlines. In such a system, a user would be able to request each job to finish by a certain deadline. and possibly to a certain monetary cost. Implementing deadline scheduling is dependent on the ability to predict the execution time of each queued job. and on an adaptive scheduling algorithm able to use those predictions to maximise deadline adherence. The thesis proposes novel solutions to these two problems and documents their implementation in a largely autonomous and self-managing way. The starting point of the work is an extensive analysis of a representative Grid workload revealing consistent workflow patterns, usage cycles and correlations between the execution times of jobs and its properties commonly collected by the Grid middleware for accounting purposes. An automated approach is proposed to identify these dependencies and use them to partition the highly variable workload into subsets of more consistent and predictable behaviour. A range of time-series forecasting models, applied in this context for the first time, were used to model the job execution times as a function of their historical behaviour and associated properties. Based on the resulting predictions of job runtimes a novel scheduling algorithm is able to estimate the latest job start time necessary to meet the requested deadline and sort the queue accordingly to minimise the amount of deadline overrun. The testing of the proposed approach was done using the actual job trace collected from a production Grid facility. The best performing execution time predictor (the auto-regressive moving average method) coupled to workload partitioning based on three simultaneous job properties returned the median absolute percentage error eentroid of only 4.75CX. This level of prediction accuracy enabled the proposed deadline scheduling method to reduce the average deadline overrun time ten-fold compared to the benchmark batch scheduler. Overall, the thesis demonstrates that deadline scheduling of computational jobs on the Grid is achievable using statistical forecasting of job execution times based on historical information. The proposed approach is easily implementable, substantially self-managing and better matched to the human workflow making it well suited for implementation in the utility Grids of the future

Contributions to the Optimisation of aircraft noise abatement procedures

Tot i que en les últimes dècades la reducció del soroll emès pels avions ha estat substancial, el seu impacte a la població ubicada a prop dels aeroports és un problema que encara persisteix. Contenir el soroll generat per les operacions d'aeronaus, tot assumint al mateix temps la creixent demanda de vols, és un dels principals desafiaments a que s'enfronten les autoritats aeroportuàries, els proveïdors de serveis per a la navegació aèria i els operadors de les aeronaus. A part de millorar l'aerodinàmica o les emissions sonores de les aeronaus, l'impacte acústic de les seves operacions es pot reduir també gràcies a la definició de nous procediments de vol més òptims. Aquests procediments s'anomenen generalment Procediments d'Atenuació de Soroll (PAS) i poden incloure rutes preferencials de vol (a fi d'evitar les zones poblades) i també perfils de vol verticals optimitzats. Els procediments actuals per a la reducció de soroll estan molt lluny de ser els òptims. En general, la seva optimització no és possible a causa de les limitacions d'avui en dia en els mètodes de navegació, els equips d'aviònica i la complexitat present en alguns espais aeris. D'altra banda, molts PAS s'han dissenyat de forma manual per un grup d'experts i amb l'ajuda de diverses iteracions. Tot i això, en els propers anys s'esperen nous sistemes d'aviònica i conceptes de gestió del trànsit aeri que permetin millorar el disseny d'aquests procediments, fent que siguin més flexibles. En els pocs casos on s'optimitzen PAS, se sol utilitzar una mètrica acústica en l'elaboració de les diferents funcions objectiu i per tant, no es tenen en compte les molèsties sonores reals. La molèstia és un concepte subjectiu, complexe i que depèn del context en que s'usa i la seva integració en l'optimització de trajectòries segueix essent un aspecte a estudiar.La present tesi doctoral es basa en el fet que en el futur serà possible definir trajectòries més flexibles i precises. D'aquesta manera es permetrà la definició de procediments de vol òptims des d'un punt de vista de molèsties acústiques. Així doncs, es considera una situació en que aquest tipus de procediments poden ser dissenyats de forma automàtica o semi-automàtica per un sistema expert basat en tècniques d'optimització i de raonament aproximat. Això serviria com una eina de presa de decisions per planificadors de l'espai aeri i dissenyadors de procediments. En aquest treball es desenvolupa una eina completa pel càlcul de PAS òptims. Això inclou un conjunt de models no lineals que tinguin en compte la dinàmica de les aeronaus, les limitacions de la trajectòria i les funcions objectiu. La molèstia del soroll es modela utilitzant tècniques de lògica difusa en funció del nivell màxim de so percebut, l'hora del dia i el tipus de zona a sobrevolar. Llavors, s'identifica i es formula formalment el problema com a un problema de control òptim multi-criteri. Per resoldre'l es proposa un mètode de transcripció directa per tal de transformar-lo en un problema de programació no lineal. A continuació s'avaluen una sèrie de tècniques d'optimització multi-objectiu i entre elles es destaca el mètode d'escalarització, el més utilitzat en la literatura. No obstant això, s'exploren diverses tècniques alternatives que permeten superar certs inconvenients que l'escalarització presenta. En aquest context, es presenten i proven tècniques d'optimització lexicogràfica, jeràrquica, igualitària (o min-max) i per objectius. D'aquest anàlisi es desprenen certes conclusions que permeten aprofitar les millors característiques de cada tècnica i formar finalment una tècnica composta d'optimització multi-objectiu. Aquesta última estratègia s'aplica amb èxit a un escenari real i complex, on s'optimitzen les sortides cap a l'Est de la pista 02 de l'aeroport de Girona. En aquest exemple, dos tipus diferents d'aeronaus volant a diferents períodes del dia són simulats obtenint, conseqüentment, diferents trajectòries òptimes.Aunque en las últimas décadas la reducción del ruido emitido por los aviones ha sido sustancial, su impacto en la población ubicada cerca de los aeropuertos es un problema persistente. Contener este ruido, asumiendo al mismo tiempo la creciente demanda de vuelos, es uno de los principales desafíos a que se enfrentan las autoridades aeroportuarias, los proveedores de servicios para la navegación y los operadores. Aparte de mejorar la aerodinámica o las emisiones sonoras de las aeronaves, su impacto acústico se puede reducir también gracias a la definición de nuevos procedimientos de vuelo optimizados. Éstos, se denominan generalmente Procedimientos de Atenuación de Ruido (PAR) y pueden incluir rutas preferenciales de vuelo (a fin de evitar las zonas pobladas) y también perfiles de vuelo optimizados.Los procedimientos actuales para la reducción de ruido están muy lejos de ser los óptimos. En general, su optimización no es posible debido a las limitaciones de hoy en día en los métodos de navegación, los equipos de aviónica y la complejidad presente en algunos espacios aéreos. Por otra parte, muchos PAR se han diseñado de forma manual por un grupo de expertos y con la ayuda de varias iteraciones. Sin embargo, en los próximos años se esperan nuevos sistemas de aviónica y conceptos de gestión del tráfico aéreo que permitan mejorar el diseño de estos procedimientos, haciendo que sean más flexibles. En los pocos casos donde se optimizan PAR, se suele utilizar una métrica acústica en la elaboración de las diferentes funciones objetivo y por lo tanto, no se tienen en cuenta las molestias sonoras reales. La molestia es un concepto subjetivo, complejo y que depende del contexto en que se usa y su integración en la optimización de trayectorias sigue siendo un aspecto a estudiar. La presente tesis doctoral se basa en el hecho de que en el futuro será posible definir trayectorias más flexibles y precisas. De esta manera se permitirá la definición de procedimientos de vuelo óptimos desde un punto de vista de molestias acústicas. Se considera una situación en que este tipo de procedimientos pueden ser diseñados de forma automática o semi-automática por un sistema experto basado en técnicas de optimización y de razonamiento aproximado. Esto serviría como una herramienta de toma de decisiones para planificadores del espacio aéreo y diseñadores de procedimientos.En este trabajo se desarrolla una herramienta completa para el cálculo de PAR óptimos. Esto incluye un conjunto de modelos no lineales que tengan en cuenta la dinámica de las aeronaves, las limitaciones de la trayectoria y las funciones objetivo. La molestia del ruido se modela utilizando técnicas de lógica difusa en función del nivel máximo de sonido percibido, la hora del día y el tipo de zona a sobrevolar. Entonces, se identifica y se formula formalmente el problema como un problema de control óptimo multi-criterio. Para resolverlo se propone un método de transcripción directa para transformarlo en un problema de programación no lineal. A continuación se evalúan una serie de técnicas de optimización multi-objetivo y entre ellas se destaca el método de escalarización, el más utilizado en la literatura. Sin embargo, se exploran diversas técnicas alternativas que permiten superar ciertos inconvenientes que la escalarización presenta. En este contexto, se presentan y prueban técnicas de optimización lexicográfica, jerárquica, igualitaria (o min-max) y por objetivos. De este análisis se desprenden ciertas conclusiones que permiten aprovechar las mejores características de cada técnica y formar finalmente una técnica compuesta de optimización multi-objetivo. Esta última estrategia se aplica con éxito en un escenario real y complejo, donde se optimizan las salidas hacia el Este de la pista 02 del aeropuerto de Girona. En este ejemplo, dos tipos diferentes de aeronaves volando a diferentes periodos del día son simulados obteniendo, consecuentemente, diferentes trayectorias óptimas.Despite the substantial reduction of the emitted aircraft noise in the last decades, the noise impact on communities located near airports is a problem that still lingers. Containing the sound generated by aircraft operations, while meeting the increasing demand for aircraft transportation, is one of the major challenges that airport authorities, air traffic service providers and aircraft operators may deal with. Aircraft noise can be reduced by improving the aerodynamics of the aircraft, the engine noise emissions but also in designing new optimised flight procedures. These procedures, are generally called Noise Abatement Procedures (NAP) and may include preferential routings (in order to avoid populated areas) and also schedule optimised vertical flight path profiles. Present noise abatement procedures are far from being optimal in regards to minimising noise nuisances. In general, their optimisation is not possible due to the limitations of navigation methods, current avionic equipments and the complexity present at some terminal airspaces. Moreover, NAP are often designed manually by a group of experts and several iterations are needed. However, in the forthcoming years, new avionic systems and new Air Traffic Management concepts are expected to significantly improve the design of flight procedures. This will make them more flexible, and therefore will allow them to be more environmental friendly. Furthermore, in the few cases where NAP are optimised, an acoustical metric is usually used when building up the different optimisation functions. Therefore, the actual noise annoyance is not taken into account in the optimisation process. The annoyance is a subjective, complex and context-dependent concept. Even if sophisticated noise annoyance models are already available today, their integration into an trajectory optimisation framework is still something to be further explored. This dissertation is mainly focused on the fact that those precise and more flexible trajectories will enable the definition of optimal flight procedures regarding the noise annoyance impact, especially in the arrival and departure phases of flights. In addition, one can conceive a situation where these kinds of procedures can be designed automatically or semi-automatically by an expert system, based on optimisation techniques and approximate reasoning. This would serve as a decision making tool for airspace planners and procedure designers.A complete framework for computing optimal NAP is developed in this work. This includes a set of nonlinear models which take into account aircraft dynamics, trajectory constraints and objective functions. The noise annoyance is modelled by using fuzzy logic techniques in function of the perceived maximum sound level, the hour of the day and the type of over-flown zone. The problem tackled, formally identified and formulated as a multi-criteria optimal control problem, uses a direct transcription method to transform it into a Non Linear Programming problem. Then, an assessment of different multi-objective optimisation techniques is presented. Among these techniques, scalarisation methods are identified as the most widely used methodologies in the present day literature. Yet, in this dissertation several alternative techniques are explored in order to overcome some known drawbacks of this technique. In this context, lexicographic, hierarchical, egalitarian (or min-max) and goal optimisation strategies are presented and tested. From this analysis some conclusions arise allowing us to take advantage of the best features of each optimisation technique aimed at building a final compound multi-objective optimisation strategy. Finally, this strategy is applied successfully to a complex and real scenario, where the East departures of runway 02 at the airport of Girona (Catalonia, Spain) are optimised. Two aircraft types are simulated at different periods of the day obtaining different optimal trajectories.Postprint (published version

Modelo basado en sistema multi-agente para distribución de ayuda en especie en logística humanitaria

Objetivos y método de estudio: ´ En esta tesis se aborda el problema de ruteo de vehículos a través de un Sistema Multi-Agente para la distribución de ayuda en especie en las actividades de logística humanitaria. El objetivo de la logística humanitaria es satisfacer las necesidades de las personas afectadas por un desastre lo más rápido posible. Esto incluye proveer de soporte, servicios, materiales, productos, y transporte a los involucrados en la asistencia a los damnificados. El objetivo general de la tesis consistió en desarrollar un modelo para el ruteo de vehículos con agentes para distribución de ayuda en logística humanitaria. La metodología utilizada consistió en programar el modelo con Sistemas MultiAgentes basado en la arquitectura BDI (Belief-Desire-Intention) implementado bajo el lenguaje de programación Java en el entorno de programación eclipse y con la herramienta para Sistemas Multi-Agentes JASON. El modelo desarrollado se aplicó a un caso de estudio para sismos que pudieran ocurrir en la Ciudad de México, donde se clasificaron dos zonas en caso de temblores, la primera de bajo riesgo y la segunda de alto de riesgo. La selección de la muestra se generó de manera aleatoria con escenarios que simularon características reales del desastre en base al caso de estudio aplicado. Se diseñaron dos experimentos, el primero del Sistema Multi-Agente y el segundo de un Sistema Mono-Agente para comparar las soluciones a los casos de evaluación propuestos: el impacto de los agentes en la distribución de ayuda humanitaria y la del impacto de la demanda en los agentes en la distribución de ayuda. Contribuciones y conclusiones: Se propone un modelo implementado en un prototipo de simulación que permite evaluar escenarios de logística humanitaria dada una flotilla de vehículos, ubicados en un centro de distribución y con características homogéneas . El modelo está basado en agentes aumentados con algoritmos tradicionales de VRP (Vehicle Routing Problem) que representan el problema de logística humanitaria y obtienen soluciones al mismo. El modelo se evaluó considerando el costo de las soluciones, tomando en cuenta cantidad de agentes y demanda variable. El estudio aporta un nuevo modelo basado en agentes para distribución de ayuda humanitaria. Dicho modelo planifica la ruta haciendo uso de agentes que distribuyen artículos de primera necesidad a través de un grafo. El modelo contribuye a la toma de decisiones en logística humanitaria y se comprobó que un Sistema MultiAgente (SMA) resulta más eficiente que un Sistema Mono-Agente en el trabajo distribuid

Salford postgraduate annual research conference (SPARC) 2012 proceedings

These proceedings bring together a selection of papers from the 2012 Salford Postgraduate Annual Research Conference (SPARC). They reflect the breadth and diversity of research interests showcased at the conference, at which over 130 researchers from Salford, the North West and other UK universities presented their work. 21 papers are collated here from the humanities, arts, social sciences, health, engineering, environment and life sciences, built environment and business

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

Support in decision-making under uncertainty: a project risk assessment tool development and supplementary advances

A foremost dispute that persists on the contemporary world’s agenda is change. The on-going social/technological/economic changes create a competitive and challenging environment for companies to endure. To benefit from these changes, world economies partially depend on emerging Small and Medium Enterprises (SMEs) and their adaptability skills, and subsequently the development of an integrated capability to innovate has become the prime strategy for most of SMEs to subsist and grow. However, innovation and change are always somewhat bonded to an inherent risk development, which subsequently brings on the necessity of a revision of risk management approaches in innovative processes, whose importance SMEs tend to disregard. Additionally, little efforts have been made to improve and create empirical models, metrics and tools to assist SMEs managing latent risks in their innovative projects. This work seeks to present and discuss a solution to support SMEs in engaging on systematic risk management practices, which consists on an integrated risk assessment and response support web-based tool - Spotrisk® - designed for SMEs. On the other hand, an inherent subjectivity is linked with risk management and identification processes, due to uncertainty trait of its nature, for each individual perceives situations according to his own idiosyncrasy, which brings complications in normalizing risk profiles and procedures. This essay aims to bring insights concerning the support in decision-making processes under uncertainty, by addressing issues related with the risk behavior character among individuals. To address such issues, subjects of neuroscience or psychology are explored and models to identify such character are proposed, as well as models to improve presented tool. This work attempts to go beyond the restrictive aim of endeavoring on technical improvement dissertation, and in embraces an exploratory conceptualization concerning micro, small and medium businesses’ traits regarding risk characters and project risk assessment tools

Renewable Energies for Sustainable Development

In the current scenario in which climate change dominates our lives and in which we all need to combat and drastically reduce the emission of greenhouse gases, renewable energies play key roles as present and future energy sources. Renewable energies vary across a wide range, and therefore, there are related studies for each type of energy. This Special Issue is composed of studies integrating the latest research innovations and knowledge focused on all types of renewable energy: onshore and offshore wind, photovoltaic, solar, biomass, geothermal, waves, tides, hydro, etc. Authors were invited submit review and research papers focused on energy resource estimation, all types of TRL converters, civil infrastructure, electrical connection, environmental studies, licensing and development of facilities, construction, operation and maintenance, mechanical and structural analysis, new materials for these facilities, etc. Analyses of a combination of several renewable energies as well as storage systems to progress the development of these sustainable energies were welcomed