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Cloud Systems and HPC As a Service of Agroindustry Cloud systems and HPC as a service of agroindustry Jordi Mateo Fornés http://hdl.handle.net/10803/667343 ADVERTIMENT. L'accés als continguts d'aquesta tesi doctoral i la seva utilització ha de respectar els drets de la persona autora. Pot ser utilitzada per a consulta o estudi personal, així com en activitats o materials d'investigació i docència en els termes establerts a l'art. 32 del Text Refós de la Llei de Propietat Intel·lectual (RDL 1/1996). Per altres utilitzacions es requereix l'autorització prèvia i expressa de la persona autora. En qualsevol cas, en la utilització dels seus continguts caldrà indicar de forma clara el nom i cognoms de la persona autora i el títol de la tesi doctoral. No s'autoritza la seva reproducció o altres formes d'explotació efectuades amb finalitats de lucre ni la seva comunicació pública des d'un lloc aliè al servei TDX. Tampoc s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant als continguts de la tesi com als seus resums i índexs. ADVERTENCIA. El acceso a los contenidos de esta tesis doctoral y su utilización debe respetar los derechos de la persona autora. Puede ser utilizada para consulta o estudio personal, así como en actividades o materiales de investigación y docencia en los términos establecidos en el art. 32 del Texto Refundido de la Ley de Propiedad Intelectual (RDL 1/1996). Para otros usos se requiere la autorización previa y expresa de la persona autora. En cualquier caso, en la utilización de sus contenidos se deberá indicar de forma clara el nombre y apellidos de la persona autora y el título de la tesis doctoral. No se autoriza su reproducción u otras formas de explotación efectuadas con fines lucrativos ni su comunicación pública desde un sitio ajeno al servicio TDR. Tampoco se autoriza la presentación de su contenido en una ventana o marco ajeno a TDR (framing). Esta reserva de derechos afecta tanto al contenido de la tesis como a sus resúmenes e índices. WARNING. Access to the contents of this doctoral thesis and its use must respect the rights of the author. It can be used for reference or private study, as well as research and learning activities or materials in the terms established by the 32nd article of the Spanish Consolidated Copyright Act (RDL 1/1996). Express and previous authorization of the author is required for any other uses. In any case, when using its content, full name of the author and title of the thesis must be clearly indicated. Reproduction or other forms of for profit use or public communication from outside TDX service is not allowed. Presentation of its content in a window or frame external to TDX (framing) is not authorized either. These rights affect both the content of the thesis and its abstracts and indexes. TESI DOCTORAL Cloud systems and HPC as a service of agroindustry Jordi Mateo Fornés Memòria presentada per optar al grau de Doctor per la Universitat de Lleida Programa de Doctorat en Enginyeria i Tecnologies de la Informació. Director/a Francesc Solsona Tehàs Lluís M. Plà Aragonès 2019 Begin at the beginning, the King said gravely, and go on till you come to the end: then stop Alice in Wonderland To you as a reader. ABSTRACT Background: Cloud computing is a new paradigm that opens a flexible and financial attractive door for business and consumers. In recent years, cloud services have reshaped the way business models are planned, saving costs and improving efficiency. There is an exponential growth of cloud solutions available in the public and private sector. This way, cloud services are based on a pay- per-use model, offering resources and service through the Internet. Moreover, the cloud architectures provide many advantages concerning scalability, main- tainability and massive data processing. High Performance Computing (HPC) decomposition methods and Operation Research (OR) models integration inside the cloud brings the opportunity to improve the performance and the quality of the cloud services. There are infinite opportunities and challenges for ex- ploiting the capabilities of Decision Support Systems (DSS) inside the cloud. The agribusiness sector can significantly be boost by the consideration of these possibilities. Methods: Queuing theory and nonlinear programming were combined to model cloud architectures and to develop trade-off policies considering different metrics and ensuring a certain level of quality of service. OR decomposition methods (Benders Decomposition and Lagrangian Decomposition) are improved using HPC paradigms. Cloud services, OR methods and decision support systems are integrated to deliver knowledge from academia to society. Two-stage sStochas- tic programming was selected to enhance the decision-making process in the agribusiness field. Finally, two different agribusiness applications were designed, deployed and tested on a real cloud platform. Results: This thesis explores methods, mathematical models and algorithms for managing cloud systems cost-effectively. Furthermore, this thesis analyses how to export and deliver this knowledge to society; in particular to the agribusiness field. The primary purpose is to assist decision-makers in their daily activity. The main results of this thesis highlight the future guidelines to build smart decision support systems combining HPC, OR and cloud platforms. The out- comes corroborate the benefits of applying parallel computing to decomposition methods to deal with stochastic models. Moreover, the results show the advan- tages of mixing cloud platforms and optimisation field offering optimisation as a service to the overall community. Furthermore, the results demonstrate that considering uncertainty and stochastic programming costs can be reduced in v agribusiness supply chains. Besides, the results show that cloud DSS’s improve the decision-making process, overcoming the current barriers. It presents a cloud application to assist pig farmers in the optimal replacement of sows. Conclusions: Several cloud models and policies were analysed and implemented using different methods and techniques. The results yielded by this thesis pro- vide strong evidence that parallel decomposition methods, such as Lagrangian Decomposition and Benders Decomposition can beat commercial solvers such as CPLEX when dealing with the optimal resolution of real-life stochastic in- stances. SPOS shows how to orchestrate cloud platforms to deliver knowledge as a service while integrating mathematical solvers in a cloud environment. In a more agroindustrial context, the stochastic model designed around the Chilean dried apple supply chain proof a cost reduction by considering uncertain up to a 6.4%. Finally, a cloud DSS was successfully developed and implemented to assist sow farmers. All the results extracted from this thesis are an essential seed for modelling a much bigger service, with great potential to become a reference in the design of cloud DSS offering all users the possibility of solving any problem, even stochastic models, and also of obtaining detailed and custom results. vi RESUM Introducció: La computació al núvol és un nou paradigma que obra un uni- vers de possibilitats en el món dels negocis i als consumidors de serveis. En els darrers anys, els serveis basats en núvol han reconfigurat la manera en què es planeja el model de negoci, estalviant costos i millorant l’eficiència. Actu- alment, hi ha un creixement exponencial de les solucions disponibles basades en el núvol al sector públic i privat. D’aquesta manera, els serveis basats en núvol es basen en un model de pagament per ús, que ofereix recursos i serveis a través d’Internet. A més a més, les arquitectures del sistema basades en núvol proporcionen molts avantatges en quant a l’escalabilitat de recursos, la sosteni- bilitat o el processament massiu de dades. Els mètodes de descomposició per a la resolució de problemes d’optimització, la computació d’altes prestacions per l’acceleració d’aquests mètodes i la seva corresponent integració dins del núvol ofereixen l’oportunitat de millorar el rendiment i la qualitat dels serveis. En el context actual, hi ha infinites oportunitats i reptes per explotar les capacitats dels sistemes de suport a la presa de decisions integrats en el núvol. Les empre- ses del sector agroalimentari poden beneficiar-se molt d’aquests sistemes/serveis per a ser més eficients i competitives. Mètodes: La teoria de cues i la programació no lineal s’han utilitzat com a instrument per a modelar arquitectures basades en el núvol i desenvolupar polí- tiques balancejades tenint en compte diferents mètriques, com la disponibilitat o l’eficiència per garantir un cert nivell de qualitat de servei. La computació d’altes prestacions s’ha utilitzat per millorar el rendiment de les tècniques de descompoció (Benders i Lagrange). Els serveis cloud, els mètodes d’investiga- ció operativa i els sistemes de suport a la presa de decisions s’han integrat per transferir el coneixement des de l’àmbit acadèmic a la societat. La programa- ció estocàstica bietapa s’ha seleccionat per millor les decisions dels agronegocis. Finalment s’ha dissenyat, implementat i provat un servei d’optimització i dues aplicacions d’agronegocis diferents en una plataforma basada en el núvol. Resultats: Aquesta tesi explora mètodes, models matemàtics i algorismes per a una gestió eficient dels sistemes en el núvol. També explora com exportar i lliurar aquest coneixement a la societat, en particular al camp dels agronegocis per millora el procés de presa de decisions. Els principals resultats d’aquesta tesi ressalten les pautes per construir sistemes intel·ligents de suport a la decisió integrats en plataformes en el núvol. Els resultats corroboren els beneficis de vii l’aplicació de la computació d’altes prestacions juntament amb els mètodes de descomposició per tractar models estocàstics. A més a més, els resultats mostren els avantatges de barrejar plataformes en el núvol i els models de programació matemàtica per oferir optimització a la comunitat en general.
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