IDRA (IDeal Resource Allocation): Computing ideal speedups in parallel logic programming

We present a technique to estimate accurate speedups for parallel logic programs with relative independence from characteristics of a given implementation or underlying parallel hardware. The proposed technique is based on gathering accurate data describing one execution at run-time, which is fed to a simulator. Alternative schedulings are then simulated and estimates computed for the corresponding speedups. A tool implementing the aforementioned techniques is presented, and its predictions are compared to the performance of real systems, showing good correlation.

IDRA (IDeal Resource Allocation): A tool for computing ideal speedups

Performance studies of actual parallel systems usually tend to concéntrate on the effectiveness of a given implementation. This is often done in the absolute, without quantitave reference to the potential parallelism contained in the programs from the point of view of the execution paradigm. We feel that studying the parallelism inherent to the programs is interesting, as it gives information about the best possible behavior of any implementation and thus allows contrasting the results obtained. We propose a method for obtaining ideal speedups for programs through a combination of sequential or parallel execution and simulation, and the algorithms that allow implementing the method. Our approach is novel and, we argüe, more accurate than previously proposed methods, in that a crucial part of the data - the execution times of tasks - is obtained from actual executions, while speedup is computed by simulation. This allows obtaining speedup (and other) data under controlled and ideal assumptions regarding issues such as number of processor, scheduling algorithm and overheads, etc. The results obtained can be used for example to evalúate the ideal parallelism that a program contains for a given model of execution and to compare such "perfect" parallelism to that obtained by a given implementation of that model. We also present a tool, IDRA, which implements the proposed method, and results obtained with IDRA for benchmark programs, which are then compared with those obtained in actual executions on real parallel systems.

Resource allocation in GMD and SVD-based MIMO System

Singular-value decomposition (SVD)-based multiple-input multiple output (MIMO) systems, where the whole MIMO channel is decomposed into a number of unequally weighted single-input single-output (SISO) channels, have attracted a lot of attention in the wireless community. The unequal weighting of the SISO channels has led to intensive research on bit- and power allocation even in MIMO channel situation with poor scattering conditions identified as the antennas correlation effect. In this situation, the unequal weighting of the SISO channels becomes even much stronger. In comparison to the SVD-assisted MIMO transmission, geometric mean decomposition (GMD)-based MIMO systems are able to compensate the drawback of weighted SISO channels when using SVD, where the decomposition result is nearly independent of the antennas correlation effect. The remaining interferences after the GMD-based signal processing can be easily removed by using dirty paper precoding as demonstrated in this work. Our results show that GMD-based MIMO transmission has the potential to significantly simplify the bit and power loading processes and outperforms the SVD-based MIMO transmission as long as the same QAM-constellation size is used on all equally-weighted SISO channels.

Optimizing the reliability and resource efficiency of MapReduce-based systems

Debido al gran incremento de datos digitales que ha tenido lugar en los últimos años, ha surgido un nuevo paradigma de computación paralela para el procesamiento eficiente de grandes volúmenes de datos. Muchos de los sistemas basados en este paradigma, también llamados sistemas de computación intensiva de datos, siguen el modelo de programación de Google MapReduce. La principal ventaja de los sistemas MapReduce es que se basan en la idea de enviar la computación donde residen los datos, tratando de proporcionar escalabilidad y eficiencia. En escenarios libres de fallo, estos sistemas generalmente logran buenos resultados. Sin embargo, la mayoría de escenarios donde se utilizan, se caracterizan por la existencia de fallos. Por tanto, estas plataformas suelen incorporar características de tolerancia a fallos y fiabilidad. Por otro lado, es reconocido que las mejoras en confiabilidad vienen asociadas a costes adicionales en recursos. Esto es razonable y los proveedores que ofrecen este tipo de infraestructuras son conscientes de ello. No obstante, no todos los enfoques proporcionan la misma solución de compromiso entre las capacidades de tolerancia a fallo (o de manera general, las capacidades de fiabilidad) y su coste. Esta tesis ha tratado la problemática de la coexistencia entre fiabilidad y eficiencia de los recursos en los sistemas basados en el paradigma MapReduce, a través de metodologías que introducen el mínimo coste, garantizando un nivel adecuado de fiabilidad. Para lograr esto, se ha propuesto: (i) la formalización de una abstracción de detección de fallos; (ii) una solución alternativa a los puntos únicos de fallo de estas plataformas, y, finalmente, (iii) un nuevo sistema de asignación de recursos basado en retroalimentación a nivel de contenedores. Estas contribuciones genéricas han sido evaluadas tomando como referencia la arquitectura Hadoop YARN, que, hoy en día, es la plataforma de referencia en la comunidad de los sistemas de computación intensiva de datos. En la tesis se demuestra cómo todas las contribuciones de la misma superan a Hadoop YARN tanto en fiabilidad como en eficiencia de los recursos utilizados. ABSTRACT Due to the increase of huge data volumes, a new parallel computing paradigm to process big data in an efficient way has arisen. Many of these systems, called dataintensive computing systems, follow the Google MapReduce programming model. The main advantage of these systems is based on the idea of sending the computation where the data resides, trying to provide scalability and efficiency. In failure-free scenarios, these frameworks usually achieve good results. However, these ones are not realistic scenarios. Consequently, these frameworks exhibit some fault tolerance and dependability techniques as built-in features. On the other hand, dependability improvements are known to imply additional resource costs. This is reasonable and providers offering these infrastructures are aware of this. Nevertheless, not all the approaches provide the same tradeoff between fault tolerant capabilities (or more generally, reliability capabilities) and cost. In this thesis, we have addressed the coexistence between reliability and resource efficiency in MapReduce-based systems, looking for methodologies that introduce the minimal cost and guarantee an appropriate level of reliability. In order to achieve this, we have proposed: (i) a formalization of a failure detector abstraction; (ii) an alternative solution to single points of failure of these frameworks, and finally (iii) a novel feedback-based resource allocation system at the container level. Finally, our generic contributions have been instantiated for the Hadoop YARN architecture, which is the state-of-the-art framework in the data-intensive computing systems community nowadays. The thesis demonstrates how all our approaches outperform Hadoop YARN in terms of reliability and resource efficiency.

Communication Middleware for Distributed Hard Real-Time Systems in Java

Distributed real-time embedded systems are becoming increasingly important to society. More demands will be made on them and greater reliance will be placed on the delivery of their services. A relevant subset of them is high-integrity or hard real-time systems, where failure can cause loss of life, environmental harm, or significant financial loss. Additionally, the evolution of communication networks and paradigms as well as the necessity of demanding processing power and fault tolerance, motivated the interconnection between electronic devices; many of the communications have the possibility of transferring data at a high speed. The concept of distributed systems emerged as systems where different parts are executed on several nodes that interact with each other via a communication network. Java’s popularity, facilities and platform independence have made it an interesting language for the real-time and embedded community. This was the motivation for the development of RTSJ (Real-Time Specification for Java), which is a language extension intended to allow the development of real-time systems. The use of Java in the development of high-integrity systems requires strict development and testing techniques. However, RTJS includes a number of language features that are forbidden in such systems. In the context of the HIJA project, the HRTJ (Hard Real-Time Java) profile was developed to define a robust subset of the language that is amenable to static analysis for high-integrity system certification. Currently, a specification under the Java community process (JSR- 302) is being developed. Its purpose is to define those capabilities needed to create safety critical applications with Java technology called Safety Critical Java (SCJ). However, neither RTSJ nor its profiles provide facilities to develop distributed realtime applications. This is an important issue, as most of the current and future systems will be distributed. The Distributed RTSJ (DRTSJ) Expert Group was created under the Java community process (JSR-50) in order to define appropriate abstractions to overcome this problem. Currently there is no formal specification. The aim of this thesis is to develop a communication middleware that is suitable for the development of distributed hard real-time systems in Java, based on the integration between the RMI (Remote Method Invocation) model and the HRTJ profile. It has been designed and implemented keeping in mind the main requirements such as the predictability and reliability in the timing behavior and the resource usage. iThe design starts with the definition of a computational model which identifies among other things: the communication model, most appropriate underlying network protocols, the analysis model, and a subset of Java for hard real-time systems. In the design, the remote references are the basic means for building distributed applications which are associated with all non-functional parameters and resources needed to implement synchronous or asynchronous remote invocations with real-time attributes. The proposed middleware separates the resource allocation from the execution itself by defining two phases and a specific threading mechanism that guarantees a suitable timing behavior. It also includes mechanisms to monitor the functional and the timing behavior. It provides independence from network protocol defining a network interface and modules. The JRMP protocol was modified to include two phases, non-functional parameters, and message size optimizations. Although serialization is one of the fundamental operations to ensure proper data transmission, current implementations are not suitable for hard real-time systems and there are no alternatives. This thesis proposes a predictable serialization that introduces a new compiler to generate optimized code according to the computational model. The proposed solution has the advantage of allowing us to schedule the communications and to adjust the memory usage at compilation time. In order to validate the design and the implementation a demanding validation process was carried out with emphasis in the functional behavior, the memory usage, the processor usage (the end-to-end response time and the response time in each functional block) and the network usage (real consumption according to the calculated consumption). The results obtained in an industrial application developed by Thales Avionics (a Flight Management System) and in exhaustive tests show that the design and the prototype are reliable for industrial applications with strict timing requirements. Los sistemas empotrados y distribuidos de tiempo real son cada vez más importantes para la sociedad. Su demanda aumenta y cada vez más dependemos de los servicios que proporcionan. Los sistemas de alta integridad constituyen un subconjunto de gran importancia. Se caracterizan por que un fallo en su funcionamiento puede causar pérdida de vidas humanas, daños en el medio ambiente o cuantiosas pérdidas económicas. La necesidad de satisfacer requisitos temporales estrictos, hace más complejo su desarrollo. Mientras que los sistemas empotrados se sigan expandiendo en nuestra sociedad, es necesario garantizar un coste de desarrollo ajustado mediante el uso técnicas adecuadas en su diseño, mantenimiento y certificación. En concreto, se requiere una tecnología flexible e independiente del hardware. La evolución de las redes y paradigmas de comunicación, así como la necesidad de mayor potencia de cómputo y de tolerancia a fallos, ha motivado la interconexión de dispositivos electrónicos. Los mecanismos de comunicación permiten la transferencia de datos con alta velocidad de transmisión. En este contexto, el concepto de sistema distribuido ha emergido como sistemas donde sus componentes se ejecutan en varios nodos en paralelo y que interactúan entre ellos mediante redes de comunicaciones. Un concepto interesante son los sistemas de tiempo real neutrales respecto a la plataforma de ejecución. Se caracterizan por la falta de conocimiento de esta plataforma durante su diseño. Esta propiedad es relevante, por que conviene que se ejecuten en la mayor variedad de arquitecturas, tienen una vida media mayor de diez anos y el lugar ˜ donde se ejecutan puede variar. El lenguaje de programación Java es una buena base para el desarrollo de este tipo de sistemas. Por este motivo se ha creado RTSJ (Real-Time Specification for Java), que es una extensión del lenguaje para permitir el desarrollo de sistemas de tiempo real. Sin embargo, RTSJ no proporciona facilidades para el desarrollo de aplicaciones distribuidas de tiempo real. Es una limitación importante dado que la mayoría de los actuales y futuros sistemas serán distribuidos. El grupo DRTSJ (DistributedRTSJ) fue creado bajo el proceso de la comunidad de Java (JSR-50) con el fin de definir las abstracciones que aborden dicha limitación, pero en la actualidad aun no existe una especificacion formal. El objetivo de esta tesis es desarrollar un middleware de comunicaciones para el desarrollo de sistemas distribuidos de tiempo real en Java, basado en la integración entre el modelo de RMI (Remote Method Invocation) y el perfil HRTJ. Ha sido diseñado e implementado teniendo en cuenta los requisitos principales, como la predecibilidad y la confiabilidad del comportamiento temporal y el uso de recursos. El diseño parte de la definición de un modelo computacional el cual identifica entre otras cosas: el modelo de comunicaciones, los protocolos de red subyacentes más adecuados, el modelo de análisis, y un subconjunto de Java para sistemas de tiempo real crítico. En el diseño, las referencias remotas son el medio básico para construcción de aplicaciones distribuidas las cuales son asociadas a todos los parámetros no funcionales y los recursos necesarios para la ejecución de invocaciones remotas síncronas o asíncronas con atributos de tiempo real. El middleware propuesto separa la asignación de recursos de la propia ejecución definiendo dos fases y un mecanismo de hebras especifico que garantiza un comportamiento temporal adecuado. Además se ha incluido mecanismos para supervisar el comportamiento funcional y temporal. Se ha buscado independencia del protocolo de red definiendo una interfaz de red y módulos específicos. También se ha modificado el protocolo JRMP para incluir diferentes fases, parámetros no funcionales y optimizaciones de los tamaños de los mensajes. Aunque la serialización es una de las operaciones fundamentales para asegurar la adecuada transmisión de datos, las actuales implementaciones no son adecuadas para sistemas críticos y no hay alternativas. Este trabajo propone una serialización predecible que ha implicado el desarrollo de un nuevo compilador para la generación de código optimizado acorde al modelo computacional. La solución propuesta tiene la ventaja que en tiempo de compilación nos permite planificar las comunicaciones y ajustar el uso de memoria. Con el objetivo de validar el diseño e implementación se ha llevado a cabo un exigente proceso de validación con énfasis en: el comportamiento funcional, el uso de memoria, el uso del procesador (tiempo de respuesta de extremo a extremo y en cada uno de los bloques funcionales) y el uso de la red (consumo real conforme al estimado). Los buenos resultados obtenidos en una aplicación industrial desarrollada por Thales Avionics (un sistema de gestión de vuelo) y en las pruebas exhaustivas han demostrado que el diseño y el prototipo son fiables para aplicaciones industriales con estrictos requisitos temporales.

Bio-inspired FPGA Architecture for Self-Calibration of an Image Compression Core based on Wavelet Transforms in Embedded Systems

A generic bio-inspired adaptive architecture for image compression suitable to be implemented in embedded systems is presented. The architecture allows the system to be tuned during its calibration phase. An evolutionary algorithm is responsible of making the system evolve towards the required performance. A prototype has been implemented in a Xilinx Virtex-5 FPGA featuring an adaptive wavelet transform core directed at improving image compression for specific types of images. An Evolution Strategy has been chosen as the search algorithm and its typical genetic operators adapted to allow for a hardware friendly implementation. HW/SW partitioning issues are also considered after a high level description of the algorithm is profiled which validates the proposed resource allocation in the device fabric. To check the robustness of the system and its adaptation capabilities, different types of images have been selected as validation patterns. A direct application of such a system is its deployment in an unknown environment during design time, letting the calibration phase adjust the system parameters so that it performs efcient image compression. Also, this prototype implementation may serve as an accelerator for the automatic design of evolved transform coefficients which are later on synthesized and implemented in a non-adaptive system in the final implementation device, whether it is a HW or SW based computing device. The architecture has been built in a modular way so that it can be easily extended to adapt other types of image processing cores. Details on this pluggable component point of view are also given in the paper.

CP debugging needs and tools

Conventional programming techniques are not well suited for solving many highly combinatorial industrial problems, like scheduling, decision making, resource allocation or planning. Constraint Programming (CP), an emerging software technology, offers an original approach allowing for efficient and flexible solving of complex problems, through combined implementation of various constraint solvers and expert heuristics. Its applications are increasingly elded in various industries.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

Approaches Regarding the Competition in Romanian Sugar Market

This paper proposes an economic instrument designed to assess the competitive nature of the sugar industry in Romania. In the first part of the paper is presented the theoretical background underlying index (HHI) and its calculation methodology. Then comes the results of a first application of this index for a total of 10 plants in the sugar industry, the robustness of these results is discussed. We believe HHI is a proactive tool that may prove useful competition authority, in its pursuit of continuous monitoring of various industries in the economy and in the internal decision-making on resource allocation institution (Peacock, and Prisecaru, 2013).The starting point of our research is to free competition in the European market with competitors much stronger than Romanian plants, plants that produce at a price lower than the domestic ones. In our study we will see if it is a concentration of production in factories around the strongest in Romania, concentration accompanied by the collapse of those who could not resist the market.The market concentration, competition policy, we will follow using the HHI index, for evaluation of impact analysis on existing trade, the number and size of competitors, protecting existing sales structures, avoiding disruptions in the competitive environment, etc.

Optimal water allocation in shortage situations as applied to an irrigation community.

This work studies the most beneficial way of allocating water in an irrigation community in water shortage situations. Therefore, it proposes that the irrigation surface area be divided into homogeneous zones, each with a beneficial relationship with respect to the water applied. The mathematical formula that enables one to obtain the optimal quota for the users or irrigation community as a whole has been found for individual relations of a quadratic or power type, and these have yielded different and complementary characteristics. Dimensionless variables have been used to display the results, and to compare with other alternative allocation rules such as the proportional rule, referencing the situation without water restrictions. As a result, for each water shortage situation, the water that is allocated to each user is obtained, together with the losses in individual income and the losses for the community as a whole. Furthermore, a proposal is put forth for establishing the marginal benefit from the water available, which could be of interest in enabling each community to analyze whether it is in its best interest to invest in increasing the resource, or to sell the resource to other users. Finally, an example is given to demonstrate how the method works and to show that, when the differences between the production schemes are considered, the differences in benefit reduction between the proportional allocation and the optimal allocation are also sizeable. Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)IR.1943-4774.0000667

The optimal allocation rule and the water market as the most effective tools of managing water shortage in an irrigation district

The conference program will cover all areas of environmental and resource economics, ranging from topics prevailing in the general debate, such as climate change, energy sources, water management and ecosystem services evaluation, to more specialized subjects such as biodiversity conservation or persistent organic pollutants. The congress will be held on the Faculty of Economics of the University of Girona, located in Montilivi, a city quarter situated just few minutes from the city center, conveniently connected by bus lines L8 and L11.