And-or parallel prolog: a recomputation based approach

We argüe that in order to exploit both Independent And- and Or-parallelism in Prolog programs there is advantage in recomputing some of the independent goals, as opposed to all their solutions being reused. We present an abstract model, called the Composition-Tree, for representing and-or parallelism in Prolog Programs. The Composition-tree closely mirrors sequential Prolog execution by recomputing some independent goals rather than fully re-using them. We also outline two environment representation techniques for And-Or parallel execution of full Prolog based on the Composition-tree model abstraction. We argüe that these techniques have advantages over earlier proposals for exploiting and-or parallelism in Prolog.

Towards execution time estimation in abstract machine-based languages

Abstract machines provide a certain separation between platformdependent and platform-independent concerns in compilation. Many of the differences between architectures are encapsulated in the speciflc abstract machine implementation and the bytecode is left largely architecture independent. Taking advantage of this fact, we present a framework for estimating upper and lower bounds on the execution times of logic programs running on a bytecode-based abstract machine. Our approach includes a one-time, programindependent proflling stage which calculates constants or functions bounding the execution time of each abstract machine instruction. Then, a compile-time cost estimation phase, using the instruction timing information, infers expressions giving platform-dependent upper and lower bounds on actual execution time as functions of input data sizes for each program. Working at the abstract machine level makes it possible to take into account low-level issues in new architectures and platforms by just reexecuting the calibration stage instead of having to tailor the analysis for each architecture and platform. Applications of such predicted execution times include debugging/veriflcation of time properties, certiflcation of time properties in mobile code, granularity control in parallel/distributed computing, and resource-oriented specialization.

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.

A semantic scheduler architecture for federated hybrid clouds

Cloud computing is one the most relevant computing paradigms available nowadays. Its adoption has increased during last years due to the large investment and research from business enterprises and academia institutions. Among all the services cloud providers usually offer, Infrastructure as a Service has reached its momentum for solving HPC problems in a more dynamic way without the need of expensive investments. The integration of a large number of providers is a major goal as it enables the improvement of the quality of the selected resources in terms of pricing, speed, redundancy, etc. In this paper, we propose a system architecture, based on semantic solutions, to build an interoperable scheduler for federated clouds that works with several IaaS (Infrastructure as a Service) providers in a uniform way. Based on this architecture we implement a proof-of-concept prototype and test it with two different cloud solutions to provide some experimental results about the viability of our approach.

Abstract interpretation-based code certification for pervasive systems: Preliminary experiments

Proof carrying code is a general methodology for certifying that the execution of an untrusted mobile code is safe, according to a predefined safety policy. The basic idea is that the code supplier attaches a certifícate (or proof) to the mobile code which, then, the consumer checks in order to ensure that the code is indeed safe. The potential benefit is that the consumer's task is reduced from the level of proving to the level of checking, a much simpler task. Recently, the abstract interpretation techniques developed in logic programming have been proposed as a basis for proof carrying code [1]. To this end, the certifícate is generated from an abstract interpretation-based proof of safety. Intuitively, the verification condition is extracted from a set of assertions guaranteeing safety and the answer table generated during the analysis. Given this information, it is relatively simple and fast to verify that the code does meet this proof and so its execution is safe. This extended abstract reports on experiments which illustrate several issues involved in abstract interpretation-based code certification. First, we describe the implementation of our system in the context of CiaoPP: the preprocessor of the Ciao multi-paradigm (constraint) logic programming system. Then, by means of some experiments, we show how code certification is aided in the implementation of the framework. Finally, we discuss the application of our method within the área of pervasive systems which may lack the necessary computing resources to verify safety on their own. We herein illustrate the relevance of the information inferred by existing cost analysis to control resource usage in this context. Moreover, since the (rather complex) analysis phase is replaced by a simpler, efficient checking process at the code consumer side, we believe that our abstract interpretation-based approach to proof-carrying code becomes practically applicable to this kind of systems.

Constraint-based runtime prediction of SLA violations in service orchestrations

Service compositions put together loosely-coupled component services to perform more complex, higher level, or cross-organizational tasks in a platform-independent manner. Quality-of-Service (QoS) properties, such as execution time, availability, or cost, are critical for their usability, and permissible boundaries for their values are defined in Service Level Agreements (SLAs). We propose a method whereby constraints that model SLA conformance and violation are derived at any given point of the execution of a service composition. These constraints are generated using the structure of the composition and properties of the component services, which can be either known or empirically measured. Violation of these constraints means that the corresponding scenario is unfeasible, while satisfaction gives values for the constrained variables (start / end times for activities, or number of loop iterations) which make the scenario possible. These results can be used to perform optimized service matching or trigger preventive adaptation or healing.

An abstract machine based execution model for computer architecture design and efficient implementation of logic programs in parallel.

The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs.

Improving probabilistic flood forecasting through a data assimilation scheme based on genetic programming

Opportunities offered by high performance computing provide a significant degree of promise in the enhancement of the performance of real-time flood forecasting systems. In this paper, a real-time framework for probabilistic flood forecasting through data assimilation is presented. The distributed rainfall-runoff real-time interactive basin simulator (RIBS) model is selected to simulate the hydrological process in the basin. Although the RIBS model is deterministic, it is run in a probabilistic way through the results of calibration developed in a previous work performed by the authors that identifies the probability distribution functions that best characterise the most relevant model parameters. Adaptive techniques improve the result of flood forecasts because the model can be adapted to observations in real time as new information is available. The new adaptive forecast model based on genetic programming as a data assimilation technique is compared with the previously developed flood forecast model based on the calibration results. Both models are probabilistic as they generate an ensemble of hydrographs, taking the different uncertainties inherent in any forecast process into account. The Manzanares River basin was selected as a case study, with the process being computationally intensive as it requires simulation of many replicas of the ensemble in real time.

Contribución al estudio del criptoanálisis y diseño de los criptosistemas caóticos

The extraordinary increase of new information technologies, the development of Internet, the electronic commerce, the e-government, mobile telephony and future cloud computing and storage, have provided great benefits in all areas of society. Besides these, there are new challenges for the protection of information, such as the loss of confidentiality and integrity of electronic documents. Cryptography plays a key role by providing the necessary tools to ensure the safety of these new media. It is imperative to intensify the research in this area, to meet the growing demand for new secure cryptographic techniques. The theory of chaotic nonlinear dynamical systems and the theory of cryptography give rise to the chaotic cryptography, which is the field of study of this thesis. The link between cryptography and chaotic systems is still subject of intense study. The combination of apparently stochastic behavior, the properties of sensitivity to initial conditions and parameters, ergodicity, mixing, and the fact that periodic points are dense, suggests that chaotic orbits resemble random sequences. This fact, and the ability to synchronize multiple chaotic systems, initially described by Pecora and Carroll, has generated an avalanche of research papers that relate cryptography and chaos. The chaotic cryptography addresses two fundamental design paradigms. In the first paradigm, chaotic cryptosystems are designed using continuous time, mainly based on chaotic synchronization techniques; they are implemented with analog circuits or by computer simulation. In the second paradigm, chaotic cryptosystems are constructed using discrete time and generally do not depend on chaos synchronization techniques. The contributions in this thesis involve three aspects about chaotic cryptography. The first one is a theoretical analysis of the geometric properties of some of the most employed chaotic attractors for the design of chaotic cryptosystems. The second one is the cryptanalysis of continuos chaotic cryptosystems and finally concludes with three new designs of cryptographically secure chaotic pseudorandom generators. The main accomplishments contained in this thesis are: v Development of a method for determining the parameters of some double scroll chaotic systems, including Lorenz system and Chua’s circuit. First, some geometrical characteristics of chaotic system have been used to reduce the search space of parameters. Next, a scheme based on the synchronization of chaotic systems was built. The geometric properties have been employed as matching criterion, to determine the values of the parameters with the desired accuracy. The method is not affected by a moderate amount of noise in the waveform. The proposed method has been applied to find security flaws in the continuous chaotic encryption systems. Based on previous results, the chaotic ciphers proposed by Wang and Bu and those proposed by Xu and Li are cryptanalyzed. We propose some solutions to improve the cryptosystems, although very limited because these systems are not suitable for use in cryptography. Development of a method for determining the parameters of the Lorenz system, when it is used in the design of two-channel cryptosystem. The method uses the geometric properties of the Lorenz system. The search space of parameters has been reduced. Next, the parameters have been accurately determined from the ciphertext. The method has been applied to cryptanalysis of an encryption scheme proposed by Jiang. In 2005, Gunay et al. proposed a chaotic encryption system based on a cellular neural network implementation of Chua’s circuit. This scheme has been cryptanalyzed. Some gaps in security design have been identified. Based on the theoretical results of digital chaotic systems and cryptanalysis of several chaotic ciphers recently proposed, a family of pseudorandom generators has been designed using finite precision. The design is based on the coupling of several piecewise linear chaotic maps. Based on the above results a new family of chaotic pseudorandom generators named Trident has been designed. These generators have been specially designed to meet the needs of real-time encryption of mobile technology. According to the above results, this thesis proposes another family of pseudorandom generators called Trifork. These generators are based on a combination of perturbed Lagged Fibonacci generators. This family of generators is cryptographically secure and suitable for use in real-time encryption. Detailed analysis shows that the proposed pseudorandom generator can provide fast encryption speed and a high level of security, at the same time. El extraordinario auge de las nuevas tecnologías de la información, el desarrollo de Internet, el comercio electrónico, la administración electrónica, la telefonía móvil y la futura computación y almacenamiento en la nube, han proporcionado grandes beneficios en todos los ámbitos de la sociedad. Junto a éstos, se presentan nuevos retos para la protección de la información, como la suplantación de personalidad y la pérdida de la confidencialidad e integridad de los documentos electrónicos. La criptografía juega un papel fundamental aportando las herramientas necesarias para garantizar la seguridad de estos nuevos medios, pero es imperativo intensificar la investigación en este ámbito para dar respuesta a la demanda creciente de nuevas técnicas criptográficas seguras. La teoría de los sistemas dinámicos no lineales junto a la criptografía dan lugar a la ((criptografía caótica)), que es el campo de estudio de esta tesis. El vínculo entre la criptografía y los sistemas caóticos continúa siendo objeto de un intenso estudio. La combinación del comportamiento aparentemente estocástico, las propiedades de sensibilidad a las condiciones iniciales y a los parámetros, la ergodicidad, la mezcla, y que los puntos periódicos sean densos asemejan las órbitas caóticas a secuencias aleatorias, lo que supone su potencial utilización en el enmascaramiento de mensajes. Este hecho, junto a la posibilidad de sincronizar varios sistemas caóticos descrita inicialmente en los trabajos de Pecora y Carroll, ha generado una avalancha de trabajos de investigación donde se plantean muchas ideas sobre la forma de realizar sistemas de comunicaciones seguros, relacionando así la criptografía y el caos. La criptografía caótica aborda dos paradigmas de diseño fundamentales. En el primero, los criptosistemas caóticos se diseñan utilizando circuitos analógicos, principalmente basados en las técnicas de sincronización caótica; en el segundo, los criptosistemas caóticos se construyen en circuitos discretos u ordenadores, y generalmente no dependen de las técnicas de sincronización del caos. Nuestra contribución en esta tesis implica tres aspectos sobre el cifrado caótico. En primer lugar, se realiza un análisis teórico de las propiedades geométricas de algunos de los sistemas caóticos más empleados en el diseño de criptosistemas caóticos vii continuos; en segundo lugar, se realiza el criptoanálisis de cifrados caóticos continuos basados en el análisis anterior; y, finalmente, se realizan tres nuevas propuestas de diseño de generadores de secuencias pseudoaleatorias criptográficamente seguros y rápidos. La primera parte de esta memoria realiza un análisis crítico acerca de la seguridad de los criptosistemas caóticos, llegando a la conclusión de que la gran mayoría de los algoritmos de cifrado caóticos continuos —ya sean realizados físicamente o programados numéricamente— tienen serios inconvenientes para proteger la confidencialidad de la información ya que son inseguros e ineficientes. Asimismo una gran parte de los criptosistemas caóticos discretos propuestos se consideran inseguros y otros no han sido atacados por lo que se considera necesario más trabajo de criptoanálisis. Esta parte concluye señalando las principales debilidades encontradas en los criptosistemas analizados y algunas recomendaciones para su mejora. En la segunda parte se diseña un método de criptoanálisis que permite la identificaci ón de los parámetros, que en general forman parte de la clave, de algoritmos de cifrado basados en sistemas caóticos de Lorenz y similares, que utilizan los esquemas de sincronización excitador-respuesta. Este método se basa en algunas características geométricas del atractor de Lorenz. El método diseñado se ha empleado para criptoanalizar eficientemente tres algoritmos de cifrado. Finalmente se realiza el criptoanálisis de otros dos esquemas de cifrado propuestos recientemente. La tercera parte de la tesis abarca el diseño de generadores de secuencias pseudoaleatorias criptográficamente seguras, basadas en aplicaciones caóticas, realizando las pruebas estadísticas, que corroboran las propiedades de aleatoriedad. Estos generadores pueden ser utilizados en el desarrollo de sistemas de cifrado en flujo y para cubrir las necesidades del cifrado en tiempo real. Una cuestión importante en el diseño de sistemas de cifrado discreto caótico es la degradación dinámica debida a la precisión finita; sin embargo, la mayoría de los diseñadores de sistemas de cifrado discreto caótico no ha considerado seriamente este aspecto. En esta tesis se hace hincapié en la importancia de esta cuestión y se contribuye a su esclarecimiento con algunas consideraciones iniciales. Ya que las cuestiones teóricas sobre la dinámica de la degradación de los sistemas caóticos digitales no ha sido totalmente resuelta, en este trabajo utilizamos algunas soluciones prácticas para evitar esta dificultad teórica. Entre las técnicas posibles, se proponen y evalúan varias soluciones, como operaciones de rotación de bits y desplazamiento de bits, que combinadas con la variación dinámica de parámetros y con la perturbación cruzada, proporcionan un excelente remedio al problema de la degradación dinámica. Además de los problemas de seguridad sobre la degradación dinámica, muchos criptosistemas se rompen debido a su diseño descuidado, no a causa de los defectos esenciales de los sistemas caóticos digitales. Este hecho se ha tomado en cuenta en esta tesis y se ha logrado el diseño de generadores pseudoaleatorios caóticos criptogr áficamente seguros.

User-independent accelerometer-based gesture recognition for mobile devices

Many mobile devices embed nowadays inertial sensors. This enables new forms of human-computer interaction through the use of gestures (movements performed with the mobile device) as a way of communication. This paper presents an accelerometer-based gesture recognition system for mobile devices which is able to recognize a collection of 10 different hand gestures. The system was conceived to be light and to operate in a user -independent manner in real time. The recognition system was implemented in a smart phone and evaluated through a collection of user tests, which showed a recognition accuracy similar to other state-of-the art techniques and a lower computational complexity. The system was also used to build a human -robot interface that enables controlling a wheeled robot with the gestures made with the mobile phone.

Ubiquitous green computing techniques for high demand applications in smart environments

Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in WSNs infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the WSN infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

Micro-scale habitat associations of woody plants in a neotropical cloud forest

Species?habitat associations may contribute to the maintenance of species richness in tropical forests, but previous research has been conducted almost exclusively in lowland forests and has emphasized the importance of topography and edaphic conditions. Is the distribution of woody plant species in a Peruvian cloud forest determined by microhabitat conditions? What is the role of environmental characteristics and forest structure in habitat partitioning in a tropical cloud forest? We examined species?habitat associations in three 1-ha plots using the torus-translation method. We used three different criteria to define habitats for habitat partitioning analyses, based on microtopography, forest structure and both sets of factors. The number of species associated either positively or negatively with each habitat was assessed. Habitats defined on the basis of environmental conditions and forest structure discriminated a greater number of positive and negative associations at the scale of our analyses in a tropical cloud forest. Both topographic conditions and forest structure contribute to small-scale microhabitat partitioning of woody plant species in a Peruvian tropical cloud forest. Nevertheless, canopy species were most correlated with the distribution of environmental variables, while understorey species displayed associations with forest structure.

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro.

Assessing user bias in affect detection within context-based spoken dialog systems

This paper presents an empirical evidence of user bias within a laboratory-oriented evaluation of a Spoken Dialog System. Specifically, we addressed user bias in their satisfaction judgements. We question the reliability of this data for modeling user emotion, focusing on contentment and frustration in a spoken dialog system. This bias is detected through machine learning experiments that were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. The target used was the satisfaction rating and the predictors were conversational/dialog features. Our results indicated that standard classifiers were significantly more successful in discriminating frustration and contentment and the intensities of these emotions (reflected by user satisfaction ratings) from annotator data than from user data. Indirectly, the results showed that conversational features are reliable predictors of the two abovementioned emotions.