Monitoring and debugging distributed systems is inherently a difficult problem. Events collected during the execution of distributed systems can enable developers to diagnose and fix faults. Process-time diagrams are normally used to view the relationships between the events and understand the interaction between processes over time. A major difficulty with analyzing these sets of events is that they are usually very large. Therefore, being able to search through the event-data sets can enable users to get to points of interest quickly and find out if patterns in the dataset represent the expected behaviour of the system. A lot of research work has been done to improve the search algorithm for finding event-patterns in large partial-order datasets. In this thesis, we improve on this work by parallelizing the search algorithm. This is useful as many computers these days have more than one core or processor. Therefore, it makes sense to exploit this available computing power as part of an effort to improve the speed of the algorithm. The search problem itself can be modeled as a Constraint Satisfaction Problem (CSP). We develop a simple and efficient way of generating tasks (to be executed by the cores) that guarantees that no two cores will ever repeat the same work-effort during the search. Our approach is generic and can be applied to any CSP consisting of a large domain space. We also implement an efficient dynamic work-stealing strategy that ensures the cores are kept busy throughout the execution of the parallel algorithm. We evaluate the efficiency and scalability of our algorithm through experiments and show that we can achieve efficiencies of up to 80% on a 24-core machine.

Ladner’s theorem states that if P ≠ NP, then there are problems in NP that are neither in P nor NP-complete. Csp(Γ) is a class of problems containing many well-studied combinatorial problems in NP. Csp(Γ) problems are of the form: given a set of variables constrained by a set of constraints from the set of allowed constraints Γ, is there an assignment to the variables satisfying all constraints? A famous, and in the light of Ladner’s theorem, surprising conjecture states that there is a complexity dichotomy for Csp(Γ); that is, for any fixed finite Γ, the Csp(Γ) problem is either in P or NP-complete. In this thesis we focus on problems expressible in the Csp(Γ) framework with different computational goals, such as: counting the number of solutions, deciding whether two sets of constraints have the same set of solutions, deciding whether all minimal solutions of a set of constraints satisfies an additional constraint etc. By doing so, we capture a host of problems ranging from fundamental problems in nonmonotonic logics, such as abduction and circumscription, to problems regarding the equivalence of systems of linear equations. For several of these classes of problem, we are able to give complete complexity classifications and rule out the possibility of problems of intermediate complexity. For example, we prove that the inference problem in propositional variable circumscription, parameterized by the set of allowed constraints Γ, is either in P, coNP-complete, or ΠP/2-complete. As a by-product of these classifications, new tractable cases and hardness results for well-studied problems are discovered. The techniques we use to obtain these complexity classifications are to a large extent based on connections between algebraic clone theory and the complexity of Csp(Γ). We are able to extend these powerful algebraic techniques to several of the problems studied in this thesis. Hence, this thesis also contributes to the understanding of when these algebraic techniques are applicable and not.

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19117号 / 情博第563号 / 新制||情||99(附属図書館) / 32068 / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 石田 亨, 教授 吉川 正俊, 教授 河原 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Cette thèse se situe dans le contexte de la programmation par contraintes (CP). Plus précisément, nous nous sommes intéressés au problème de satisfaction de contraintes pondérées (WCSP). De nombreuses approches ont été proposées pour traiter ce problème d’optimisation. Les méthodes les plus efficaces utilisent des cohérences locales souples sophistiquées comme par exemple la cohérence d’arc directionnelle complète FDAC∗, la cohérence d’arc directionnelle existentielle EDAC∗, etc. Établies grâce à des opérations de transferts de coût préservant l’équivalence des réseaux, l’utilisation de ces cohérences permet généralement d’accélérer la résolution en réduisant l’espace de recherche via la suppression de valeurs et le calcul de bornes inférieures utiles en pratique. Cependant, l’utilisation de ces méthodes pose un problème lorsque l’arité des contraintes augmente de manière significative. L’efficacité des techniques du cadre du problème de satisfaction de contraintes (CSP) étant avérée, nous pensons que l’intégration de techniques CSP peut être très utile à la résolution d’instances WCSP. Dans cette thèse, nous proposons tout d’abord un algorithme de filtrage établissant la cohérence d’arc souple généralisée GAC∗ sur des contraintes tables souples de grande arité. Cette approche combine la technique de réduction tabulaire simple (STR), issue du cadre CSP, et le principe de transfert de coûts. Notre approche qui est polynomiale calcule efficacement pour chaque valeur les coûts minimaux dans les tuples explicites et implicites des contraintes tables souples. Ces coûts minimaux sont ensuite utilisés pour transférer les coûts afin d’établir GAC∗. Dans un second temps, nous proposons une approche alternative aux méthodes de résolution habituelles du problème WCSP. Elle consiste à résoudre une instance WCSP en résolvant une séquence d’instances CSP classiques obtenues depuis cette instance WCSP. À partir d’une instance CSP dans laquelle toutes les contraintes de l’instanceWCSP d’origine sont durcies au maximum, les instances CSP suivantes correspondent à un relâchement progressif de contraintes de l’instance WCSP déterminées par l’extraction de noyaux insatisfaisables minimaux (MUC) depuis les réseaux insatisfaisables de la séquence. Nos résultats expérimentaux montrent que notre première approche est compétitive avec l’état de l’art, tandis que la deuxième représente une approche alternative aux méthodes de résolutionhabituelles d’instances WCSP. / This thesis is in the context of constraint programming (CP). Specifically, we are interested in the Weighted Constraint Satisfaction Problem (WCSP). Many approaches have been proposed to handle this optimization problem. The most effective methods use sophisticated soft local consistencies such as, for example, full directional arc consistency FDAC∗, existential directional arc consistency EDAC∗, etc. Established by equivalence preserving transformations (cost transfer operations), the use of these consistencies generally allows both to accelerate the resolution by reducing the search space through the elimination of values and to compute lower bounds useful in practice. However, these methods reach theirlimits when the arity of constraints increases significantly. The techniques of the Constraint Satisfaction Problem framework (CSP) having proved efficienty, we believe that the integration of CSP techniques can be very useful for solving WCSP instances. In this thesis, we first propose a filtering algorithm to enforce a soft version of generalized arc consistency (GAC∗) on soft table constraints of large arity. This approach combines the techniques of simple tabular reduction (STR), from the CSP framework, with the techniques of cost transfer. Our approach, proved polynomial, efficiently calculates for each value the minimum cost of the explicit and implicit tuples from soft table constraints. The minimum costs are thenused to transfer costs to establish GAC∗. In a second step, we propose an alternative approach to the usual techniques to solve WCSP. The principle is to solve a WCSP instance by solving a sequence of classical CSP instances obtained from this WCSP instance. From a CSP instance containing all the constraints hardened to the maximum from the WCSP instance, the next CSP instances correspond to a progressive relaxation of constraints defined by extraction of minimal unsatisfiable cores (MUC) from unsatisfiable networks of the sequence. Our experimental results show that our first approach is competitive with the state-of-the-art, whereas the second one represents an alternative approach to the usual methods to solve WCSP instances.

Nowadays, assembly robots are increasingly used in the manufacturing industry to replace or collaborate with human labors. This is the goal of the dual arm assembly robot developed by ABB. With the rapid upgrading in consumer electronics products, the lifetime of an assembly line could be only a few months. However, even for experienced programmers, to manually construct a good enough assembly sequence is time consuming, and the quality of the generated assembly sequence is not guaranteed. Moreover, a good robot assembly sequence is important to the throughput of an assembly line. For dual arm robots, it is also important to obtain a balance between the two arms, as well as handling scheduling conflicts and avoiding collisions in a crowded environment. In this master thesis, a program is produced to automatically generate the optimal assembly sequence for a class of real-world assembly cases. The solution also takes the layout of the assembly cell into account, thus constructing the best combination of cell layout, workload balancing, task sequence and task scheduling. The program is implemented using Google OR-Tools – an open-source support library for combinatorial optimization. A customized search strategy is proposed and a comparison between this strategy and the built-in search strategy of Google OR-Tools is done. The result shows that the used approach is effective for the problem study case. It takes about 4 minutes to find the optimal solution and 32 minutes to prove its optimality. In addition, the result also shows that the customized search strategy works consistently with good performance for different problem cases. Moreover, the customized strategy is more efficient than built-in search strategy in many cases. / Numera används monteringsrobotar alltmer inom tillverkningsindustrin för att ersätta eller samarbeta med människor. Detta är måluppgiften för den tvåarmiga monteringsroboten, YuMi, som utvecklats av ABB. Med den korta produktlivslängden för hemelektronikprodukter kan livslängden för en monteringslinje vara ett fåtal månader. Även för erfarna robotprogrammerare är det svårt och tidsödande att manuellt konstruera en tillräckligt bra monteringsordning, och dessutom kan resultatets kvalitet inte garanteras. En bra monteringsordning är nödvändig för genomströmningen i en monteringslinje. För tvåarmiga robotar, är det också viktigt att få en balans mellan de två armarna, samt hantering av schemakrockar och undvika kollisioner i en trång miljö. I detta examensarbete har ett program skrivits, som automatiskt genererar optimala lösningar för en klass av verkliga monteringsfall. Lösningen tar hänsyn till utformningen av monteringscellen och arrangerar cellen på bästa sätt, balanserar arbetsbelastningen, ordnar och tidsbestämmer uppgifter. Programmet använder sig av Google OR-Tools – ett öppet kodbibliotek för kombinatorisk optimering. Dessutom föreslås en skräddarsydd sökstrategi, som jämförs med Google OR-Tools inbyggda sökstrategi. Resultatet visar att den använda metoden är effektiv för problemtypen. Det tar ungefär 4 minuter att hitta den optimala lösningen och 32 minuter för att bevisa optimalitet. Dessutom visar resultatet att den anpassade sökstrategin konsekvent har en bra prestanda för olika problemfall. Dessutom är den anpassade strategin effektivare än den inbyggda sökstrategin i många fall.

As reações químicas que resultam da expressão de genes são complexas e ainda não são total- mente compreendidas. Sabe-se que os genes enviam, recebem, e processam informações formando uma complexa rede de comunicação, mas a arquitetura e dinâmica destas redes não são totalmente conhecidas. Dessa forma, um problema importante é determinar como os genes se relacionam dentro da célula. Esse processo de determinar o relacionamento entre os genes é conhecido como inferência de redes gênicas. Uma das formas para representar o relacionamento entre os genes é usar modelos matemáticos e computacionais de Redes Gênicas. Em especial, um dos modelos de grande interesse é o de Redes Booleanas (BN - do inglês Boolean Networks), no qual os genes podem assumir dois estados, ativo ou inativo, se estão, respectivamente, expressos ou não. Estes estados podem variar ao longo do tempo, dependendo de como os genes se relacionam. Nosso interesse está em estudar um caso particular deste modelo, conhecido como Redes Booleanas Limiarizadas, onde apenas uma classe de funções booleanas é utilizada para construir as BNs. Para inferir as Redes Booleanas Limiarizadas, usamos um algoritmo constituído de dois passos. Primeiro, usamos o arcabouço do Problema de Satisfação de Restrições (CSP - do inglês Constraint Satisfaction Problem) para inferir conjuntos de soluções consistentes com uma dada série temporal de um conjunto de genes. Em seguida analisamos o comportamento dinâmico das soluções encon- tradas , filtrando conjuntos de soluções de maior interesse para testes práticos em laboratório. Usando o arcabouço do CSP, construímos um solver, usando a biblioteca Gecode,1 para inferência de redes consistentes, usando como entrada uma série temporal oriunda de dados de microarrays. Em seguida, através da simulação da dinâmica de uma amostra das redes encontradas no passo anterior, fomos capazes de determinar algumas restrições interessantes para filtrar o conjunto de redes. Aplicamos o nosso método para três conjuntos de dados: dois artificiais, e para validação, usamos uma série temporal de uma rede artificial conhecida na literatura. Com isso fomos capazes de inferir conjuntos de redes gênicas de possível interesse para testes em laboratório. / The chemical reactions that result in gene expression are complex and not yet fully understood. It is known that genes send, receive and process information to form a complex network of com- munication, but the architecture and dynamics of these networks are not fully known. Thus, one major problem is to determine how genes are linked within the cell. This process of determining the relationship between genes is known as inference of genetic networks. One way to represent the relationship between genes is to use mathematical and computer models of genetic networks. In particular, one of the models of great interest are Boolean Networks (BN), in which genes can take two states, active or inactive, if they are, respectively, expressed or not. These states may vary over time, depending on how genes are related. Our interest is in studying a case of this particular model, known as thresholded Boolean networks, where only one class of Boolean functions is used to build the GNs. To infer the thresholded Boolean networks, we use an algorithm that consists of two steps. First, we use the framework of Constraint Satisfaction Problem (CSP) to infer sets of solutions consistent with a time series of a given set of genes. Then analyze the dynamic behavior of the solutions, filtering sets of solutions with interest for practical tests in the laboratory. Using the framework of the CSP, we constructed a solver, using the library Gecode, 2 for in- ference of consistent networks, using as input a time series arising from microarrays data. Then, by simulating the dynamics of a sample of networks found in the previous step, we were able to determine some interesting constraints to filter the set of networks. We apply our method to three datasets: two artificial, and for validation, we use a time series of an artificial network known from literature. Thus we were able to infer genetic networks sets of possible interest for laboratory tests.

Facing global and dynamic competition environment, companies have to collaborate with other companies instead of struggle alone to optimize performance of supply chain. In a distributed supply chain structure, it is an important issue for companies to coordinate seamlessly to effectively fulfill customer orders. In this thesis, we seek to propose a fast and flexible method to solve the order fulfillment scheduling conflicts among partners in a supply chain. Due to the risk of exposing trade secrets and the cost of gathering information, the centralized constraint satisfaction mechanism is infeasible to handle distributed scheduling problem in real world environment. Moreover, the distributed constraints satisfaction model just focuses on finding a globally executable order fulfillment schedule. Therefore, we propose an agent-based distributed coordination mechanism that integrates negotiation with generic algorithm. We chose the mold manufacturing industry as an example and conducted experiments to evaluate the performance of the proposed mechanism and to compare with other benchmark methods proposed by researchers prior to this study. The experimental results indicate that the distributed coordination mechanism we proposed is a feasible approach to solve the order fulfillment scheduling conflicts in outsourcing activities in a supply chain.

Web service composition is an inevitable aspect of web services technology, which solves complex problems by combining available basic services and ordering them to best suit the problem requirements. Automatic composition gives us flexibility of selecting best candidate services at composition time, this would require the user to define the resource allocation constraints for selecting and composing candidate web services. Resource allocation constraints define restrictions on how to allocate resources, and scheduling under resource allocation constraints to provide proper resource allocation to tasks. In this work, web service composition system named as CWSF (Composite Web Service Framework) constructed for users to define a workflow system in which a rich set of constraints can be defined on web services. On the contrary many technologies and studies, CWSF provides a user-friendly environment for modeling web service composition system. The output of the framework is the scheduling of web service composition in which how and when web services are executed are defined. With this work, a language, CWSL is defined to describe workflow, resource allocation constraints, selection and discovery rules of web services and associated semantic information. An important property of CWSF system is converting web service composition problem into a constraint satisfaction problem to find the best solution that meet the all criteria defined by user. Furthermore, CWSF has ability to display other possible solutions to provides users flexibility. This study also includes semantic matching and mapping facilities for service discovery.

Les acides ribonucléiques (ARN) forment des structures tri-dimensionnelles complexes stabilisées par la formation de la structure secondaire (2D), elle-même formée de paires de bases. Plusieurs méthodes computationnelles ont été créées dans les dernières années afin de prédire la structure 2D d’ARNs, en partant de la séquence. Afin de simplifier le calcul, ces méthodes appliquent généralement des restrictions sur le type de paire de bases et la topologie des structures 2D prédites. Ces restrictions font en sorte qu’il est parfois difficile de savoir à quel point la totalité des paires de bases peut être représentée par ces structures 2D restreintes. MC-Unfold fut créé afin de trouver les structures 2D restreintes qui pourraient être associées à une structure secondaire complète, en fonction des restrictions communément utilisées par les méthodes de prédiction de structure secondaire. Un ensemble de 321 monomères d’ARN totalisant plus de 4223 structures fut assemblé afin d’évaluer les méthodes de prédiction de structure 2D. La majorité de ces structures ont été déterminées par résonance magnétique nucléaire et crystallographie aux rayons X. Ces structures ont été dépliés par MC-Unfold et les structures résultantes ont été comparées à celles prédites par les méthodes de prédiction. La performance de MC-Unfold sur un ensemble de structures expérimentales est encourageante. En moins de 5 minutes, 96% des 227 structures ont été complètement dépliées, le reste des structures étant trop complexes pour être déplié rapidement. Pour ce qui est des méthodes de prédiction de structure 2D, les résultats indiquent qu’elles sont capable de prédire avec un certain succès les structures expérimentales, particulièrement les petites molécules. Toutefois, si on considère les structures larges ou contenant des pseudo-noeuds, les résultats sont généralement défavorables. Les résultats obtenus indiquent que les méthodes de prédiction de structure 2D devraient être utilisées avec prudence, particulièrement pour de larges molécules. / Ribonucleic acids (RNA) adopt complex three dimensional structures which are stabilized by the formation of base pairs, also known as the secondary (2D) structure. Predicting where and how many of these interactions occur has been the focus of many computational methods called 2D structure prediction algorithms. These methods disregard some interactions, which makes it difficult to know how well a 2D structure represents an RNA structure, especially when large amounts of base pairs are ignored. MC-Unfold was created to remove interactions violating the assumptions used by prediction methods. This process, named unfolding, extends previous planarization and pseudoknot removal methods. To evaluate how well computational methods can predict experimental structures, a set of 321 RNA monomers corresponding to more than 4223 experimental structures was acquired. These structures were mostly determined using nuclear magnetic resonance and X-ray crystallography. MC-Unfold was used to remove interactions the prediction algorithms were not expected to predict. These structures were then compared with the structured predicted. MC-Unfold performed very well on the test set it was given. In less than five minutes, 96% of the 227 structure could be exhaustively unfolded. The few remaining structures are very large and could not be unfolded in reasonable time. MC-Unfold is therefore a practical alternative to the current methods. As for the evaluation of prediction methods, MC-Unfold demonstrated that the computational methods do find experimental structures, especially for small molecules. However, when considering large or pseudoknotted molecules, the results are not so encouraging. As a consequence, 2D structure prediction methods should be used with caution, especially for large structures.

For a finite relational structure A, the Constraint Satisfaction Problem with template A, or CSP(A), is the problem of deciding whether an input relational structure X admits a homomorphism to A. The CSP dichotomy conjecture of Feder and Vardi states that for any A, CSP(A) is either in P or NP-complete. In the first part we present the algebraic approach to CSP and summarize known results about CSP for digraphs, also known as the H-coloring problem. In the second part we study a class of oriented trees called special polyads. Using the algebraic approach we confirm the dichotomy conjecture for special polyads. We provide a finer description of the tractable cases and give a construction of a special polyad T such that CSP(T) is tractable, but T does not have width 1 and admits no near-unanimity polymorphisms.