Effective Iterative Techniques for Fingerprinting Design IP

Fingerprinting is an approach that assigns a unique and invisible ID to each sold instance of the intellectual property (IP). One of the key advantages fingerprinting-based intellectual property protection (IPP) has over watermarking-based IPP is the enabling of tracing stolen hardware or software. Fingerprinting schemes have been widely and effectively used to achieve this goal; however, their application domain has been restricted only to static artifacts, such as image and audio, where distinct copies can be obtained easily. In this paper, we propose the first generic fingerprinting technique that can be applied to an arbitrary synthesis (optimization or decision) or compilation problem and, therefore to hardware and software IPs. The key problem with design IP fingerprinting is that there is a need to generate a large number of structurally unique but functionally and timing identical designs. To reduce the cost of generating such distinct copies, we apply iterative optimization in an incremental fashion to solve a fingerprinted instance. Therefore, we leverage on the optimization effort already spent in obtaining previous solutions, yet we generate a uniquely fingerprinted new solution. This generic approach is the basis for developing specific fingerprinting techniques for four important problems in VLSI CAD: partitioning, graph coloring, satisfiability, and standard-cell placement. We demonstrate the effectiveness of the new fingerprinting-based IPP techniques on a number of standard benchmarks

Exact Coloring of Real-Life Graphs is Easy

Graph coloring has several important applications in VLSI CAD. Since graph coloring is NP-complete, heuristics are used to approximate the optimum solution. But heuristic solutions are typically 10% off, and as muchas 100% off, the minimum coloring. This paper shows that since real-life graphs appear to be 1-perfect, one can indeed solve them exactly for a small overhead

Arithmetic and Modularity in Declarative Languages for Knowledge Representation

The past decade has witnessed the development of many important declarative languages for knowledge representation and reasoning such as answer set programming (ASP) languages and languages that extend first-order logic. Also, since these languages depend on background solvers, the recent advancements in the efficiency of solvers has positively affected the usability of such languages. This thesis studies extensions of knowledge representation (KR) languages with arithmetical operators and methods to combine different KR languages. With respect to arithmetic in declarative KR languages, we show that existing KR languages suffer from a huge disparity between their expressiveness and their computational power. Therefore, we develop an ideal KR language that captures the complexity class NP for arithmetical search problems and guarantees universality and efficiency for solving such problems. Moreover, we introduce a framework to language-independently combine modules from different KR languages. We study complexity and expressiveness of our framework and develop algorithms to solve modular systems. We define two semantics for modular systems based on (1) a model-theoretical view and (2) an operational view on modular systems. We prove that our two semantics coincide and also develop mechanisms to approximate answers to modular systems using the operational view. We augment our algorithm these approximation mechanisms to speed up the process of solving modular system. We further generalize our modular framework with supported model semantics that disallows self-justifying models. We show that supported model semantics generalizes our two previous model-theoretical and operational semantics. We compare and contrast the expressiveness of our framework under supported model semantics with another framework for interlinking knowledge bases, i.e., multi-context systems, and prove that supported model semantics generalizes and unifies different semantics of multi-context systems. Motivated by the wide expressiveness of supported models, we also define a new supported equilibrium semantics for multi-context systems and show that supported equilibrium semantics generalizes previous semantics for multi-context systems. Furthermore, we also define supported semantics for propositional programs and show that supported model semnatics generalizes the acclaimed stable model semantics and extends the two celebrated properties of rationality and minimality of intended models beyond the scope of logic programs

Optimisation des flux de trafic aérien

Cette thèse s'inscrit dans le domaine de l'optimisation globale appliquée aux flux de trafic aérien. Le problème abordé consiste à optimiser les flux de trafic aérien sans imposer de retards au décollage. On considère tout d'abord le système existant tel quel, en cherchant à améliorer l'écoulement du trafic simplement en équilibrant les regroupements des secteurs élémentaires d'espace sur les positions de contrôle. Des méthodes déterministes (A*, Branch and bound) et un algorithme génétique sont utilisés pour répartir au mieux la charge de trafic entre les positions. Dans un deuxième temps on s'autorise à modifier la structure de l'espace aérien, en partant des flux directs origine-destination pour construire, par une méthode de partitionnement et une triangulation de Delaunay, un réseau de routes aériennes répondant à certains critères d'espacement des points de croisement. On évalue dans un troisième temps l'intérêt de séparer verticalement les flux aériens, dans leur phase de croisière. Cette évaluation porte sur le nombre et la nature des conflits détectés lors de simulations en temps accéléré, en allouant ou non des niveaux de croisières séparés. Dans un quatrième temps, on génère pour les principaux flux de trafic des trajectoires 3D complètes, séparées les unes des autres, en tenant compte de la disparité des performances des avions sur chaque flux. Deux types de stratégies sont explorées : une approche séquentielle où un algorithme A* est appliqué successivement à chaque flux dans un ordre choisi, et une approche globale où toutes les trajectoires sont considérées simultanément, en utilisant un algorithme génétique. Les algorithmes sont d'abord testés sur des cas simples avant d'être appliqués aux données réelles, en France et en Europe. Enfin, en dernier lieu, la dimension temporelle est prise en compte afin de planifier dynamiquement des trajectoires 4D non-conflictuelles pour des trains d'avions. ABSTRACT : This work belongs to the field of global optimization, applied to air traffic flows. The problem being addressed consists of optimizing air traffic flows without regulating the traffic demand. Firstly, the current system is enhanced only by considering the sector configurations of the controllers working positions. Deterministic methods (A*, Branch and bound) and a genetic algorithm are used to balance the workload between control positions, by splitting and merging airspace sectors. Secondly, we allow ourselves to modify the airspace structure. A routes network is computed from the direct origin-destination flows, with crossing points satisfying constraints of minimum distance, using a partitioning method and a Delaunay triangulation. Thirdly, the profit brought by the vertical separation of air traffic flows is assessed through fast-time simulations, by considering the nature of conflicts detected with or without a cruise level allocation. Fourthly, full 3D-trajectories are computed for the main flows, taking into account the variety of aircraft performances within each flow. Two strategies are proposed : the 1 vs. n strategy uses an A* algorithm to compute each trajectory in turn, separating the new trajectory from the previous ones, and the global strategy applies a genetic algorithm to the whole set of trajectories. Both algorithms are first tried on basic flow configurations, and then applied to real traffic data over France and Europe. Finally, the time dimension is taken into account in order to generate conflict-free 4D-trajectories for groups of aircraft following the same route