Combined static and dynamic assertion-based debugging of constraint logic programs

We propose a general framework for assertion-based debugging of constraint logic programs. Assertions are linguistic constructions for expressing properties of programs. We define several assertion schemas for writing (partial) specifications for constraint logic programs using quite general properties, including user-defined programs. The framework is aimed at detecting deviations of the program behavior (symptoms) with respect to the given assertions, either at compile-time (i.e., statically) or run-time (i.e., dynamically). We provide techniques for using information from global analysis both to detect at compile-time assertions which do not hold in at least one of the possible executions (i.e., static symptoms) and assertions which hold for all possible executions (i.e., statically proved assertions). We also provide program transformations which introduce tests in the program for checking at run-time those assertions whose status cannot be determined at compile-time. Both the static and the dynamic checking are provably safe in the sense that all errors flagged are definite violations of the pecifications. Finally, we report briefly on the currently implemented instances of the generic framework.

A framework for assertion-based debugging in constraint logic programming

We propose a general framework for assertion-based debugging of constraint logic programs. Assertions are linguistic constructions which allow expressing properties of programs. We define assertion schemas which allow writing (partial) specifications for constraint logic programs using quite general properties, including user-defined programs. The framework is aimed at detecting deviations of the program behavior (symptoms) with respect to the given assertions, either at compile-time or run-time. We provide techniques for using information from global analysis both to detect at compile-time assertions which do not hold in at least one of the possible executions (i.e., static symptoms) and assertions which hold for all possible executions (i.e., statically proved assertions). We also provide program transformations which introduce tests in the program for checking at run-time those assertions whose status cannot be determined at compile-time. Both the static and the dynamic checking are provably safe in the sense that all errors flagged are definite violations of the specifications. Finally, we report on an implemented instance of the assertion language and framework.

Towards a concurrent semantics-based analysis of CC and CLP. principles and practice of constraint programming

Abstract is not available.

Automatic parallelization of irregular and pointer-based computations: perspectives from logic and constraint programming

Irregular computations pose some of the most interesting and challenging problems in automatic parallelization. Irregularity appears in certain kinds of numerical problems and is pervasive in symbolic applications. Such computations often use dynamic data structures which make heavy use of pointers. This complicates all the steps of a parallelizing compiler, from independence detection to task partitioning and placement. In the past decade there has been significant progress in the development of parallelizing compilers for logic programming and, more recently, constraint programming. The typical applications of these paradigms frequently involve irregular computations, which arguably makes the techniques used in these compilers potentially interesting. In this paper we introduce in a tutorial way some of the problems faced by parallelizing compilers for logic and constraint programs. These include the need for inter-procedural pointer aliasing analysis for independence detection and having to manage speculative and irregular computations through task granularity control and dynamic task allocation. We also provide pointers to some of the progress made in these áreas. In the associated talk we demónstrate representatives of several generations of these parallelizing compilers.

A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtopping

Sophisticated security verification on routing repaired balanced cell-based dual-rail logic against side channel analysis

Conventional dual-rail precharge logic suffers from difficult implementations of dual-rail structure for obtaining strict compensation between the counterpart rails. As a light-weight and high-speed dual-rail style, balanced cell-based dual-rail logic (BCDL) uses synchronised compound gates with global precharge signal to provide high resistance against differential power or electromagnetic analyses. BCDL can be realised from generic field programmable gate array (FPGA) design flows with constraints. However, routings still exist as concerns because of the deficient flexibility on routing control, which unfavourably results in bias between complementary nets in security-sensitive parts. In this article, based on a routing repair technique, novel verifications towards routing effect are presented. An 8 bit simplified advanced encryption processing (AES)-co-processor is executed that is constructed on block random access memory (RAM)-based BCDL in Xilinx Virtex-5 FPGAs. Since imbalanced routing are major defects in BCDL, the authors can rule out other influences and fairly quantify the security variants. A series of asymptotic correlation electromagnetic (EM) analyses are launched towards a group of circuits with consecutive routing schemes to be able to verify routing impact on side channel analyses. After repairing the non-identical routings, Mutual information analyses are executed to further validate the concrete security increase obtained from identical routing pairs in BCDL.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Chain routing:a new routing framework for the Internet based on complete orders

A new framework to perform routing at the autonomous system (AS) level is proposed here. This mechanism, called chain routing framework (CRF), uses complete orders as its main topological unit. Since complete orders are acyclic digraphs that possess a known topology, it is possible to use these acyclic structures to route consistently packets between a group of ASs. The adoption of complete orders also allows easy identification and avoidance of persistent route oscillations, eliminates the possibility of developing transient loops in paths and provides a structure that facilitates the implementation of traffic engineering. Moreover, by combining CRF with other mechanisms that implement complete orders in time, the authors propose that it is possible to design a new routing protocol, which can be more reliable and stable than the border gateway protocol. © 2011 The Institution of Engineering and Technology.

Context-Based Customization of Routing Functions for Web GIS Applications

This poster presentation features three route planning applications developed by the Florida International University GIS Center and the Geomatics program at the University of Florida, and outlines their context based differences. The first route planner has been developed for cyclists in three Florida counties, i.e. Miami Dade County, Broward County, and Palm Beach County. The second route planner computes safe pedestrian routes to schools and has been developed for Miami Dade County. The third route planner combines pre-compiled cultural/eco routes and point-to-point route planning for the City of Coral Gables. This poster highlights the differences in design (user interface) and implementation (routing options) between the three route planners as a result of a different application context and target audience.

Constraint-force-based approach of modelling compliant mechanisms: principle and application

Numerous works have been conducted on modelling basic compliant elements such as wire beams, and closed-form analytical models of most basic compliant elements have been well developed. However, the modelling of complex compliant mechanisms is still a challenging work. This paper proposes a constraint-force-based (CFB) modelling approach to model compliant mechanisms with a particular emphasis on modelling complex compliant mechanisms. The proposed CFB modelling approach can be regarded as an improved free-body- diagram (FBD) based modelling approach, and can be extended to a development of the screw-theory-based design approach. A compliant mechanism can be decomposed into rigid stages and compliant modules. A compliant module can offer elastic forces due to its deformation. Such elastic forces are regarded as variable constraint forces in the CFB modelling approach. Additionally, the CFB modelling approach defines external forces applied on a compliant mechanism as constant constraint forces. If a compliant mechanism is at static equilibrium, all the rigid stages are also at static equilibrium under the influence of the variable and constant constraint forces. Therefore, the constraint force equilibrium equations for all the rigid stages can be obtained, and the analytical model of the compliant mechanism can be derived based on the constraint force equilibrium equations. The CFB modelling approach can model a compliant mechanism linearly and nonlinearly, can obtain displacements of any points of the rigid stages, and allows external forces to be exerted on any positions of the rigid stages. Compared with the FBD based modelling approach, the CFB modelling approach does not need to identify the possible deformed configuration of a complex compliant mechanism to obtain the geometric compatibility conditions and the force equilibrium equations. Additionally, the mathematical expressions in the CFB approach have an easily understood physical meaning. Using the CFB modelling approach, the variable constraint forces of three compliant modules, a wire beam, a four-beam compliant module and an eight-beam compliant module, have been derived in this paper. Based on these variable constraint forces, the linear and non-linear models of a decoupled XYZ compliant parallel mechanism are derived, and verified by FEA simulations and experimental tests.

Clustering-based Query Routing in Cooperative Semi-structured Peer to Peer Networks

We consider the problem of resource selection in clustered Peer-to-Peer Information Retrieval (P2P IR) networks with cooperative peers. The clustered P2P IR framework presents a significant departure from general P2P IR architectures by employing clustering to ensure content coherence between resources at the resource selection layer, without disturbing document allocation. We propose that such a property could be leveraged in resource selection by adapting well-studied and popular inverted lists for centralized document retrieval. Accordingly, we propose the Inverted PeerCluster Index (IPI), an approach that adapts the inverted lists, in a straightforward manner, for resource selection in clustered P2P IR. IPI also encompasses a strikingly simple peer-specific scoring mechanism that exploits the said index for resource selection. Through an extensive empirical analysis on P2P IR testbeds, we establish that IPI competes well with the sophisticated state-of-the-art methods in virtually every parameter of interest for the resource selection task, in the context of clustered P2P IR.

A new physarum network based genetic algorithm for bandwidth-delay constrained least-cost multicast routing

Bandwidth-delay constrained least-cost multicast routing is a typical NP-complete problem. Although some swarm-based intelligent algorithms (e.g., genetic algorithm (GA)) are proposed to solve this problem, the shortcomings of local search affect the computational effectiveness. Taking the ability of building a robust network of Physarum network model (PN), a new hybrid algorithm, Physarum network-based genetic algorithm (named as PNGA), is proposed in this paper. In PNGA, an updating strategy based on PN is used for improving the crossover operator of traditional GA, in which the same parts of parent chromosomes are reserved and the new offspring by the Physarum network model is generated. In order to estimate the effectiveness of our proposed optimized strategy, some typical genetic algorithms and the proposed PNGA are compared for solving multicast routing. The experiments show that PNGA has more efficient than original GA. More importantly, the PNGA is more robustness that is very important for solving the multicast routing problem.

Domain-driven classification based on multiple criteria and multiple constraint-level programming for intelligent credit scoring

Extracting knowledge from the transaction records and the personal data of credit card holders has great profit potential for the banking industry. The challenge is to detect/predict bankrupts and to keep and recruit the profitable customers. However, grouping and targeting credit card customers by traditional data-driven mining often does not directly meet the needs of the banking industry, because data-driven mining automatically generates classification outputs that are imprecise, meaningless, and beyond users' control. In this paper, we provide a novel domain-driven classification method that takes advantage of multiple criteria and multiple constraint-level programming for intelligent credit scoring. The method involves credit scoring to produce a set of customers' scores that allows the classification results actionable and controllable by human interaction during the scoring process. Domain knowledge and experts' experience parameters are built into the criteria and constraint functions of mathematical programming and the human and machine conversation is employed to generate an efficient and precise solution. Experiments based on various data sets validated the effectiveness and efficiency of the proposed methods. © 2006 IEEE.

A new genetic algorithm based on modified Physarum network model for bandwidth-delay constrained least-cost multicast routing

A mobile ad hoc network is a kind of popular self-configuring network, in which multicast routing under the quality of service constraints, is a significant challenge. Many researchers have proved that such problem can be formulated as a NP-complete problem and proposed some swarm-based intelligent algorithms to solve the optimal solution, such as the genetic algorithm (GA), bees algorithm. However, a lower efficiency of local search ability and weak robustness still limit the computational effectiveness. Aiming to those shortcomings, a new hybrid algorithm inspired by the self-organization of Physarum, is proposed in this paper. In our algorithm, an updating scheme based on Physarum network model (PM) is used for improving the crossover operator of traditional GAs, in which the same parts of parent chromosomes are reserved and the new offspring by the PM is generated. In order to estimate the effectiveness of our proposed optimized scheme, some typical genetic algorithms and their updating algorithms (PMGAs) are compared for solving the multicast routing on four different datasets. The simulation experiments show that PMGAs are more efficient than original GAs. More importantly, the PMGAs are more robustness that is very important for solving the multicast routing problem. Moreover, a series of parameter analyses is used to find a set of better setting for realizing the maximal efficiency of our algorithm.

A multicast routing scheme for efficient safety message dissemination in VANET

Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.